完善文档

.env.example

@@ -88,7 +88,7 @@ LOG_ROTATION_SIZE=10 MB
 # 本地单用户范围标识，当前阶段不实现多用户、组织、租户、OAuth 或 SSO
 DEFAULT_OWNER_SCOPE=local-user
 
-# 默认逻辑模型名（提示值；实际路由由神识端点目录决定）
+# 默认逻辑模型名。必须指向 config/models.yaml 中真实远程 provider 的逻辑模型
 DEFAULT_MODEL_HINT=deepseek-v4-flash
 
 # --- 管理端点和认证 ---
@@ -207,7 +207,7 @@ BIG_CYCLE_MEMORY_THRESHOLD=20
 # 两次大周天最小间隔（秒），避免频繁触发
 BIG_CYCLE_MIN_INTERVAL_SECONDS=300
 
-# 大周天候选生成所用模型（逻辑模型名；路由由神识决定）
+# 大周天候选生成所用模型（config/models.yaml 的逻辑模型名）
 BIG_CYCLE_MODEL=deepseek-v4-flash
 
 # 单次大周天生成的演化候选上限
@@ -238,7 +238,7 @@ MCP_STDIO_CALL_TIMEOUT_SECONDS=30
 # MCP stdio SIGTERM → SIGKILL 等待秒数
 MCP_STDIO_STOP_TIMEOUT_SECONDS=5
 
-# Embedding 模型逻辑名（路由由神识决定）
+# Embedding 模型逻辑名。指向 config/models.yaml 中已注册的 embedding 模型
 EMBEDDING_MODEL_HINT=bge-m3
 
 # --- 感知与导入 ---
@@ -259,12 +259,53 @@ IMPORT_ALLOWED_AUDIO_MIME_TYPES=audio/wav,audio/mpeg,audio/mp4,audio/flac
 
 
 # =====================================================================
-# 模型网关 · 神识（Go 网关统一接管，灵台不经手任何 Provider 密钥）
+# 模型网关 · 神识（LLM Provider API Keys）
 # =====================================================================
-# 模型端点目录（含 base_url / api_key / 上游模型 / 优先级）统一经神识环境变量 SHENSHI_ENDPOINTS 配置，
+# 模型名称、provider 映射、能力标签、超时、限流、价格等，统一放在 config/models.yaml 中。
-# 详见下方「神识 · 模型网关」段；旧 config/models|providers|pricing.yaml 与灵台侧各 provider
+# .env 只保存各 provider 的 URL 与 API key，避免模型策略散落在环境变量中。
-# API Key 已随 ai_provider 退役（归档于 shenshi/config/ 仅供参考）。
 
+# --- DeepSeek ---
+DEEPSEEK_API_KEY=
+DEEPSEEK_BASE_URL=https://api.deepseek.com
+
+# --- 火山方舟 / 豆包 ---
+VOLCENGINE_ARK_API_KEY=
+VOLCENGINE_ARK_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
+
+# --- 小米 MiMo ---
+XIAOMI_MIMO_API_KEY=
+XIAOMI_MIMO_BASE_URL=https://token-plan-cn.xiaomimimo.com/v1
+
+# --- OpenAI ---
+OPENAI_API_KEY=
+OPENAI_BASE_URL=https://api.openai.com/v1
+
+# --- Anthropic ---
+ANTHROPIC_API_KEY=
+ANTHROPIC_BASE_URL=https://api.anthropic.com
+
+# --- 元炁（本地推理引擎）---
+# 作为 OpenAI 兼容 provider 接入，供 bge-m3 embedding 等模型调用。
+YUANQI_BASE_URL=http://localhost:11434
+YUANQI_API_KEY=
+
+# --- 其他兼容网关预留 ---
+CUSTOM_LLM_API_KEY=
+CUSTOM_LLM_BASE_URL=
+
+# --- 模型 endpoint 池路由（高级调优项，保持默认即可正常工作）---
+# 物理 endpoint 池的 failover 与重试策略
+MODEL_ENDPOINT_POOL_ENABLED=true
+MODEL_ENDPOINT_POOL_DRY_RUN_SELECTION=false
+MODEL_ENDPOINT_POOL_EXPOSE_DEBUG_HEADERS=false
+MODEL_ENDPOINT_POOL_AGENT_FAILOVER_ENABLED=false
+MODEL_ENDPOINT_POOL_PER_ENDPOINT_MAX_RETRIES=1
+MODEL_ENDPOINT_POOL_RETRY_BASE_DELAY_SECONDS=0.25
+MODEL_ENDPOINT_POOL_RETRY_MAX_DELAY_SECONDS=2.0
+
+# 模型配置文件路径
+# 默认读取项目根目录 config/models.yaml；不存在时 fallback 到 config/models.example.yaml
+MODEL_CONFIG_PATH=../config/models.yaml
 
 
 # =====================================================================
@@ -624,41 +665,3 @@ SAFETY_POLICY_PATH=config/safety.yaml
 #   BACKEND_URL=http://localhost:8000          （本地开发，跨公网须 https://）
 #   Docker 部署由 docker-compose.app.yml 写死为 http://hunjing-backend:8000
 # 浏览器所有请求同源走 BFF（/api/proxy、/api/sse、/api/auth），客户端不需要后端地址。
-
-
-# =====================================================================
-# 神识 · 模型网关（Go，rewrite/1.0 M0） — 灵台唯一模型出口
-# =====================================================================
-# 神识服务地址；为空时灵台 Kernel 使用进程内回声桩（仅骨架验证，不出真实模型流）。
-# 本地开发：SHENSHI_BASE_URL=http://127.0.0.1:8080（先 shenshi/ 目录 `go run .`）
-# Docker 部署由 docker-compose.app.yml 写死为 http://hunjing-shenshi:8080
-SHENSHI_BASE_URL=
-# 灵台 → 神识服务令牌（两边一致）；为空时神识开发档放行不校验
-SHENSHI_SERVICE_TOKEN=
-# 神识流式调用超时（秒）
-SHENSHI_TIMEOUT_SECONDS=120.0
-# 神识服务监听端口（shenshi 服务自身）
-SHENSHI_PORT=8080
-# 神识自有库（usage_logs/byok_keys/quota_balances；未配置时进程内存储，重启即失）
-# 本地开发可留空；正式环境指向 hunjing-postgres（如 postgresql://hunjing:hunjing@hunjing-postgres:5432/hunjing_shenshi）
-SHENSHI_DATABASE_URL=
-# BYOK 主密钥（32 字节 hex 或 base64；未配置时 BYOK 功能整体禁用 fail-closed）
-# 生成示例：python3 -c "import secrets; print(secrets.token_hex(32))"
-SHENSHI_BYOK_MASTER_KEY=
-# 用户级软配额（token 口径；0 = 不限制，P0/P1 只做预算熔断不做计费）
-SHENSHI_USER_BUDGET_TOKENS=0
-# 神识出站端点目录（JSON 数组；未配置时回声桩兜底）。
-# type: openai_compatible（云厂商兼容面与元炁 http://hunjing-yuanqi:11434 共用）
-# 示例：
-# SHENSHI_ENDPOINTS=[{"type":"openai_compatible","name":"yuanqi","base_url":"http://hunjing-yuanqi:11434","model":"bge-chat","priority":100}]
-SHENSHI_ENDPOINTS=
-
-
-# =====================================================================
-# 照壁 · BFF（Fastify，rewrite/1.0 M0） — 鉴权透传 / SSE 直通
-# =====================================================================
-# 照壁监听端口
-BFF_PORT=3000
-# 照壁转发的灵台地址；本地开发默认 http://127.0.0.1:8000
-# Docker 部署由 docker-compose.app.yml 写死为 http://hunjing-backend:8000
-BACKEND_URL=http://127.0.0.1:8000

AGENTS.md

@@ -49,150 +49,211 @@ pi ：<https://github.com/earendil-works/pi>
 向量库：<https://github.com/oceanbase/seekdb>
 live-2d: <https://github.com/stevenjoezhang/live2d-widget>
 上下文压缩：<https://github.com/headroomlabs-ai/headroom>
-记忆：<https://github.com/AGI-is-going-to-arrive/Memory-Palace>，<https://github.com/Dataojitori/nocturne_memory>，<https://github.com/TencentCloud/TencentDB-Agent-Memory>,<https://github.com/riisovo/memory-trigger>
+记忆：<https://github.com/AGI-is-going-to-arrive/Memory-Palace>，<https://github.com/Dataojitori/nocturne_memory>，<https://github.com/TencentCloud/TencentDB-Agent-Memory>,<https://github.com/riisovo/memory-trigger>,<https://github.com/MemTensor/MemOS>
 成熟的相关的项目：<https://github.com/momori777/Artemis>，<https://github.com/RTGS2017/NagaAgent>，<https://github.com/AlfreScarlet/MoeChat>，<https://github.com/heshengtao/super-agent-party>，<https://github.com/MewCo-AI/mewco_ai_assistant_comm>，<https://github.com/weidu12123/Liyuan>
 deepseek-herness：<https://github.com/deepseek-ai/deepseek-harness>
-模型网关设计：<https://github.com/xgpxg/aiway>,<https://github.com/bestruirui/octopus>,<https://github.com/QuantumNous/new-api>,<https://github.com/cita-777/metapi>,<https://github.com/looplj/axonhubs>,<https://github.com/dyedd/lens>
+模型网关设计：<https://github.com/xgpxg/aiway>,<https://github.com/bestruirui/octopus>,<https://github.com/QuantumNous/new-api>,<https://github.com/cita-777/metapi>,<https://github.com/looplj/axonhub>,<https://github.com/dyedd/lens>
 
-## 完整技术栈
+## 项目定位
 
-> 魂镜服务映射（文化名登记见 `docs/contracts/contract-glossary.md` §2）：前端=琉璃镜（Next.js）；BFF=照壁（Fastify）；后端核心=灵台（Python FastAPI，六域业务+插件化运行时）；高并发 I/O 层=神识（Go 模型网关）+博闻（Go MCP 搜索）；桌面端=镜匣（Tauri 最小壳）；乾坤（Rust 沙箱）、天目（OCR）、元炁（本地推理）为独立辅助服务。详细架构见 `docs/architecture/`。
+本项目是一个面向长期运行与持续演化的 Agent 平台，核心目标是提供统一的 Agent Runtime、认知能力、工具执行、记忆、RAG、MCP、桌面端与基础设施。
 
----
+核心认知闭环：
 
-### 前端（TypeScript 主力）
+```mermaid
+flowchart LR
+    A["感知"] --> B["上下文"]
+    B --> C["记忆"]
+    C --> D["理解"]
+    D --> E["规划与推理"]
+    E --> F["决策"]
+    F --> G["工具 / 行动"]
+    G --> H["环境反馈"]
+    H --> I["反思"]
+    I --> C
+```
 
-**定位**：浏览器端 UI、状态管理、实时交互
+## 必读文档
-**技术选型**：
-Next.js 16 + React 19 + TypeScript + Tailwind CSS v4 + Zustand/Jotai + shadcn/ui + pnpm
 
-#### 核心依赖
+开始涉及架构修改前：
 
-- **实时通信**：SSE（主，接收流式文本/事件）/ WebSocket（双向协同场景）
+1. `docs/architecture/overview.md`
-- **数据请求**：TanStack Query（服务端状态管理与缓存）+ openapi-fetch（类型安全请求，类型由后端 OpenAPI 生成）
+2. `docs/agent/overview.md`
-- **可视化**：Mermaid（图表/流程图渲染）+ React Flow（流程编排与交互）/ Cytoscape.js（知识图谱交互）
+3. `docs/decisions/README.md`
-- **Markdown 渲染**：react-markdown + remark/rehype 插件体系 + Shiki（代码高亮，支持流式增量解析）
-- **长列表虚拟滚动**：@tanstack/react-virtual（大量数据高性能渲染）
-- **表单校验**：React Hook Form + Zod（类型安全的表单验证）
-- **测试**：Vitest（单元测试）+ Testing Library（组件测试）+ Playwright（E2E 测试）
-- **代码质量**：ESLint（flat config 格式）+ Prettier + Husky + lint-staged + commitlint
 
----
+涉及具体领域时，必须优先阅读对应领域文档。
 
-### BFF（TypeScript + Node.js）
+## 核心工程原则
 
-**定位**：前端聚合层、鉴权透传、响应裁剪、SSE/WebSocket 代理、类型安全桥接  
+- 能力与基础设施解耦。
-**技术选型**：  
+- Agent Runtime 不直接绑定具体数据库、向量库、图数据库或对象存储。
-Node.js 22 LTS + NestJS / Fastify + TypeScript + Zod + openapi-fetch
+- 外部能力通过 Tool Registry / MCP 接入。
+- 长期数据进入 PostgreSQL；Redis 不作为核心业务数据最终持久化层。
+- VectorStore、GraphStore、FileStorage 必须通过抽象接口访问。
+- API 以 OpenAPI 3.1 为契约。
+- 重要架构选择必须通过 ADR 记录。
+- 不为了技术复杂度而提前引入分布式基础设施。
 
-#### 核心依赖
+## Repository 结构
 
-- **HTTP 框架**：Fastify（高性能）或 NestJS（模块化结构化）
+- `apps/`：客户端与服务应用。
-- **聚合/代理**：http-proxy / undici（请求转发与合并）
+- `packages/`：共享库与 SDK。
-- **鉴权**：JWT + cookie 透传
+- `services/`：独立基础服务。
-- **日志**：pino（高性能结构化日志）
+- `docs/`：架构、设计、规范与 ADR。
-- **配置管理**：dotenv / convict（环境配置校验）
+- `tests/`：跨模块测试与评估。
-- **测试**：Vitest + supertest（API 集成测试）
+- `scripts/`：开发和运维脚本。
-- **代码质量**：ESLint + Prettier + Husky
 
----
+## Agent Runtime 规则
 
-### 后端核心（Python + uv）
+Agent Runtime 是系统核心。
 
-**定位**：业务主力、AI Agent 编排、RAG 检索
+所有 Agent Run 应具有稳定的 `run_id`，并可追踪：
-**技术选型**：
-Python 3.12+（uv 包管理）+ FastAPI + SQLAlchemy 2.0 + Alembic + Pydantic v2 + httpx + loguru + uvicorn
 
-#### 核心依赖
+`Run -> Plan -> Model Call -> Memory -> Tool Call -> Observation -> Reflection -> Result`
 
-- **任务队列**：Celery（稳定分布式任务）/ ARQ（轻量级，基于 Redis）
+Agent 不应把业务逻辑隐含在 Prompt 中；稳定规则、权限和状态应由代码或配置表达。
-- **LLM 接入**：OpenAI SDK / LiteLLM（多厂商统一接口）
-- **文档解析**：unstructured（多格式文档解析）+ pymupdf（PDF 处理）+ markitdown（Markdown 转换）
-- **Agent 引擎**：LangGraph（有状态多 Agent 编排）或 自研轻量引擎
-- **MCP 协议**：自研 MCP Client（stdio/sse 传输，接入第三方 MCP Server）
-- **记忆系统**：自研三层记忆架构（Redis 短期记忆 + PostgreSQL 长期记忆 + VectorStore 向量记忆）
-- **规划与推理**：自研 ReAct 循环 + Plan-and-Execute 模式
-- **工具系统**：自研工具注册表（装饰器注册 + Pydantic 参数校验）+ 内置工具集（文件/网页/向量/图/代码沙箱/数据库/HTTP）
-- **工具权限控制**：基于 Tauri 能力模型 + RBAC 用户角色
-- **流式输出**：SSE 事件驱动（text_delta / tool_call / tool_result / agent_thought / finish）
-- **断点续传**：Redis 缓存中间状态（支持重连恢复）
-- **向量库抽象层**：自研 VectorStore 接口 → ChromaDB（开发） / PGVector（过渡） / Milvus（生产）
-- **图数据库抽象层**：自研 GraphStore 接口 → Neo4j（开发） / NebulaGraph（生产）
-- **文件存储抽象层**：自研 FileStorage 接口 → 本地（开发） / MinIO（自建） / S3（生产）
-- **安全防护**：LLM Guard（Prompt Injection 检测）+ 自研输出审核（敏感词/隐私脱敏）
-- **审计日志**：所有工具调用记录（用户 + 时间 + 工具 + 参数 + 结果）
-- **评测框架**：DeepEval / Ragas（RAG 质量评估）
-- **调试工具**：自研 Debug Panel（推理链可视化）/ LangSmith（可选）
-- **测试**：pytest + pytest-asyncio + respx（HTTP Mock）
-- **代码质量**：Ruff（lint + format）+ mypy + pre-commit
 
----
+## Memory 规则
 
-### 桌面端（Rust + Tauri）
+采用六类逻辑记忆：
 
-**定位**：桌面客户端外壳、本地文件索引、沙箱执行、本地向量检索、离线能力
+- Working Memory
-**技术选型**：
+- Episodic Memory
-Rust（cargo 管理）+ Tauri v2 + tokio + serde + specta（TypeScript 类型导出）
+- Semantic Memory
+- Procedural Memory
+- Social Memory
+- Identity Memory
 
-#### 核心依赖
+统一通过 `Memory Manager` 访问。
 
-- **本地检索**：tantivy（全文检索）
+业务代码不得直接依赖 Redis、VectorStore 等具体实现。
-- **沙箱执行**：Tauri 进程隔离 + 权限模型（capabilities 映射为 Agent 工具授权）
-- **打包分发**：tauri-plugin-updater（自动更新）+ tauri-plugin-store（本地配置存储）
-- **前端通信**：Tauri commands（同步/异步调用）+ events（双向事件）+ specta（类型安全）
-- **代码质量**：clippy + rustfmt
 
----
+详细设计：`docs/agent/memory.md`
 
-### 高并发 I/O 层（Go）
+## Planning / Reasoning 规则
 
-**定位**：网页抓取集群、API 网关与限流、长连接转发、定时调度、轻量级数据聚合
+规划与推理采用多模式架构：
-**技术选型**：
-Go 1.25+（go mod 管理）+ Gin / Echo + colly + goquery + zap + viper
 
-#### 核心依赖
+- ReAct
+- Plan-and-Execute
+- Reflection
+- Self-Correction
+- Dynamic Replanning
 
-- **并发控制**：ants（协程池）+ golang.org/x/time/rate（限流器）
+详细设计：`docs/agent/planning.md`、`docs/agent/reasoning.md`。
-- **无头浏览器**：chromedp / rod（动态页面渲染抓取）
-- **配置与服务发现**：viper（配置管理）+ etcd（服务注册与发现，可选）
-- **可观测性**：OpenTelemetry-Go + Prometheus client
-- **测试**：testing + testify + httptest
-- **代码质量**：golangci-lint + gofumpt
 
----
+## Tool 规则
 
-### 基础设施
+所有 Agent Tool 必须：
 
-#### 数据库
+- 注册到 Tool Registry。
+- 使用结构化参数 Schema。
+- 经过权限检查。
+- 具有超时和错误处理。
+- 记录调用审计。
+- 返回统一结果结构。
 
-- **关系数据库**：PostgreSQL 16（主库，支持 pgvector 扩展）
+详细设计：`docs/tools/overview.md`
-- **缓存/消息队列**：Redis 7+（Session / 任务队列 / 限流计数器 / 短期记忆存储）
 
-#### 向量数据库
+## MCP 规则
 
-- **开发/测试**：ChromaDB（轻量快速）
+MCP 是外部工具和上下文扩展协议。
-- **生产过渡**：PostgreSQL + pgvector（减少运维复杂度）
-- **大规模生产**：Milvus（分布式向量检索）
 
-#### 图数据库
+MCP Tool 必须经过内部 Tool Adapter 和 Permission Layer，不得绕过统一权限体系。
 
-- **开发/测试**：Neo4j（社区版，易于上手）
+详细设计：`docs/mcp/overview.md`
-- **大规模生产**：NebulaGraph（分布式图数据库，高性能）
 
-#### 文件/对象存储
+## API 规则
 
-- **开发环境**：本地文件系统
+- API 使用 OpenAPI 3.1。
-- **自建生产**：MinIO（兼容 S3 协议）
+- FastAPI 负责生成服务端 Schema。
-- **云生产**：AWS S3 / 阿里云 OSS / 腾讯云 COS
+- 前端优先使用类型安全客户端。
+- SSE 用于 Agent 流式事件。
+- WebSocket 只用于确有双向实时通信需求的场景。
+- API 错误使用统一错误模型。
 
-#### 容器
+详细设计：`docs/api/overview.md`
 
-- **容器化**：Docker + Docker Compose（本地开发环境一键编排）
+## 数据访问规则
 
-#### API 契约
+- PostgreSQL：核心业务与长期结构化数据。
+- Redis：缓存、短期状态、运行态数据。
+- VectorStore：向量检索。
+- GraphStore：关系与知识图谱。
+- FileStorage：对象与文件。
+- 所有可替换基础设施通过接口隔离。
 
-- **规范**：OpenAPI 3.1（单一真源）
+## 安全规则
-- **客户端生成**：openapi-generator（生成 TypeScript / Go 客户端）
+
+安全采用纵深防御：
+
+`Authentication -> RBAC -> Tool Permission -> Sandbox -> Audit`
+
+Tauri Capabilities 与服务端 RBAC 属于不同安全边界，不得混为一谈。
+
+必须考虑：
+
+- Prompt Injection
+- Secret Leakage
+- Sensitive Data
+- Tool Abuse
+- Sandbox Escape
+- Auditability
+
+## 测试规则
+
+新增能力至少考虑：
+
+- Unit Test
+- Integration Test
+- API Test
+- Tool Test
+- Agent Workflow Test
+
+RAG / Agent 的关键能力必须增加 Evaluation，而不能只依赖普通单元测试。
+
+## 常用技术约束
+
+### Python
+
+Python 3.12+，使用 `uv` 管理依赖；Ruff + mypy。
+
+### TypeScript
+
+Next.js + React + TypeScript；pnpm；ESLint + Prettier。
+
+### Rust
+
+Tauri v2 + Tokio；rustfmt + clippy。
+
+### Go
+
+Go 1.25+；gofumpt + golangci-lint。
+
+## 文档规则
+
+架构修改必须同步修改相关 `docs/`。
+
+改变技术选择或重要架构决策时创建 ADR。
+
+不要把完整设计复制到 `AGENTS.md`；`AGENTS.md` 只保留必须影响 Agent 行为的规则和导航。
+
+## 文档导航
+
+- 总体架构：`docs/architecture/overview.md`
+- Agent：`docs/agent/overview.md`
+- Memory：`docs/agent/memory.md`
+- Planning：`docs/agent/planning.md`
+- Reasoning：`docs/agent/reasoning.md`
+- RAG：`docs/rag/overview.md`
+- Tools：`docs/tools/overview.md`
+- MCP：`docs/mcp/overview.md`
+- API：`docs/api/overview.md`
+- 数据：`docs/data/database.md`
+- 安全：`docs/security/overview.md`
+- 基础设施：`docs/infrastructure/development.md`
+- 测试：`docs/testing/strategy.md`
+- ADR：`docs/decisions/README.md`
 
 ## 文档设计
 
@@ -206,7 +267,6 @@ Go 1.25+（go mod 管理）+ Gin / Echo + colly + goquery + zap + viper
 Docker 文件放在根目录 `docker/` 下。
 容器名称以 `hunjing` 开头。
 Compose 文件不使用顶部 `version` 字段。
-本地开发默认使用 SQLite 文件数据库，正式环境使用 PostgreSQL，并按需启用 Milvus、Neo4j / NebulaGraph、Redis 和对象存储。
 
 ## 项目目录
 
@@ -226,15 +286,7 @@ Compose 文件不使用顶部 `version` 字段。
 
 ### 本地开发（Makefile 统一入口）
 
-所有本地服务的启动、测试与数据库迁移统一经根目录 Makefile（`make help` 查看全部）：
+所有本地服务的启动、测试与数据库迁移统一经根目录 Makefile（`make help` 查看全部）
-
-```bash
-make dev-core                 # 核心三服务并行：灵台 + 神识 + 照壁
-make dev-backend              # 灵台（另有 dev-shenshi / dev-bff / dev-frontend / dev-sandbox / dev-tianmu / dev-yuanqi）
-make db-upgrade               # Alembic 升级到 head（迁移编号 000/001/002…）
-make db-revision m="说明"     # 生成下一号迁移（自动编号 + autogenerate，禁手写哈希 id）
-make test                     # 全部测试（backend / shenshi / bff / frontend）
-```
 
 ### Docker
 
@@ -244,7 +296,6 @@ make test                     # 全部测试（backend / shenshi / bff / fronten
 ```bash
 # 先准备配置（只需一次）
 cp .env.example .env                       # 填写 POSTGRES_PASSWORD 与各 *_API_KEY
-# 模型端点目录经 SHENSHI_ENDPOINTS 配置（见 .env.example 神识段），无需复制 yaml
 
 # 1) 启动基础设施（首次创建 hunjing-net 网络；Milvus 会自动带起 hunjing-etcd / hunjing-minio）
 docker compose -f docker/docker-compose.infra.yml up -d

CLAUDE.md

@@ -1 +0,0 @@
-@AGENTS.md

Makefile

@@ -1,142 +1,30 @@
-# ==============================
+# Makefile for cleaning Python cache files and empty directories
-# 魂镜 · 统一开发入口（rewrite/1.0）
+# Author: AI Assistant
-# 所有本地服务的启动 / 测试 / 数据库迁移统一经本文件；
+# Usage: make clean or make clean-all
-# Docker 编排（基础设施与应用容器）见 AGENTS.md「开发命令」与 docker/README.md。
-# ==============================
 
+.PHONY: clean clean-all clean-pyc clean-pytest clean-mypy clean-empty-dirs help
+
+# Colors for pretty output
 GREEN  := \033[0;32m
 YELLOW := \033[0;33m
-NC     := \033[0m
+RED    := \033[0;31m
+NC     := \033[0m # No Color
 
-.PHONY: help \
+# Default target
-  dev-backend dev-shenshi dev-bff dev-frontend dev-sandbox dev-tianmu dev-yuanqi dev-core dev-all \
-  db-upgrade db-downgrade db-revision db-current \
-  test test-backend test-shenshi test-bff test-frontend \
-  vet-shenshi typecheck-bff \
-  infra-up app-up app-down \
-  clean clean-all clean-pyc clean-pytest clean-mypy clean-empty-dirs clean-dry-run
-
-# 默认目标
 help:
-	@echo "$(GREEN)魂镜统一开发入口$(NC)"
+	@echo "$(GREEN)Available targets:$(NC)"
-	@echo ""
+	@echo "  $(YELLOW)make clean$(NC)        - Remove Python cache files, pytest cache, mypy cache, and empty directories"
-	@echo "$(YELLOW)服务启动（开发）$(NC)"
+	@echo "  $(YELLOW)make clean-pyc$(NC)    - Remove Python cache files (__pycache__, .pyc, .pyo)"
-	@echo "  make dev-backend     灵台（uvicorn 热重载，:8000）"
+	@echo "  $(YELLOW)make clean-pytest$(NC) - Remove pytest cache (.pytest_cache)"
-	@echo "  make dev-shenshi     神识（go run，:8080）"
+	@echo "  $(YELLOW)make clean-mypy$(NC)   - Remove mypy cache (.mypy_cache)"
-	@echo "  make dev-bff         照壁（tsx watch，:3000）"
+	@echo "  $(YELLOW)make clean-empty-dirs$(NC) - Remove empty directories"
-	@echo "  make dev-frontend    琉璃镜（next dev，:3001）"
+	@echo "  $(YELLOW)make clean-all$(NC)    - Remove everything (cache, logs, coverage, build, dist, etc.)"
-	@echo "  make dev-sandbox     乾坤沙箱（cargo run，:8090）"
-	@echo "  make dev-tianmu      天目 OCR（:8101，可选）"
-	@echo "  make dev-yuanqi      元炁本地推理（:11434，可选）"
-	@echo "  make dev-core        核心三服务并行（灵台+神识+照壁）"
-	@echo "  make dev-all         前述全部并行（不含沙箱/天目/元炁）"
-	@echo ""
-	@echo "$(YELLOW)数据库（Alembic，迁移编号 000/001/002…）$(NC)"
-	@echo "  make db-upgrade      升级到最新（head）"
-	@echo "  make db-downgrade    回退一步"
-	@echo "  make db-revision m=\"说明\"  生成下一号迁移（自动编号+autogenerate）"
-	@echo "  make db-current      查看当前版本"
-	@echo ""
-	@echo "$(YELLOW)测试与检查$(NC)"
-	@echo "  make test            全部（后端+神识+照壁+前端）"
-	@echo "  make test-backend / test-shenshi / test-bff / test-frontend"
-	@echo "  make vet-shenshi     go vet"
-	@echo "  make typecheck-bff   tsc --noEmit"
-	@echo ""
-	@echo "$(YELLOW)Docker 编排快捷方式$(NC)"
-	@echo "  make infra-up / app-up / app-down"
-	@echo ""
-	@echo "$(YELLOW)清理$(NC)"
-	@echo "  make clean / clean-all / clean-dry-run"
-
-# ============================== 服务启动（开发） ==============================
-
-dev-backend:
-	cd backend && uv run python -m app.main
-
-dev-shenshi:
-	cd shenshi && go run .
-
-dev-bff:
-	cd bff && npm run dev
-
-dev-frontend:
-	cd frontend && pnpm dev
-
-dev-sandbox:
-	cd sandbox && cargo run
-
-dev-tianmu:
-	cd tianmu && uv run tianmu
-
-dev-yuanqi:
-	cd yuanqi && uv run uvicorn src.main:app
-
-# 核心三服务并行：灵台 + 神识 + 照壁（M0 验收链路）
-dev-core:
-	$(MAKE) -j3 dev-backend dev-shenshi dev-bff
-
-dev-all:
-	$(MAKE) -j4 dev-backend dev-shenshi dev-bff dev-frontend
-
-# ============================== 数据库（Alembic） ==============================
-
-# 迁移约定：revision id 与文件名前缀用三位顺序号（000、001、002…），生成统一走
-# `make db-revision`（自动取最大号+1 并传 --rev-id）；不要手写哈希 id。
-db-upgrade:
-	cd backend && uv run alembic upgrade head
-
-db-downgrade:
-	cd backend && uv run alembic downgrade -1
-
-db-revision:
-	@next=$$(ls backend/alembic/versions 2>/dev/null | grep -E '^[0-9][0-9][0-9]_.*\.py$$' | cut -c1-3 | sort -n | tail -1); \
-	if [ -z "$$next" ]; then echo "未找到顺序编号迁移，请先确认基线 000 存在"; exit 1; fi; \
-	next=$$(printf '%03d' $$((10#$$next + 1))); \
-	echo "$(GREEN)生成迁移 $(NC)$$next：$(m)"; \
-	cd backend && uv run alembic revision --autogenerate --rev-id $$next -m "$(m)"
-
-db-current:
-	cd backend && uv run alembic current
-
-# ============================== 测试与检查 ==============================
-
-test-backend:
-	cd backend && uv run pytest -q
-
-test-shenshi:
-	cd shenshi && go test ./...
-
-test-bff:
-	cd bff && npm test --silent
-
-test-frontend:
-	cd frontend && pnpm test
-
-test: test-backend test-shenshi test-bff test-frontend
-
-vet-shenshi:
-	cd shenshi && go vet ./...
-
-typecheck-bff:
-	cd bff && npm run type-check --silent
-
-# ============================== Docker 编排快捷方式 ==============================
-
-infra-up:
-	docker compose -f docker/docker-compose.infra.yml up -d
-
-app-up:
-	docker compose -f docker/docker-compose.app.yml up -d --build
-
-app-down:
-	docker compose -f docker/docker-compose.app.yml down
-
-# ============================== 清理（保留原有能力） ==============================
 
+# Main clean target
 clean: clean-pyc clean-pytest clean-mypy clean-empty-dirs
 	@echo "$(GREEN)✓ Cleanup completed successfully!$(NC)"
 
+# Clean Python cache files
 clean-pyc:
 	@echo "$(YELLOW)Removing Python cache files...$(NC)"
 	@find . -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
@@ -145,35 +33,55 @@ clean-pyc:
 	@find . -type f -name "*.pyd" -delete 2>/dev/null || true
 	@echo "$(GREEN)✓ Python cache files removed$(NC)"
 
+# Clean pytest cache
 clean-pytest:
 	@echo "$(YELLOW)Removing pytest cache...$(NC)"
 	@rm -rf .pytest_cache 2>/dev/null || true
 	@find . -type d -name ".pytest_cache" -exec rm -rf {} + 2>/dev/null || true
 	@echo "$(GREEN)✓ Pytest cache removed$(NC)"
 
+# Clean mypy cache
 clean-mypy:
 	@echo "$(YELLOW)Removing mypy cache...$(NC)"
 	@rm -rf .mypy_cache 2>/dev/null || true
 	@find . -type d -name ".mypy_cache" -exec rm -rf {} + 2>/dev/null || true
 	@echo "$(GREEN)✓ Mypy cache removed$(NC)"
 
+# Remove empty directories
 clean-empty-dirs:
 	@echo "$(YELLOW)Removing empty directories...$(NC)"
+	@# Remove empty directories (including hidden ones), excluding .git and .venv
 	@find . -type d -empty -not -path "./.git/*" -not -path "./.venv/*" -not -path "./venv/*" -not -path "./env/*" -not -path "./.env/*" -delete 2>/dev/null || true
+	@# Second pass to remove newly created empty parent directories
 	@find . -type d -empty -not -path "./.git/*" -not -path "./.venv/*" -not -path "./venv/*" -not -path "./env/*" -not -path "./.env/*" -delete 2>/dev/null || true
 	@echo "$(GREEN)✓ Empty directories removed$(NC)"
 
+# Clean everything (extended cleanup)
 clean-all: clean
 	@echo "$(YELLOW)Removing additional files...$(NC)"
+	@# Coverage reports
 	@rm -rf htmlcov .coverage coverage.xml .coverage.* 2>/dev/null || true
+	@# Build artifacts
 	@rm -rf build/ dist/ *.egg-info .eggs/ 2>/dev/null || true
+	@# Log files
 	@find . -type f -name "*.log" -delete 2>/dev/null || true
+	@# Jupyter notebooks checkpoint
 	@find . -type d -name ".ipynb_checkpoints" -exec rm -rf {} + 2>/dev/null || true
+	@# IDE files (optional, uncomment if needed)
+	# @rm -rf .vscode/ .idea/ 2>/dev/null || true
 	@echo "$(GREEN)✓ Extended cleanup completed!$(NC)"
 
+# Dry run - show what would be deleted (for safety)
 clean-dry-run:
-	@echo "$(YELLOW)Dry run - files that would be deleted (run 'make clean' to delete):$(NC)"
+	@echo "$(YELLOW)Dry run - files that would be deleted:$(NC)"
+	@echo "\nPython cache files:"
 	@find . -type d -name "__pycache__" 2>/dev/null || echo "None"
 	@find . -type f -name "*.pyc" 2>/dev/null || echo "None"
+	@find . -type f -name "*.pyo" 2>/dev/null || echo "None"
+	@echo "\nPytest cache:"
 	@find . -type d -name ".pytest_cache" 2>/dev/null || echo "None"
+	@echo "\nMypy cache:"
 	@find . -type d -name ".mypy_cache" 2>/dev/null || echo "None"
+	@echo "\nEmpty directories:"
+	@find . -type d -empty -not -path "./.git/*" -not -path "./.venv/*" 2>/dev/null || echo "None"
+	@echo "$(YELLOW)\nRun 'make clean' to actually delete these files$(NC)"

README.md

@@ -49,17 +49,12 @@
 
 ## 技术边界
 
-工程架构以根目录 `AGENTS.md` 完整技术栈为基准，按五层组织；服务与文化命名登记见[契约词典](docs/contracts/contract-glossary.md)。
+| 服务 | 技术 | 主要职责 |
-
+| --- | --- | --- |
-| 服务 | 文化名 | 技术 | 主要职责 |
+| 灵台 | Python | 人物、镜树、人格、记忆、缘契、三界与认知编排 |
-| --- | --- | --- | --- |
+| 神识 | Go | Provider、Endpoint、模型路由、流式、BYOK、配额与成本 |
-| 前端 | 琉璃镜 | Next.js / React / TS | 全部 Web 界面、镜树阅读、治理呈现、Live2D 与浏览器通感 |
+| 乾坤 | Rust | 沙箱、高风险执行、设备与具身安全 |
-| BFF | 照壁 | Node.js / Fastify | 鉴权透传、SSE 代理、响应裁剪、类型桥接 |
+| 琉璃镜 | TypeScript / Next.js | 全部 Web 用户界面、Live2D 与浏览器通感 |
-| 后端核心 | 灵台 | Python / FastAPI | 六域业务、插件化认知运行时（九枢）、事件溯源、司命裁决、百工注册 |
-| 模型网关 | 神识 | Go | Provider、路由、流式、BYOK、配额与成本计量 |
-| 桌面壳 | 镜匣 | Rust / Tauri | 最小桌面壳、本地能力桥、乾坤本地执行通道 |
-| 隔离执行 | 乾坤 | Rust / axum | 沙箱、高风险执行、设备与具身安全 |
-| 辅助服务 | 博闻 / 天目 / 元炁 | Go / Python | MCP 联网搜索 / 本地 OCR / 本地推理 |
 
 神识、百工、司命和灵台遵循：**神识通协议，百工掌能力，司命决边界，灵台承结果。**
 
@@ -74,7 +69,7 @@ flowchart LR
     E --> F[代码与测试]
 ```
 
-现有代码是迁移与审计对象，不反向覆盖已确认的产品定义。当前处于 rewrite/1.0 全量重写期，架构与契约层已按五层栈重建，范围与节奏见重写执行计划（已收口删除）。
+现有代码是迁移与审计对象，不反向覆盖已确认的产品定义。
 
 ## 文档入口
 

backend/.pre-commit-config.yaml

@@ -1,16 +0,0 @@
-repos:
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.15.17
-    hooks:
-      - id: ruff
-        args: [--fix]
-        types_or: [python, pyi]
-      - id: ruff-format
-        types_or: [python, pyi]
-  - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v2.1.0
-    hooks:
-      - id: mypy
-        args: [--no-strict-optional, --ignore-missing-imports, --follow-imports=silent]
-        additional_dependencies: ["types-redis"]
-        files: ^app/

backend/CLAUDE.md

@@ -0,0 +1,64 @@
+# 后端开发
+
+## 技术栈
+
+Python 3.12 + FastAPI + SQLAlchemy + Alembic + loguru + httpx + chromadb
+uv (用于虚拟环境和依赖管理)
+
+## 开发命令
+
+启动命令之前确保目前在backend目录下，并且已经激活了虚拟环境。默认本地开发使用 SQLite（aiosqlite）文件数据库，Redis、ChromaDB、Neo4j 暂不启用
+
+```bash
+uv venv -p 3.12                                       # 创建虚拟环境
+source .venv/bin/activate                             # 激活虚拟环境
+uv add <pkg>                                          # 添加依赖
+uv remove <pkg>                                       # 移除依赖
+uv run python -m app.main                            # 按 .env 中 BACKEND_HOST/BACKEND_PORT 启动服务
+uv run uvicorn app.main:app --reload --port 8000      # 手动指定端口启动服务（命令行 --port 会覆盖 .env）
+
+# 数据库迁移
+uv run alembic revision --autogenerate --rev-id=001 -m "描述"       # 生成迁移
+uv run alembic upgrade head                           # 执行迁移
+uv run alembic downgrade -1                           # 回滚一个版本
+uv run alembic current                                # 查看当前版本
+
+# 测试
+uv run pytest                                         # 运行测试
+```
+
+## 代码规范
+
+在__init__文件中可以将模块内的类、函数等导出，方便其他模块导入使用
+遵循 PEP 8 代码风格指南和更加pythonic的开发方式
+遵循单一职责原则，每个文件、类、函数等都要只干一件事
+使用 loguru 进行日志记录，避免使用 logging 模块
+使用 Alembic 进行数据库迁移，禁止手动修改数据库表结构，文件命名以迁移版本号开头，例如 001_initial.py；迁移必须优先兼容 SQLite，涉及 PostgreSQL 专用 DDL 时必须提供 SQLite 分支或显式跳过
+使用alembic init alembic命令初始化迁移环境，使用命令生成相关的迁移文件,不能直接生成迁移文件
+使用 httpx 进行异步 HTTP 请求，禁止在路由函数内直接使用同步数据库会话或 httpx 客户端
+所有的测试代码都写在tests目录下，测试文件命名以test_开头，测试函数命名以test_开头
+所有敏感信息（如密钥、Token、数据库密码）必须通过环境变量或配置文件管理，禁止硬编码到代码中
+
+## 代码审查
+
+开发完成后必须使用以下命令进行代码检查：
+
+```bash
+uv run ruff check         # Lint 检查
+uv run ruff check --fix   # 自动修复部分代码风格问题
+uv run pre-commit run --all-files  # 可选：完整运行 CI 级检查（包括类型检查）
+```
+
+确保没有任何 lint 错误后再提交。
+
+## 绝对禁止事项
+
+直接修改 pyproject.toml 文件添加或者移除依赖（必须使用 uv add/remove 命令）
+在路由函数内直接使用同步数据库会话（必须通过 Depends 注入）
+在路由函数内直接 async with httpx.AsyncClient()
+使用 logging 模块（统一用 loguru）
+硬编码密钥、Token、数据库密码到代码
+手动创建/修改数据库表结构（必须使用 Alembic 迁移）
+在 `modules/` 中 import `repositories` / `db` / `integrations` / `ai_provider` / `httpx` / `sqlalchemy`（领域层禁止 IO，需要 IO 时上移到 services/application）
+在业务目录（`ai_provider` / `integrations` 等）中持有 `settings.py` / `config.py`（配置统一进 `core/config/`）
+使用 `python-dotenv`（`.env` 由 `core/config` 以绝对路径 `_env_file` 加载）

backend/alembic.ini

@@ -15,10 +15,6 @@ script_location = %(here)s/alembic
 # Or organize into date-based subdirectories (requires recursive_version_locations = true)
 # file_template = %%(year)d/%%(month).2d/%%(day).2d_%%(hour).2d%%(minute).2d_%%(second).2d_%%(rev)s_%%(slug)s
 
-# 魂镜迁移编号约定（rewrite/1.0）：revision id 与文件名前缀使用三位顺序号（000、001、002…），
-# 生成统一走根目录 `make db-revision m="说明"`（自动取最大号+1 并传 --rev-id），不手写哈希 id。
-file_template = %%(rev)s_%%(slug)s
-
 # sys.path path, will be prepended to sys.path if present.
 # defaults to the current working directory.  for multiple paths, the path separator
 # is defined by "path_separator" below.

backend/alembic/versions/000_rewrite_1_0_baseline.py

@@ -1,889 +0,0 @@
-"""rewrite-1.0 基线：合并既有模式为单一起点
-
-Revision ID: 843abf719fde
-Revises: 
-Create Date: 2026-08-21 21:57:55.890597
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '000'
-down_revision: Union[str, Sequence[str], None] = None
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('agent_roster',
-    sa.Column('role', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('responsibility', sa.Text(), nullable=False),
-    sa.Column('enabled', sa.Boolean(), nullable=False),
-    sa.Column('last_active_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('role')
-    )
-    op.create_table('characters',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('display_name', sa.String(length=120), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('language', sa.String(length=20), nullable=False),
-    sa.Column('profile_json', sa.Text(), nullable=False),
-    sa.Column('model_policy_json', sa.Text(), nullable=False),
-    sa.Column('safety_policy_id', sa.String(length=80), nullable=True),
-    sa.Column('current_personality_version_id', sa.String(length=80), nullable=True),
-    sa.Column('personality_summary', sa.Text(), nullable=True),
-    sa.Column('mission', sa.Text(), nullable=True),
-    sa.Column('safety_guidelines', sa.Text(), nullable=True),
-    sa.Column('current_mood_id', sa.String(length=80), nullable=True),
-    sa.Column('privacy_level', sa.String(length=40), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('is_system_template', sa.Boolean(), nullable=False),
-    sa.Column('source_template_id', sa.String(length=80), nullable=True),
-    sa.Column('template_key', sa.String(length=80), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('activated_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('archived_at', sa.DateTime(timezone=True), nullable=True),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_characters_is_system_template'), 'characters', ['is_system_template'], unique=False)
-    op.create_index(op.f('ix_characters_owner_scope'), 'characters', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_characters_source_template_id'), 'characters', ['source_template_id'], unique=False)
-    op.create_index(op.f('ix_characters_status'), 'characters', ['status'], unique=False)
-    op.create_index(op.f('ix_characters_template_key'), 'characters', ['template_key'], unique=False)
-    op.create_table('generation_preferences',
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('default_model_hint', sa.String(length=120), nullable=False),
-    sa.Column('temperature', sa.Float(), nullable=False),
-    sa.Column('top_p', sa.Float(), nullable=False),
-    sa.Column('max_output_tokens', sa.Integer(), nullable=False),
-    sa.Column('streaming', sa.Boolean(), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('owner_scope')
-    )
-    op.create_table('idempotency_keys',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('key', sa.String(length=200), nullable=False),
-    sa.Column('scope', sa.String(length=120), nullable=False),
-    sa.Column('method', sa.String(length=20), nullable=False),
-    sa.Column('path', sa.String(length=500), nullable=False),
-    sa.Column('request_hash', sa.String(length=128), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('response_status_code', sa.Integer(), nullable=False),
-    sa.Column('response_body_json', sa.Text(), nullable=False),
-    sa.Column('resource_type', sa.String(length=80), nullable=True),
-    sa.Column('resource_id', sa.String(length=120), nullable=True),
-    sa.Column('trace_id', sa.String(length=80), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('scope', 'key', name='uq_idempotency_scope_key')
-    )
-    op.create_index(op.f('ix_idempotency_keys_expires_at'), 'idempotency_keys', ['expires_at'], unique=False)
-    op.create_index(op.f('ix_idempotency_keys_key'), 'idempotency_keys', ['key'], unique=False)
-    op.create_index(op.f('ix_idempotency_keys_scope'), 'idempotency_keys', ['scope'], unique=False)
-    op.create_index(op.f('ix_idempotency_keys_trace_id'), 'idempotency_keys', ['trace_id'], unique=False)
-    op.create_table('mcp_servers',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('transport', sa.String(length=40), nullable=False),
-    sa.Column('endpoint_url', sa.String(length=500), nullable=True),
-    sa.Column('auth_token', sa.String(length=500), nullable=True),
-    sa.Column('command', sa.String(length=500), nullable=True),
-    sa.Column('args_json', sa.Text(), nullable=True),
-    sa.Column('env_json', sa.Text(), nullable=True),
-    sa.Column('cwd', sa.String(length=500), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('tools_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('name')
-    )
-    op.create_index(op.f('ix_mcp_servers_status'), 'mcp_servers', ['status'], unique=False)
-    op.create_table('model_endpoint_overrides',
-    sa.Column('logical_model_name', sa.String(length=120), nullable=False),
-    sa.Column('endpoint_name', sa.String(length=120), nullable=False),
-    sa.Column('base_url', sa.String(length=500), nullable=True),
-    sa.Column('api_key', sa.String(length=500), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=True),
-    sa.Column('weight', sa.Integer(), nullable=True),
-    sa.Column('priority', sa.Integer(), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('logical_model_name', 'endpoint_name')
-    )
-    op.create_table('pending_confirmations',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('tool', sa.String(length=120), nullable=False),
-    sa.Column('input_json', sa.Text(), nullable=False),
-    sa.Column('risk_level', sa.String(length=40), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=False),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('trace_id', sa.String(length=80), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('resolved_at', sa.DateTime(timezone=True), nullable=True),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_pending_confirmations_character_id'), 'pending_confirmations', ['character_id'], unique=False)
-    op.create_index(op.f('ix_pending_confirmations_run_id'), 'pending_confirmations', ['run_id'], unique=False)
-    op.create_index(op.f('ix_pending_confirmations_status'), 'pending_confirmations', ['status'], unique=False)
-    op.create_table('perception_channels',
-    sa.Column('channel', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('enabled', sa.Boolean(), nullable=False),
-    sa.Column('consent_status', sa.String(length=40), nullable=False),
-    sa.Column('privacy_level', sa.String(length=40), nullable=False),
-    sa.Column('risk_level', sa.String(length=20), nullable=False),
-    sa.Column('last_active_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('channel')
-    )
-    op.create_table('permissions',
-    sa.Column('id', sa.String(length=40), nullable=False),
-    sa.Column('resource', sa.String(length=80), nullable=False),
-    sa.Column('action', sa.String(length=80), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_permissions_resource'), 'permissions', ['resource'], unique=False)
-    op.create_table('roles',
-    sa.Column('id', sa.String(length=40), nullable=False),
-    sa.Column('name', sa.String(length=80), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('is_system', sa.Boolean(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_roles_name'), 'roles', ['name'], unique=True)
-    op.create_table('skills',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('trigger', sa.Text(), nullable=False),
-    sa.Column('prompt_fragment', sa.Text(), nullable=False),
-    sa.Column('tool_bindings_json', sa.Text(), nullable=False),
-    sa.Column('risk_level', sa.String(length=8), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('name')
-    )
-    op.create_index(op.f('ix_skills_status'), 'skills', ['status'], unique=False)
-    op.create_table('tool_policies',
-    sa.Column('name', sa.String(length=80), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('risk_level', sa.String(length=20), nullable=False),
-    sa.Column('permission_policy', sa.String(length=20), nullable=False),
-    sa.Column('side_effect', sa.Boolean(), nullable=False),
-    sa.Column('audit_required', sa.Boolean(), nullable=False),
-    sa.Column('source', sa.String(length=20), nullable=False),
-    sa.Column('enabled', sa.Boolean(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('name')
-    )
-    op.create_table('users',
-    sa.Column('id', sa.String(length=40), nullable=False),
-    sa.Column('username', sa.String(length=80), nullable=False),
-    sa.Column('email', sa.String(length=255), nullable=False),
-    sa.Column('password_hash', sa.String(length=255), nullable=False),
-    sa.Column('is_active', sa.Boolean(), nullable=False),
-    sa.Column('is_admin', sa.Boolean(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('email')
-    )
-    op.create_index(op.f('ix_users_username'), 'users', ['username'], unique=True)
-    op.create_table('world_entities',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('type', sa.String(length=40), nullable=False),
-    sa.Column('name', sa.String(length=200), nullable=False),
-    sa.Column('attributes_json', sa.Text(), nullable=False),
-    sa.Column('state_type', sa.String(length=40), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('sources_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_world_entities_type'), 'world_entities', ['type'], unique=False)
-    op.create_table('big_cycles',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('trigger', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('phase', sa.String(length=40), nullable=True),
-    sa.Column('memory_count_at_trigger', sa.Integer(), nullable=False),
-    sa.Column('evaluation_snapshot_json', sa.Text(), nullable=True),
-    sa.Column('summary', sa.Text(), nullable=True),
-    sa.Column('error_code', sa.String(length=80), nullable=True),
-    sa.Column('error_message', sa.Text(), nullable=True),
-    sa.Column('started_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('completed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_big_cycles_character_id'), 'big_cycles', ['character_id'], unique=False)
-    op.create_index(op.f('ix_big_cycles_completed_at'), 'big_cycles', ['completed_at'], unique=False)
-    op.create_index(op.f('ix_big_cycles_status'), 'big_cycles', ['status'], unique=False)
-    op.create_table('character_emotion_states',
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('mood', sa.String(length=40), nullable=False),
-    sa.Column('intensity', sa.Float(), nullable=False),
-    sa.Column('baseline_mood', sa.String(length=40), nullable=False),
-    sa.Column('baseline_intensity', sa.Float(), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('last_trigger_event_id', sa.String(length=80), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('character_id')
-    )
-    op.create_table('character_import_jobs',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('material_type', sa.String(length=40), nullable=False),
-    sa.Column('source_type', sa.String(length=40), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('format', sa.String(length=40), nullable=False),
-    sa.Column('media_type', sa.String(length=40), nullable=True),
-    sa.Column('mime_type', sa.String(length=80), nullable=True),
-    sa.Column('source_description', sa.Text(), nullable=True),
-    sa.Column('speaker_label', sa.String(length=120), nullable=True),
-    sa.Column('consent_status', sa.String(length=40), nullable=False),
-    sa.Column('usage_scope', sa.String(length=40), nullable=False),
-    sa.Column('checksum', sa.String(length=120), nullable=True),
-    sa.Column('item_count', sa.Integer(), nullable=False),
-    sa.Column('storage_path', sa.String(length=500), nullable=True),
-    sa.Column('raw_content', sa.Text(), nullable=True),
-    sa.Column('error_code', sa.String(length=80), nullable=True),
-    sa.Column('error_message', sa.Text(), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_character_import_jobs_character_id'), 'character_import_jobs', ['character_id'], unique=False)
-    op.create_index(op.f('ix_character_import_jobs_checksum'), 'character_import_jobs', ['checksum'], unique=False)
-    op.create_index(op.f('ix_character_import_jobs_material_type'), 'character_import_jobs', ['material_type'], unique=False)
-    op.create_index(op.f('ix_character_import_jobs_status'), 'character_import_jobs', ['status'], unique=False)
-    op.create_table('character_world_entities',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('type', sa.String(length=40), nullable=False),
-    sa.Column('name', sa.String(length=200), nullable=False),
-    sa.Column('attributes_json', sa.Text(), nullable=False),
-    sa.Column('state_type', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('sources_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_character_world_entities_character_id'), 'character_world_entities', ['character_id'], unique=False)
-    op.create_index(op.f('ix_character_world_entities_status'), 'character_world_entities', ['status'], unique=False)
-    op.create_index(op.f('ix_character_world_entities_type'), 'character_world_entities', ['type'], unique=False)
-    op.create_table('chat_sessions',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_chat_sessions_character_id'), 'chat_sessions', ['character_id'], unique=False)
-    op.create_index(op.f('ix_chat_sessions_owner_scope'), 'chat_sessions', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_chat_sessions_status'), 'chat_sessions', ['status'], unique=False)
-    op.create_table('goals',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('title', sa.String(length=300), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('level', sa.String(length=40), nullable=False),
-    sa.Column('type', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('priority', sa.Integer(), nullable=False),
-    sa.Column('progress', sa.Float(), nullable=False),
-    sa.Column('constraints_json', sa.Text(), nullable=False),
-    sa.Column('parent_id', sa.String(length=80), nullable=True),
-    sa.Column('success_criteria_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['parent_id'], ['goals.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_goals_character_id'), 'goals', ['character_id'], unique=False)
-    op.create_index(op.f('ix_goals_level'), 'goals', ['level'], unique=False)
-    op.create_index(op.f('ix_goals_status'), 'goals', ['status'], unique=False)
-    op.create_table('lorebooks',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('name', sa.String(length=200), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('scan_depth', sa.Integer(), nullable=True),
-    sa.Column('token_budget', sa.Integer(), nullable=True),
-    sa.Column('recursive_scanning', sa.Boolean(), nullable=False),
-    sa.Column('scope', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_lorebooks_character_id'), 'lorebooks', ['character_id'], unique=False)
-    op.create_index(op.f('ix_lorebooks_owner_scope'), 'lorebooks', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_lorebooks_scope'), 'lorebooks', ['scope'], unique=False)
-    op.create_index(op.f('ix_lorebooks_status'), 'lorebooks', ['status'], unique=False)
-    op.create_table('memories',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('type', sa.String(length=60), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('source', sa.String(length=80), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('importance', sa.Float(), nullable=False),
-    sa.Column('sensitivity', sa.String(length=40), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('deleted_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('temporal_context_json', sa.Text(), server_default='{}', nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_memories_character_id'), 'memories', ['character_id'], unique=False)
-    op.create_index(op.f('ix_memories_status'), 'memories', ['status'], unique=False)
-    op.create_table('personality_versions',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('version', sa.Integer(), nullable=False),
-    sa.Column('identity_profile', sa.Text(), nullable=False),
-    sa.Column('role_destiny', sa.Text(), nullable=False),
-    sa.Column('personality_seed', sa.Text(), nullable=False),
-    sa.Column('traits', sa.Text(), nullable=False),
-    sa.Column('expression_style', sa.Text(), nullable=False),
-    sa.Column('values', sa.Text(), nullable=False),
-    sa.Column('relationship_pattern', sa.Text(), nullable=False),
-    sa.Column('emotion_baseline', sa.Text(), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('created_by', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('rolled_back_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_personality_versions_character_id'), 'personality_versions', ['character_id'], unique=False)
-    op.create_table('role_permissions',
-    sa.Column('role_id', sa.String(length=40), nullable=False),
-    sa.Column('permission_id', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['permission_id'], ['permissions.id'], ondelete='CASCADE'),
-    sa.ForeignKeyConstraint(['role_id'], ['roles.id'], ondelete='CASCADE'),
-    sa.PrimaryKeyConstraint('role_id', 'permission_id')
-    )
-    op.create_table('time_anniversaries',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=200), nullable=False),
-    sa.Column('calendar', sa.String(length=20), nullable=False),
-    sa.Column('date', sa.String(length=20), nullable=False),
-    sa.Column('recurs_yearly', sa.Boolean(), nullable=False),
-    sa.Column('kind', sa.String(length=40), nullable=False),
-    sa.Column('subject_type', sa.String(length=40), nullable=False),
-    sa.Column('source', sa.String(length=40), nullable=False),
-    sa.Column('metadata_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_time_anniversaries_character_id'), 'time_anniversaries', ['character_id'], unique=False)
-    op.create_table('user_roles',
-    sa.Column('user_id', sa.String(length=40), nullable=False),
-    sa.Column('role_id', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['role_id'], ['roles.id'], ondelete='CASCADE'),
-    sa.ForeignKeyConstraint(['user_id'], ['users.id'], ondelete='CASCADE'),
-    sa.PrimaryKeyConstraint('user_id', 'role_id')
-    )
-    op.create_table('character_profile_candidates',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('import_job_id', sa.String(length=80), nullable=True),
-    sa.Column('field', sa.String(length=60), nullable=False),
-    sa.Column('value', sa.Text(), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=True),
-    sa.Column('reviewed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['import_job_id'], ['character_import_jobs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_character_profile_candidates_character_id'), 'character_profile_candidates', ['character_id'], unique=False)
-    op.create_index(op.f('ix_character_profile_candidates_import_job_id'), 'character_profile_candidates', ['import_job_id'], unique=False)
-    op.create_index(op.f('ix_character_profile_candidates_status'), 'character_profile_candidates', ['status'], unique=False)
-    op.create_table('curiosity_questions',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('cycle_id', sa.String(length=80), nullable=False),
-    sa.Column('question', sa.Text(), nullable=False),
-    sa.Column('source', sa.String(length=60), nullable=False),
-    sa.Column('related_entities_json', sa.Text(), nullable=False),
-    sa.Column('expected_value', sa.Float(), nullable=False),
-    sa.Column('urgency', sa.Float(), nullable=False),
-    sa.Column('risk_level', sa.String(length=8), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['cycle_id'], ['big_cycles.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_curiosity_questions_character_id'), 'curiosity_questions', ['character_id'], unique=False)
-    op.create_index(op.f('ix_curiosity_questions_cycle_id'), 'curiosity_questions', ['cycle_id'], unique=False)
-    op.create_table('evolution_candidates',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('cycle_id', sa.String(length=80), nullable=False),
-    sa.Column('type', sa.String(length=60), nullable=False),
-    sa.Column('source', sa.String(length=60), nullable=False),
-    sa.Column('level', sa.String(length=8), nullable=False),
-    sa.Column('scope', sa.String(length=40), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=False),
-    sa.Column('proposal', sa.Text(), nullable=False),
-    sa.Column('delta_json', sa.Text(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('benefit_score', sa.Float(), nullable=False),
-    sa.Column('risk_score', sa.Float(), nullable=False),
-    sa.Column('drift_score', sa.Float(), nullable=False),
-    sa.Column('auto_apply_allowed', sa.Boolean(), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('resulting_target_id', sa.String(length=80), nullable=True),
-    sa.Column('error_message', sa.Text(), nullable=True),
-    sa.Column('reviewed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('reviewed_by', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['cycle_id'], ['big_cycles.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_evolution_candidates_character_id'), 'evolution_candidates', ['character_id'], unique=False)
-    op.create_index(op.f('ix_evolution_candidates_cycle_id'), 'evolution_candidates', ['cycle_id'], unique=False)
-    op.create_index(op.f('ix_evolution_candidates_status'), 'evolution_candidates', ['status'], unique=False)
-    op.create_table('import_items',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('import_job_id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('item_type', sa.String(length=40), nullable=False),
-    sa.Column('role', sa.String(length=40), nullable=False),
-    sa.Column('sequence', sa.Integer(), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('metadata_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['import_job_id'], ['character_import_jobs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_import_items_character_id'), 'import_items', ['character_id'], unique=False)
-    op.create_index(op.f('ix_import_items_import_job_id'), 'import_items', ['import_job_id'], unique=False)
-    op.create_table('lorebook_entries',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('lorebook_id', sa.String(length=80), nullable=False),
-    sa.Column('keys_json', sa.Text(), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('secondary_keys_json', sa.Text(), nullable=False),
-    sa.Column('constant', sa.Boolean(), nullable=False),
-    sa.Column('selective', sa.Boolean(), nullable=False),
-    sa.Column('enabled', sa.Boolean(), nullable=False),
-    sa.Column('case_sensitive', sa.Boolean(), nullable=False),
-    sa.Column('use_regex', sa.Boolean(), nullable=False),
-    sa.Column('position', sa.String(length=40), nullable=False),
-    sa.Column('insertion_order', sa.Integer(), nullable=False),
-    sa.Column('priority', sa.Integer(), nullable=False),
-    sa.Column('comment', sa.String(length=500), nullable=False),
-    sa.Column('bound_entity_id', sa.String(length=80), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['lorebook_id'], ['lorebooks.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_lorebook_entries_bound_entity_id'), 'lorebook_entries', ['bound_entity_id'], unique=False)
-    op.create_index(op.f('ix_lorebook_entries_lorebook_id'), 'lorebook_entries', ['lorebook_id'], unique=False)
-    op.create_table('memory_candidates',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('import_job_id', sa.String(length=80), nullable=True),
-    sa.Column('cycle_id', sa.String(length=80), nullable=True),
-    sa.Column('type', sa.String(length=60), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('importance', sa.Float(), nullable=False),
-    sa.Column('sensitivity', sa.String(length=40), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=True),
-    sa.Column('reviewed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['cycle_id'], ['big_cycles.id'], ),
-    sa.ForeignKeyConstraint(['import_job_id'], ['character_import_jobs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_memory_candidates_character_id'), 'memory_candidates', ['character_id'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_cycle_id'), 'memory_candidates', ['cycle_id'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_import_job_id'), 'memory_candidates', ['import_job_id'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_status'), 'memory_candidates', ['status'], unique=False)
-    op.create_table('memory_links',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('source_memory_id', sa.String(length=80), nullable=False),
-    sa.Column('target_memory_id', sa.String(length=80), nullable=False),
-    sa.Column('relation', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['source_memory_id'], ['memories.id'], ),
-    sa.ForeignKeyConstraint(['target_memory_id'], ['memories.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_memory_links_character_id'), 'memory_links', ['character_id'], unique=False)
-    op.create_index(op.f('ix_memory_links_source_memory_id'), 'memory_links', ['source_memory_id'], unique=False)
-    op.create_index(op.f('ix_memory_links_target_memory_id'), 'memory_links', ['target_memory_id'], unique=False)
-    op.create_table('personality_proposals',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('fields_json', sa.Text(), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('resulting_version_id', sa.String(length=80), nullable=True),
-    sa.Column('reviewed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('reviewed_by', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['resulting_version_id'], ['personality_versions.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_personality_proposals_character_id'), 'personality_proposals', ['character_id'], unique=False)
-    op.create_index(op.f('ix_personality_proposals_status'), 'personality_proposals', ['status'], unique=False)
-    op.create_table('plans',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('goal_id', sa.String(length=80), nullable=True),
-    sa.Column('title', sa.String(length=300), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('assumptions_json', sa.Text(), nullable=False),
-    sa.Column('risks_json', sa.Text(), nullable=False),
-    sa.Column('required_tools_json', sa.Text(), nullable=False),
-    sa.Column('success_criteria_json', sa.Text(), nullable=False),
-    sa.Column('step_count', sa.Integer(), nullable=False),
-    sa.Column('completed_steps', sa.Integer(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['goal_id'], ['goals.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_plans_goal_id'), 'plans', ['goal_id'], unique=False)
-    op.create_index(op.f('ix_plans_status'), 'plans', ['status'], unique=False)
-    op.create_table('runs',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('session_id', sa.String(length=80), nullable=True),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('goal', sa.String(length=300), nullable=True),
-    sa.Column('origin', sa.String(length=40), nullable=False),
-    sa.Column('model_hint', sa.String(length=120), nullable=True),
-    sa.Column('started_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('completed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('error_code', sa.String(length=80), nullable=True),
-    sa.Column('error_message', sa.Text(), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['session_id'], ['chat_sessions.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_runs_character_id'), 'runs', ['character_id'], unique=False)
-    op.create_index(op.f('ix_runs_session_id'), 'runs', ['session_id'], unique=False)
-    op.create_index(op.f('ix_runs_status'), 'runs', ['status'], unique=False)
-    op.create_table('world_relations',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('subject_id', sa.String(length=80), nullable=False),
-    sa.Column('predicate', sa.String(length=120), nullable=False),
-    sa.Column('object_id', sa.String(length=80), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['object_id'], ['character_world_entities.id'], ),
-    sa.ForeignKeyConstraint(['subject_id'], ['character_world_entities.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_world_relations_character_id'), 'world_relations', ['character_id'], unique=False)
-    op.create_index(op.f('ix_world_relations_object_id'), 'world_relations', ['object_id'], unique=False)
-    op.create_index(op.f('ix_world_relations_subject_id'), 'world_relations', ['subject_id'], unique=False)
-    op.create_table('audit_events',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('pivot', sa.String(length=40), nullable=True),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('action', sa.String(length=120), nullable=False),
-    sa.Column('actor', sa.String(length=80), nullable=False),
-    sa.Column('risk_level', sa.String(length=20), nullable=False),
-    sa.Column('decision', sa.String(length=40), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=True),
-    sa.Column('input_summary', sa.Text(), nullable=True),
-    sa.Column('output_summary', sa.Text(), nullable=True),
-    sa.Column('trace_id', sa.String(length=80), nullable=True),
-    sa.Column('resource_type', sa.String(length=80), nullable=True),
-    sa.Column('resource_id', sa.String(length=120), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['run_id'], ['runs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_audit_events_character_id'), 'audit_events', ['character_id'], unique=False)
-    op.create_index(op.f('ix_audit_events_pivot'), 'audit_events', ['pivot'], unique=False)
-    op.create_index(op.f('ix_audit_events_run_id'), 'audit_events', ['run_id'], unique=False)
-    op.create_index(op.f('ix_audit_events_trace_id'), 'audit_events', ['trace_id'], unique=False)
-    op.create_table('chat_messages',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('session_id', sa.String(length=80), nullable=False),
-    sa.Column('role', sa.String(length=40), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('modality', sa.String(length=40), nullable=False),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('metadata_json', sa.Text(), nullable=False),
-    sa.Column('sensitivity', sa.String(length=40), nullable=False),
-    sa.Column('versions_json', sa.Text(), nullable=False, comment='版本历史 JSON 数组：[{content, created_at}]，按生成顺序排列，末尾最新'),
-    sa.Column('active_version_idx', sa.Integer(), nullable=False, comment='当前活跃版本在 versions_json 中的索引（0-based）'),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('deleted_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['run_id'], ['runs.id'], ),
-    sa.ForeignKeyConstraint(['session_id'], ['chat_sessions.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_chat_messages_character_id'), 'chat_messages', ['character_id'], unique=False)
-    op.create_index(op.f('ix_chat_messages_run_id'), 'chat_messages', ['run_id'], unique=False)
-    op.create_index(op.f('ix_chat_messages_session_id'), 'chat_messages', ['session_id'], unique=False)
-    op.create_table('events',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('type', sa.String(length=80), nullable=False),
-    sa.Column('source', sa.String(length=40), nullable=False),
-    sa.Column('payload_json', sa.Text(), nullable=False),
-    sa.Column('visibility', sa.String(length=40), nullable=False),
-    sa.Column('sensitivity', sa.String(length=40), nullable=False),
-    sa.Column('trace_id', sa.String(length=80), nullable=True),
-    sa.Column('parent_id', sa.String(length=80), nullable=True),
-    sa.Column('sequence', sa.Integer(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['run_id'], ['runs.id'], ),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('run_id', 'sequence', name='uq_events_run_sequence')
-    )
-    op.create_index(op.f('ix_events_character_id'), 'events', ['character_id'], unique=False)
-    op.create_index(op.f('ix_events_run_id'), 'events', ['run_id'], unique=False)
-    op.create_index(op.f('ix_events_trace_id'), 'events', ['trace_id'], unique=False)
-    op.create_index(op.f('ix_events_type'), 'events', ['type'], unique=False)
-    op.create_table('exploratory_subgoals',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('cycle_id', sa.String(length=80), nullable=False),
-    sa.Column('parent_goal_id', sa.String(length=80), nullable=True),
-    sa.Column('curiosity_question_id', sa.String(length=80), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('expected_information_gain', sa.Float(), nullable=False),
-    sa.Column('interruption_cost', sa.Float(), nullable=False),
-    sa.Column('risk_level', sa.String(length=8), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('reviewed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('reviewed_by', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['curiosity_question_id'], ['curiosity_questions.id'], ),
-    sa.ForeignKeyConstraint(['cycle_id'], ['big_cycles.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_exploratory_subgoals_character_id'), 'exploratory_subgoals', ['character_id'], unique=False)
-    op.create_index(op.f('ix_exploratory_subgoals_curiosity_question_id'), 'exploratory_subgoals', ['curiosity_question_id'], unique=False)
-    op.create_index(op.f('ix_exploratory_subgoals_cycle_id'), 'exploratory_subgoals', ['cycle_id'], unique=False)
-    op.create_index(op.f('ix_exploratory_subgoals_status'), 'exploratory_subgoals', ['status'], unique=False)
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(op.f('ix_exploratory_subgoals_status'), table_name='exploratory_subgoals')
-    op.drop_index(op.f('ix_exploratory_subgoals_cycle_id'), table_name='exploratory_subgoals')
-    op.drop_index(op.f('ix_exploratory_subgoals_curiosity_question_id'), table_name='exploratory_subgoals')
-    op.drop_index(op.f('ix_exploratory_subgoals_character_id'), table_name='exploratory_subgoals')
-    op.drop_table('exploratory_subgoals')
-    op.drop_index(op.f('ix_events_type'), table_name='events')
-    op.drop_index(op.f('ix_events_trace_id'), table_name='events')
-    op.drop_index(op.f('ix_events_run_id'), table_name='events')
-    op.drop_index(op.f('ix_events_character_id'), table_name='events')
-    op.drop_table('events')
-    op.drop_index(op.f('ix_chat_messages_session_id'), table_name='chat_messages')
-    op.drop_index(op.f('ix_chat_messages_run_id'), table_name='chat_messages')
-    op.drop_index(op.f('ix_chat_messages_character_id'), table_name='chat_messages')
-    op.drop_table('chat_messages')
-    op.drop_index(op.f('ix_audit_events_trace_id'), table_name='audit_events')
-    op.drop_index(op.f('ix_audit_events_run_id'), table_name='audit_events')
-    op.drop_index(op.f('ix_audit_events_pivot'), table_name='audit_events')
-    op.drop_index(op.f('ix_audit_events_character_id'), table_name='audit_events')
-    op.drop_table('audit_events')
-    op.drop_index(op.f('ix_world_relations_subject_id'), table_name='world_relations')
-    op.drop_index(op.f('ix_world_relations_object_id'), table_name='world_relations')
-    op.drop_index(op.f('ix_world_relations_character_id'), table_name='world_relations')
-    op.drop_table('world_relations')
-    op.drop_index(op.f('ix_runs_status'), table_name='runs')
-    op.drop_index(op.f('ix_runs_session_id'), table_name='runs')
-    op.drop_index(op.f('ix_runs_character_id'), table_name='runs')
-    op.drop_table('runs')
-    op.drop_index(op.f('ix_plans_status'), table_name='plans')
-    op.drop_index(op.f('ix_plans_goal_id'), table_name='plans')
-    op.drop_table('plans')
-    op.drop_index(op.f('ix_personality_proposals_status'), table_name='personality_proposals')
-    op.drop_index(op.f('ix_personality_proposals_character_id'), table_name='personality_proposals')
-    op.drop_table('personality_proposals')
-    op.drop_index(op.f('ix_memory_links_target_memory_id'), table_name='memory_links')
-    op.drop_index(op.f('ix_memory_links_source_memory_id'), table_name='memory_links')
-    op.drop_index(op.f('ix_memory_links_character_id'), table_name='memory_links')
-    op.drop_table('memory_links')
-    op.drop_index(op.f('ix_memory_candidates_status'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_import_job_id'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_cycle_id'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_character_id'), table_name='memory_candidates')
-    op.drop_table('memory_candidates')
-    op.drop_index(op.f('ix_lorebook_entries_lorebook_id'), table_name='lorebook_entries')
-    op.drop_index(op.f('ix_lorebook_entries_bound_entity_id'), table_name='lorebook_entries')
-    op.drop_table('lorebook_entries')
-    op.drop_index(op.f('ix_import_items_import_job_id'), table_name='import_items')
-    op.drop_index(op.f('ix_import_items_character_id'), table_name='import_items')
-    op.drop_table('import_items')
-    op.drop_index(op.f('ix_evolution_candidates_status'), table_name='evolution_candidates')
-    op.drop_index(op.f('ix_evolution_candidates_cycle_id'), table_name='evolution_candidates')
-    op.drop_index(op.f('ix_evolution_candidates_character_id'), table_name='evolution_candidates')
-    op.drop_table('evolution_candidates')
-    op.drop_index(op.f('ix_curiosity_questions_cycle_id'), table_name='curiosity_questions')
-    op.drop_index(op.f('ix_curiosity_questions_character_id'), table_name='curiosity_questions')
-    op.drop_table('curiosity_questions')
-    op.drop_index(op.f('ix_character_profile_candidates_status'), table_name='character_profile_candidates')
-    op.drop_index(op.f('ix_character_profile_candidates_import_job_id'), table_name='character_profile_candidates')
-    op.drop_index(op.f('ix_character_profile_candidates_character_id'), table_name='character_profile_candidates')
-    op.drop_table('character_profile_candidates')
-    op.drop_table('user_roles')
-    op.drop_index(op.f('ix_time_anniversaries_character_id'), table_name='time_anniversaries')
-    op.drop_table('time_anniversaries')
-    op.drop_table('role_permissions')
-    op.drop_index(op.f('ix_personality_versions_character_id'), table_name='personality_versions')
-    op.drop_table('personality_versions')
-    op.drop_index(op.f('ix_memories_status'), table_name='memories')
-    op.drop_index(op.f('ix_memories_character_id'), table_name='memories')
-    op.drop_table('memories')
-    op.drop_index(op.f('ix_lorebooks_status'), table_name='lorebooks')
-    op.drop_index(op.f('ix_lorebooks_scope'), table_name='lorebooks')
-    op.drop_index(op.f('ix_lorebooks_owner_scope'), table_name='lorebooks')
-    op.drop_index(op.f('ix_lorebooks_character_id'), table_name='lorebooks')
-    op.drop_table('lorebooks')
-    op.drop_index(op.f('ix_goals_status'), table_name='goals')
-    op.drop_index(op.f('ix_goals_level'), table_name='goals')
-    op.drop_index(op.f('ix_goals_character_id'), table_name='goals')
-    op.drop_table('goals')
-    op.drop_index(op.f('ix_chat_sessions_status'), table_name='chat_sessions')
-    op.drop_index(op.f('ix_chat_sessions_owner_scope'), table_name='chat_sessions')
-    op.drop_index(op.f('ix_chat_sessions_character_id'), table_name='chat_sessions')
-    op.drop_table('chat_sessions')
-    op.drop_index(op.f('ix_character_world_entities_type'), table_name='character_world_entities')
-    op.drop_index(op.f('ix_character_world_entities_status'), table_name='character_world_entities')
-    op.drop_index(op.f('ix_character_world_entities_character_id'), table_name='character_world_entities')
-    op.drop_table('character_world_entities')
-    op.drop_index(op.f('ix_character_import_jobs_status'), table_name='character_import_jobs')
-    op.drop_index(op.f('ix_character_import_jobs_material_type'), table_name='character_import_jobs')
-    op.drop_index(op.f('ix_character_import_jobs_checksum'), table_name='character_import_jobs')
-    op.drop_index(op.f('ix_character_import_jobs_character_id'), table_name='character_import_jobs')
-    op.drop_table('character_import_jobs')
-    op.drop_table('character_emotion_states')
-    op.drop_index(op.f('ix_big_cycles_status'), table_name='big_cycles')
-    op.drop_index(op.f('ix_big_cycles_completed_at'), table_name='big_cycles')
-    op.drop_index(op.f('ix_big_cycles_character_id'), table_name='big_cycles')
-    op.drop_table('big_cycles')
-    op.drop_index(op.f('ix_world_entities_type'), table_name='world_entities')
-    op.drop_table('world_entities')
-    op.drop_index(op.f('ix_users_username'), table_name='users')
-    op.drop_table('users')
-    op.drop_table('tool_policies')
-    op.drop_index(op.f('ix_skills_status'), table_name='skills')
-    op.drop_table('skills')
-    op.drop_index(op.f('ix_roles_name'), table_name='roles')
-    op.drop_table('roles')
-    op.drop_index(op.f('ix_permissions_resource'), table_name='permissions')
-    op.drop_table('permissions')
-    op.drop_table('perception_channels')
-    op.drop_index(op.f('ix_pending_confirmations_status'), table_name='pending_confirmations')
-    op.drop_index(op.f('ix_pending_confirmations_run_id'), table_name='pending_confirmations')
-    op.drop_index(op.f('ix_pending_confirmations_character_id'), table_name='pending_confirmations')
-    op.drop_table('pending_confirmations')
-    op.drop_table('model_endpoint_overrides')
-    op.drop_index(op.f('ix_mcp_servers_status'), table_name='mcp_servers')
-    op.drop_table('mcp_servers')
-    op.drop_index(op.f('ix_idempotency_keys_trace_id'), table_name='idempotency_keys')
-    op.drop_index(op.f('ix_idempotency_keys_scope'), table_name='idempotency_keys')
-    op.drop_index(op.f('ix_idempotency_keys_key'), table_name='idempotency_keys')
-    op.drop_index(op.f('ix_idempotency_keys_expires_at'), table_name='idempotency_keys')
-    op.drop_table('idempotency_keys')
-    op.drop_table('generation_preferences')
-    op.drop_index(op.f('ix_characters_template_key'), table_name='characters')
-    op.drop_index(op.f('ix_characters_status'), table_name='characters')
-    op.drop_index(op.f('ix_characters_source_template_id'), table_name='characters')
-    op.drop_index(op.f('ix_characters_owner_scope'), table_name='characters')
-    op.drop_index(op.f('ix_characters_is_system_template'), table_name='characters')
-    op.drop_table('characters')
-    op.drop_table('agent_roster')
-    # ### end Alembic commands ###

backend/alembic/versions/001_镜生域_灵胚_执镜关系_命台_魂籍表与人物增量列.py

@@ -1,108 +0,0 @@
-"""镜生域：灵胚、执镜关系、命台、魂籍表与人物增量列
-
-Revision ID: 001
-Revises: 000
-Create Date: 2026-08-21 22:23:35.864890
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '001'
-down_revision: Union[str, Sequence[str], None] = '000'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('embryo_drafts',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('source', sa.String(length=40), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('description', sa.Text(), nullable=True),
-    sa.Column('identity_baseline_json', sa.Text(), nullable=False),
-    sa.Column('rehearsals_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_embryo_drafts_owner_scope'), 'embryo_drafts', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_embryo_drafts_status'), 'embryo_drafts', ['status'], unique=False)
-    op.create_table('custodianships',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('custodian_scope', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_custodianships_character_id'), 'custodianships', ['character_id'], unique=True)
-    op.create_index(op.f('ix_custodianships_custodian_scope'), 'custodianships', ['custodian_scope'], unique=False)
-    op.create_table('identity_records',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('version', sa.Integer(), nullable=False),
-    sa.Column('payload_json', sa.Text(), nullable=False),
-    sa.Column('digest', sa.String(length=64), nullable=False),
-    sa.Column('signature', sa.String(length=128), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('character_id', 'version', name='uq_identity_char_version')
-    )
-    op.create_index(op.f('ix_identity_records_character_id'), 'identity_records', ['character_id'], unique=False)
-    op.create_table('runtime_seats',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('epoch', sa.Integer(), nullable=False),
-    sa.Column('holder', sa.String(length=120), nullable=True),
-    sa.Column('lease_expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_runtime_seats_character_id'), 'runtime_seats', ['character_id'], unique=True)
-    op.add_column('characters', sa.Column('source', sa.String(length=40), server_default='original', nullable=False))
-    op.add_column('characters', sa.Column('identity_baseline_json', sa.Text(), server_default='{}', nullable=False))
-    op.add_column('characters', sa.Column('death_requested_at', sa.DateTime(timezone=True), nullable=True))
-    op.add_column('characters', sa.Column('calm_period_until', sa.DateTime(timezone=True), nullable=True))
-    op.add_column('characters', sa.Column('died_at', sa.DateTime(timezone=True), nullable=True))
-    op.create_index(op.f('ix_characters_source'), 'characters', ['source'], unique=False)
-    op.add_column('runs', sa.Column('kind', sa.String(length=40), server_default='foreground', nullable=False))
-    # SQLite 不支持 ALTER COLUMN，用 batch 模式跨方言改 runs.character_id 可空（试演 Run 无人物）
-    with op.batch_alter_table('runs') as batch_op:
-        batch_op.alter_column('character_id', existing_type=sa.String(length=80), nullable=True)
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    with op.batch_alter_table('runs') as batch_op:
-        batch_op.alter_column('character_id', existing_type=sa.String(length=80), nullable=False)
-    op.drop_column('runs', 'kind')
-    op.drop_index(op.f('ix_characters_source'), table_name='characters')
-    op.drop_column('characters', 'died_at')
-    op.drop_column('characters', 'calm_period_until')
-    op.drop_column('characters', 'death_requested_at')
-    op.drop_column('characters', 'identity_baseline_json')
-    op.drop_column('characters', 'source')
-    op.drop_index(op.f('ix_runtime_seats_character_id'), table_name='runtime_seats')
-    op.drop_table('runtime_seats')
-    op.drop_index(op.f('ix_identity_records_character_id'), table_name='identity_records')
-    op.drop_table('identity_records')
-    op.drop_index(op.f('ix_custodianships_custodian_scope'), table_name='custodianships')
-    op.drop_index(op.f('ix_custodianships_character_id'), table_name='custodianships')
-    op.drop_table('custodianships')
-    op.drop_index(op.f('ix_embryo_drafts_status'), table_name='embryo_drafts')
-    op.drop_index(op.f('ix_embryo_drafts_owner_scope'), table_name='embryo_drafts')
-    op.drop_table('embryo_drafts')
-    # ### end Alembic commands ###

backend/alembic/versions/002_add_chat_session_owner_scope.py

@@ -0,0 +1,56 @@
+"""add_chat_session_owner_scope
+
+Revision ID: 002
+Revises: 001
+Create Date: 2026-07-14 07:54:32.969191
+
+"""
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = '002'
+down_revision: str | Sequence[str] | None = '001'
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    is_sqlite = conn.engine.dialect.name == "sqlite"
+
+    if is_sqlite:
+        # SQLite：用 batch 模式加列（新增 NOT NULL 列需 batch recreating）
+        with op.batch_alter_table("chat_sessions") as batch_op:
+            batch_op.add_column(
+                sa.Column("owner_scope", sa.String(length=80), nullable=False, server_default=""),
+            )
+            batch_op.create_index("ix_chat_sessions_owner_scope", ["owner_scope"])
+        # 移除 server_default（仅 DDL 阶段需要）
+        with op.batch_alter_table("chat_sessions") as batch_op:
+            batch_op.alter_column("owner_scope", server_default=None)
+    else:
+        op.add_column(
+            "chat_sessions",
+            sa.Column("owner_scope", sa.String(length=80), nullable=False, server_default=""),
+        )
+        op.create_index(
+            op.f("ix_chat_sessions_owner_scope"), "chat_sessions", ["owner_scope"], unique=False
+        )
+        op.alter_column("chat_sessions", "owner_scope", server_default=None)
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    is_sqlite = conn.engine.dialect.name == "sqlite"
+
+    if is_sqlite:
+        with op.batch_alter_table("chat_sessions") as batch_op:
+            batch_op.drop_index("ix_chat_sessions_owner_scope")
+            batch_op.drop_column("owner_scope")
+    else:
+        op.drop_index(op.f("ix_chat_sessions_owner_scope"), table_name="chat_sessions")
+        op.drop_column("chat_sessions", "owner_scope")

backend/alembic/versions/002_镜树域_主题树_节点_引文锚_归真记录_移栽谱系.py

@@ -1,125 +0,0 @@
-"""镜树域：主题树、节点、引文锚、归真记录、移栽谱系
-
-Revision ID: 002
-Revises: 001
-Create Date: 2026-08-21 22:49:03.731149
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '002'
-down_revision: Union[str, Sequence[str], None] = '001'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('tree_transplants',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('source_tree_id', sa.String(length=80), nullable=False),
-    sa.Column('source_node_id', sa.String(length=80), nullable=False),
-    sa.Column('new_tree_id', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_tree_transplants_new_tree_id'), 'tree_transplants', ['new_tree_id'], unique=False)
-    op.create_index(op.f('ix_tree_transplants_source_tree_id'), 'tree_transplants', ['source_tree_id'], unique=False)
-    op.create_table('mirror_trees',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('title', sa.String(length=300), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('default_realm', sa.String(length=40), nullable=False),
-    sa.Column('working_entry_node_id', sa.String(length=80), nullable=True),
-    sa.Column('transplanted_from_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_mirror_trees_character_id'), 'mirror_trees', ['character_id'], unique=False)
-    op.create_index(op.f('ix_mirror_trees_status'), 'mirror_trees', ['status'], unique=False)
-    op.create_table('canonizations',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('tree_id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('scope', sa.String(length=40), nullable=False),
-    sa.Column('world_id', sa.String(length=80), nullable=True),
-    sa.Column('endpoint_node_id', sa.String(length=80), nullable=False),
-    sa.Column('path_nodes_json', sa.Text(), nullable=False),
-    sa.Column('confirmed_by', sa.String(length=80), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['tree_id'], ['mirror_trees.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_canonizations_character_id'), 'canonizations', ['character_id'], unique=False)
-    op.create_index(op.f('ix_canonizations_endpoint_node_id'), 'canonizations', ['endpoint_node_id'], unique=False)
-    op.create_index(op.f('ix_canonizations_scope'), 'canonizations', ['scope'], unique=False)
-    op.create_index(op.f('ix_canonizations_tree_id'), 'canonizations', ['tree_id'], unique=False)
-    op.create_table('tree_nodes',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('tree_id', sa.String(length=80), nullable=False),
-    sa.Column('parent_node_id', sa.String(length=80), nullable=True),
-    sa.Column('node_type', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=40), nullable=False),
-    sa.Column('author', sa.String(length=40), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('realm', sa.String(length=40), nullable=False),
-    sa.Column('generation_meta_json', sa.Text(), nullable=False),
-    sa.Column('supersedes_node_id', sa.String(length=80), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['parent_node_id'], ['tree_nodes.id'], ),
-    sa.ForeignKeyConstraint(['tree_id'], ['mirror_trees.id'], ),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('tree_id', 'supersedes_node_id', name='uq_tree_node_supersedes')
-    )
-    op.create_index(op.f('ix_tree_nodes_node_type'), 'tree_nodes', ['node_type'], unique=False)
-    op.create_index(op.f('ix_tree_nodes_parent_node_id'), 'tree_nodes', ['parent_node_id'], unique=False)
-    op.create_index(op.f('ix_tree_nodes_status'), 'tree_nodes', ['status'], unique=False)
-    op.create_index(op.f('ix_tree_nodes_tree_id'), 'tree_nodes', ['tree_id'], unique=False)
-    op.create_table('citations',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('node_id', sa.String(length=80), nullable=False),
-    sa.Column('target_type', sa.String(length=40), nullable=False),
-    sa.Column('locator_json', sa.Text(), nullable=False),
-    sa.Column('snapshot', sa.Text(), nullable=False),
-    sa.Column('source_id', sa.String(length=200), nullable=False),
-    sa.Column('source_version', sa.Integer(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['node_id'], ['tree_nodes.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_citations_node_id'), 'citations', ['node_id'], unique=False)
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(op.f('ix_citations_node_id'), table_name='citations')
-    op.drop_table('citations')
-    op.drop_index(op.f('ix_tree_nodes_tree_id'), table_name='tree_nodes')
-    op.drop_index(op.f('ix_tree_nodes_status'), table_name='tree_nodes')
-    op.drop_index(op.f('ix_tree_nodes_parent_node_id'), table_name='tree_nodes')
-    op.drop_index(op.f('ix_tree_nodes_node_type'), table_name='tree_nodes')
-    op.drop_table('tree_nodes')
-    op.drop_index(op.f('ix_canonizations_tree_id'), table_name='canonizations')
-    op.drop_index(op.f('ix_canonizations_scope'), table_name='canonizations')
-    op.drop_index(op.f('ix_canonizations_endpoint_node_id'), table_name='canonizations')
-    op.drop_index(op.f('ix_canonizations_character_id'), table_name='canonizations')
-    op.drop_table('canonizations')
-    op.drop_index(op.f('ix_mirror_trees_status'), table_name='mirror_trees')
-    op.drop_index(op.f('ix_mirror_trees_character_id'), table_name='mirror_trees')
-    op.drop_table('mirror_trees')
-    op.drop_index(op.f('ix_tree_transplants_source_tree_id'), table_name='tree_transplants')
-    op.drop_index(op.f('ix_tree_transplants_new_tree_id'), table_name='tree_transplants')
-    op.drop_table('tree_transplants')
-    # ### end Alembic commands ###

backend/alembic/versions/003_add_daoti_soul_fields_to_character.py

@@ -0,0 +1,36 @@
+"""add daoti soul fields to character
+
+Revision ID: 003
+Revises: 002
+Create Date: 2026-07-24 10:47:40.993422
+
+"""
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = '003'
+down_revision: str | Sequence[str] | None = '002'
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('characters', sa.Column('personality_summary', sa.Text(), nullable=True))
+    op.add_column('characters', sa.Column('mission', sa.Text(), nullable=True))
+    op.add_column('characters', sa.Column('safety_guidelines', sa.Text(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('characters', 'safety_guidelines')
+    op.drop_column('characters', 'mission')
+    op.drop_column('characters', 'personality_summary')
+    # ### end Alembic commands ###

backend/alembic/versions/003_退役旧会话模型_删除_chat_情绪_纪念日表与_runs_旧会话外键.py

@@ -1,114 +0,0 @@
-"""退役旧会话模型：删除 chat/情绪/纪念日表与 runs 旧会话外键
-
-Revision ID: 003
-Revises: 002
-Create Date: 2026-08-21 23:17:17.055812
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '003'
-down_revision: Union[str, Sequence[str], None] = '002'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # 顺序约束：先去掉 runs.session_id（batch 反射 runs 外键时 chat_sessions 须仍存在），
-    # 再删除旧会话相关表；SQLite 下 batch 自动处理索引与无名外键。
-    op.drop_index('ix_runs_session_id', table_name='runs')
-    with op.batch_alter_table('runs') as batch_op:
-        batch_op.drop_column('session_id')
-    op.drop_table('character_emotion_states')
-    op.drop_index(op.f('ix_chat_sessions_character_id'), table_name='chat_sessions')
-    op.drop_index(op.f('ix_chat_sessions_owner_scope'), table_name='chat_sessions')
-    op.drop_index(op.f('ix_chat_sessions_status'), table_name='chat_sessions')
-    op.drop_table('chat_sessions')
-    op.drop_index(op.f('ix_chat_messages_character_id'), table_name='chat_messages')
-    op.drop_index(op.f('ix_chat_messages_run_id'), table_name='chat_messages')
-    op.drop_index(op.f('ix_chat_messages_session_id'), table_name='chat_messages')
-    op.drop_table('chat_messages')
-    op.drop_index(op.f('ix_time_anniversaries_character_id'), table_name='time_anniversaries')
-    op.drop_table('time_anniversaries')
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    # 先重建 chat 表，再经 batch 恢复 runs.session_id 列与外键（SQLite 安全）
-    op.create_table('time_anniversaries',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('name', sa.VARCHAR(length=200), nullable=False),
-    sa.Column('calendar', sa.VARCHAR(length=20), nullable=False),
-    sa.Column('date', sa.VARCHAR(length=20), nullable=False),
-    sa.Column('recurs_yearly', sa.BOOLEAN(), nullable=False),
-    sa.Column('kind', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('subject_type', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('source', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('metadata_json', sa.TEXT(), nullable=False),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_time_anniversaries_character_id'), 'time_anniversaries', ['character_id'], unique=False)
-    op.create_table('chat_messages',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('session_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('role', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('content', sa.TEXT(), nullable=False),
-    sa.Column('modality', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('run_id', sa.VARCHAR(length=80), nullable=True),
-    sa.Column('metadata_json', sa.TEXT(), nullable=False),
-    sa.Column('sensitivity', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('versions_json', sa.TEXT(), nullable=False),
-    sa.Column('active_version_idx', sa.INTEGER(), nullable=False),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('deleted_at', sa.DATETIME(), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['run_id'], ['runs.id'], ),
-    sa.ForeignKeyConstraint(['session_id'], ['chat_sessions.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_chat_messages_session_id'), 'chat_messages', ['session_id'], unique=False)
-    op.create_index(op.f('ix_chat_messages_run_id'), 'chat_messages', ['run_id'], unique=False)
-    op.create_index(op.f('ix_chat_messages_character_id'), 'chat_messages', ['character_id'], unique=False)
-    op.create_table('chat_sessions',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('title', sa.VARCHAR(length=200), nullable=True),
-    sa.Column('status', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('owner_scope', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_chat_sessions_status'), 'chat_sessions', ['status'], unique=False)
-    op.create_index(op.f('ix_chat_sessions_owner_scope'), 'chat_sessions', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_chat_sessions_character_id'), 'chat_sessions', ['character_id'], unique=False)
-    op.create_table('character_emotion_states',
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('mood', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('intensity', sa.FLOAT(), nullable=False),
-    sa.Column('baseline_mood', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('baseline_intensity', sa.FLOAT(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.Column('last_trigger_event_id', sa.VARCHAR(length=80), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('character_id')
-    )
-    with op.batch_alter_table('runs') as batch_op:
-        batch_op.add_column(sa.Column('session_id', sa.String(length=80), nullable=True))
-        batch_op.create_foreign_key('fk_runs_session_id', 'chat_sessions', ['session_id'], ['id'])
-        batch_op.create_index('ix_runs_session_id', ['session_id'])
-    # ### end Alembic commands ###

backend/alembic/versions/004_add_lorebook_tables.py

@@ -0,0 +1,81 @@
+"""add lorebook tables
+
+Revision ID: 004
+Revises: 003
+Create Date: 2026-07-24 12:20:38.453954
+
+"""
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = '004'
+down_revision: str | Sequence[str] | None = '003'
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('lorebooks',
+    sa.Column('id', sa.String(length=80), nullable=False),
+    sa.Column('character_id', sa.String(length=80), nullable=True),
+    sa.Column('name', sa.String(length=200), nullable=False),
+    sa.Column('description', sa.Text(), nullable=False),
+    sa.Column('scan_depth', sa.Integer(), nullable=True),
+    sa.Column('token_budget', sa.Integer(), nullable=True),
+    sa.Column('recursive_scanning', sa.Boolean(), nullable=False),
+    sa.Column('scope', sa.String(length=40), nullable=False),
+    sa.Column('status', sa.String(length=40), nullable=False),
+    sa.Column('owner_scope', sa.String(length=80), nullable=False),
+    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
+    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
+    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_lorebooks_character_id'), 'lorebooks', ['character_id'], unique=False)
+    op.create_index(op.f('ix_lorebooks_owner_scope'), 'lorebooks', ['owner_scope'], unique=False)
+    op.create_index(op.f('ix_lorebooks_scope'), 'lorebooks', ['scope'], unique=False)
+    op.create_index(op.f('ix_lorebooks_status'), 'lorebooks', ['status'], unique=False)
+    op.create_table('lorebook_entries',
+    sa.Column('id', sa.String(length=80), nullable=False),
+    sa.Column('lorebook_id', sa.String(length=80), nullable=False),
+    sa.Column('keys_json', sa.Text(), nullable=False),
+    sa.Column('content', sa.Text(), nullable=False),
+    sa.Column('secondary_keys_json', sa.Text(), nullable=False),
+    sa.Column('constant', sa.Boolean(), nullable=False),
+    sa.Column('selective', sa.Boolean(), nullable=False),
+    sa.Column('enabled', sa.Boolean(), nullable=False),
+    sa.Column('case_sensitive', sa.Boolean(), nullable=False),
+    sa.Column('use_regex', sa.Boolean(), nullable=False),
+    sa.Column('position', sa.String(length=40), nullable=False),
+    sa.Column('insertion_order', sa.Integer(), nullable=False),
+    sa.Column('priority', sa.Integer(), nullable=False),
+    sa.Column('comment', sa.String(length=500), nullable=False),
+    sa.Column('bound_entity_id', sa.String(length=80), nullable=True),
+    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
+    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
+    sa.ForeignKeyConstraint(['lorebook_id'], ['lorebooks.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_lorebook_entries_bound_entity_id'), 'lorebook_entries', ['bound_entity_id'], unique=False)
+    op.create_index(op.f('ix_lorebook_entries_lorebook_id'), 'lorebook_entries', ['lorebook_id'], unique=False)
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_index(op.f('ix_lorebook_entries_lorebook_id'), table_name='lorebook_entries')
+    op.drop_index(op.f('ix_lorebook_entries_bound_entity_id'), table_name='lorebook_entries')
+    op.drop_table('lorebook_entries')
+    op.drop_index(op.f('ix_lorebooks_status'), table_name='lorebooks')
+    op.drop_index(op.f('ix_lorebooks_scope'), table_name='lorebooks')
+    op.drop_index(op.f('ix_lorebooks_owner_scope'), table_name='lorebooks')
+    op.drop_index(op.f('ix_lorebooks_character_id'), table_name='lorebooks')
+    op.drop_table('lorebooks')
+    # ### end Alembic commands ###

backend/alembic/versions/004_息壤记忆域_三级记忆表重建与触发_实录_退役旧记忆表.py

@@ -1,102 +0,0 @@
-"""息壤记忆域：三级记忆表重建与触发/实录，退役旧记忆表
-
-Revision ID: 004
-Revises: 003
-Create Date: 2026-08-22
-
-旧 memories/memory_links 随旧记忆管线退役整体删除（开发数据丢弃语义，data-model §9），
-新表按 app/models/xirang.py 重建。
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-revision: str = '004'
-down_revision: Union[str, Sequence[str], None] = '003'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    op.drop_table('memory_links')
-    op.drop_table('memories')
-    op.create_table('memories',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('tier', sa.String(length=20), nullable=False),
-    sa.Column('type', sa.String(length=40), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('source', sa.String(length=20), nullable=False),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('source_refs_json', sa.Text(), nullable=False),
-    sa.Column('sensitivity', sa.String(length=20), nullable=False),
-    sa.Column('priority', sa.Integer(), nullable=False),
-    sa.Column('confidence', sa.Float(), nullable=False),
-    sa.Column('vitality', sa.Float(), nullable=False),
-    sa.Column('valid_until', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('realm', sa.String(length=40), nullable=False),
-    sa.Column('prev_version_id', sa.String(length=80), nullable=True),
-    sa.Column('recall_count', sa.Integer(), nullable=False),
-    sa.Column('last_recalled_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_memories_character_id'), 'memories', ['character_id'], unique=False)
-    op.create_index(op.f('ix_memories_tier'), 'memories', ['tier'], unique=False)
-    op.create_index(op.f('ix_memories_type'), 'memories', ['type'], unique=False)
-    op.create_index(op.f('ix_memories_status'), 'memories', ['status'], unique=False)
-    op.create_index(op.f('ix_memories_prev_version_id'), 'memories', ['prev_version_id'], unique=False)
-    op.create_table('memory_triggers',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('memory_id', sa.String(length=80), nullable=False),
-    sa.Column('kind', sa.String(length=20), nullable=False),
-    sa.Column('pattern', sa.String(length=200), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['memory_id'], ['memories.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_table('factual_records',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('canonization_id', sa.String(length=80), nullable=False),
-    sa.Column('evidence_json', sa.Text(), nullable=False),
-    sa.Column('summary', sa.Text(), nullable=False),
-    sa.Column('occurred_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-
-
-def downgrade() -> None:
-    op.drop_table('factual_records')
-    op.drop_table('memory_triggers')
-    op.drop_table('memories')
-    op.create_table('memories',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('title', sa.String(length=200), nullable=True),
-    sa.Column('content', sa.Text(), nullable=False),
-    sa.Column('source', sa.String(length=40), nullable=False),
-    sa.Column('importance', sa.Float(), nullable=False),
-    sa.Column('sensitivity', sa.String(length=20), nullable=False),
-    sa.Column('temporal_context_json', sa.Text(), nullable=False),
-    sa.Column('evidence_ids_json', sa.Text(), nullable=False),
-    sa.Column('expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('deleted_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_table('memory_links',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('from_memory_id', sa.String(length=80), nullable=False),
-    sa.Column('to_memory_id', sa.String(length=80), nullable=False),
-    sa.Column('relation', sa.String(length=40), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['from_memory_id'], ['memories.id'], ),
-    sa.ForeignKeyConstraint(['to_memory_id'], ['memories.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )

backend/alembic/versions/005_运行归属用户列_runs_owner_id_用量计量透传神识.py

@@ -1,40 +0,0 @@
-"""运行归属用户列_runs_owner_id_用量计量透传神识
-
-Revision ID: 005
-Revises: 004
-Create Date: 2026-08-27 10:31:10.225717
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '005'
-down_revision: Union[str, Sequence[str], None] = '004'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_index(op.f('ix_factual_records_canonization_id'), 'factual_records', ['canonization_id'], unique=False)
-    op.create_index(op.f('ix_factual_records_character_id'), 'factual_records', ['character_id'], unique=False)
-    op.create_index(op.f('ix_memory_triggers_memory_id'), 'memory_triggers', ['memory_id'], unique=False)
-    op.add_column('runs', sa.Column('owner_id', sa.String(length=80), server_default='', nullable=False))
-    op.create_index(op.f('ix_runs_owner_id'), 'runs', ['owner_id'], unique=False)
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(op.f('ix_runs_owner_id'), table_name='runs')
-    op.drop_column('runs', 'owner_id')
-    op.drop_index(op.f('ix_memory_triggers_memory_id'), table_name='memory_triggers')
-    op.drop_index(op.f('ix_factual_records_character_id'), table_name='factual_records')
-    op.drop_index(op.f('ix_factual_records_canonization_id'), table_name='factual_records')
-    # ### end Alembic commands ###

backend/alembic/versions/006_百工域_能力注册表_授契行契_调用记录_请命超时改造_退役旧策略与端点覆盖表.py

@@ -1,153 +0,0 @@
-"""百工域_能力注册表_授契行契_调用记录_请命超时改造_退役旧策略与端点覆盖表
-
-Revision ID: 006
-Revises: 005
-Create Date: 2026-08-27 18:52:47.720303
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '006'
-down_revision: Union[str, Sequence[str], None] = '005'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('capabilities',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('executor_type', sa.String(length=20), nullable=False),
-    sa.Column('executor_ref', sa.String(length=200), nullable=False),
-    sa.Column('params_schema_json', sa.Text(), nullable=False),
-    sa.Column('risk_dims_json', sa.Text(), nullable=False),
-    sa.Column('data_scope', sa.Text(), nullable=False),
-    sa.Column('destinations', sa.Text(), nullable=False),
-    sa.Column('source', sa.String(length=20), nullable=False),
-    sa.Column('version', sa.String(length=40), nullable=False),
-    sa.Column('consent_mode', sa.String(length=10), nullable=False),
-    sa.Column('enabled', sa.Boolean(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_capabilities_owner_scope'), 'capabilities', ['owner_scope'], unique=False)
-    op.create_index('uq_capabilities_owner_name', 'capabilities', ['owner_scope', 'name'], unique=True)
-    op.create_table('mandates',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('capability_id', sa.String(length=80), nullable=False),
-    sa.Column('kind', sa.String(length=10), nullable=False),
-    sa.Column('scope_json', sa.JSON(), nullable=False),
-    sa.Column('expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('budget_total', sa.Integer(), nullable=False),
-    sa.Column('budget_used', sa.Integer(), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('granted_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('revoked_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['capability_id'], ['capabilities.id'], ),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_mandates_capability_id'), 'mandates', ['capability_id'], unique=False)
-    op.create_index(op.f('ix_mandates_character_id'), 'mandates', ['character_id'], unique=False)
-    op.create_index(op.f('ix_mandates_owner_scope'), 'mandates', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_mandates_status'), 'mandates', ['status'], unique=False)
-    op.create_table('tool_calls',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('capability_id', sa.String(length=80), nullable=False),
-    sa.Column('trace_id', sa.String(length=80), nullable=True),
-    sa.Column('decision', sa.String(length=40), nullable=False),
-    sa.Column('mandate_id', sa.String(length=80), nullable=True),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('error_code', sa.String(length=40), nullable=True),
-    sa.Column('input_digest', sa.Text(), nullable=False),
-    sa.Column('output_digest', sa.Text(), nullable=False),
-    sa.Column('evidence_json', sa.JSON(), nullable=False),
-    sa.Column('duration_ms', sa.Integer(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['run_id'], ['runs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_tool_calls_capability_id'), 'tool_calls', ['capability_id'], unique=False)
-    op.create_index(op.f('ix_tool_calls_character_id'), 'tool_calls', ['character_id'], unique=False)
-    op.create_index(op.f('ix_tool_calls_created_at'), 'tool_calls', ['created_at'], unique=False)
-    op.create_index(op.f('ix_tool_calls_run_id'), 'tool_calls', ['run_id'], unique=False)
-    op.create_index(op.f('ix_tool_calls_trace_id'), 'tool_calls', ['trace_id'], unique=False)
-    op.drop_index(op.f('ix_skills_status'), table_name='skills')
-    op.drop_table('skills')
-    op.drop_table('tool_policies')
-    op.drop_table('model_endpoint_overrides')
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('model_endpoint_overrides',
-    sa.Column('logical_model_name', sa.VARCHAR(length=120), nullable=False),
-    sa.Column('endpoint_name', sa.VARCHAR(length=120), nullable=False),
-    sa.Column('base_url', sa.VARCHAR(length=500), nullable=True),
-    sa.Column('api_key', sa.VARCHAR(length=500), nullable=True),
-    sa.Column('status', sa.VARCHAR(length=40), nullable=True),
-    sa.Column('weight', sa.INTEGER(), nullable=True),
-    sa.Column('priority', sa.INTEGER(), nullable=True),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.PrimaryKeyConstraint('logical_model_name', 'endpoint_name')
-    )
-    op.create_table('tool_policies',
-    sa.Column('name', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('description', sa.TEXT(), nullable=False),
-    sa.Column('risk_level', sa.VARCHAR(length=20), nullable=False),
-    sa.Column('permission_policy', sa.VARCHAR(length=20), nullable=False),
-    sa.Column('side_effect', sa.BOOLEAN(), nullable=False),
-    sa.Column('audit_required', sa.BOOLEAN(), nullable=False),
-    sa.Column('source', sa.VARCHAR(length=20), nullable=False),
-    sa.Column('enabled', sa.BOOLEAN(), nullable=False),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.PrimaryKeyConstraint('name')
-    )
-    op.create_table('skills',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('name', sa.VARCHAR(length=120), nullable=False),
-    sa.Column('description', sa.TEXT(), nullable=False),
-    sa.Column('trigger', sa.TEXT(), nullable=False),
-    sa.Column('prompt_fragment', sa.TEXT(), nullable=False),
-    sa.Column('tool_bindings_json', sa.TEXT(), nullable=False),
-    sa.Column('risk_level', sa.VARCHAR(length=8), nullable=False),
-    sa.Column('status', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.PrimaryKeyConstraint('id'),
-    sa.UniqueConstraint('name')
-    )
-    op.create_index(op.f('ix_skills_status'), 'skills', ['status'], unique=False)
-    op.drop_index(op.f('ix_tool_calls_trace_id'), table_name='tool_calls')
-    op.drop_index(op.f('ix_tool_calls_run_id'), table_name='tool_calls')
-    op.drop_index(op.f('ix_tool_calls_created_at'), table_name='tool_calls')
-    op.drop_index(op.f('ix_tool_calls_character_id'), table_name='tool_calls')
-    op.drop_index(op.f('ix_tool_calls_capability_id'), table_name='tool_calls')
-    op.drop_table('tool_calls')
-    op.drop_index(op.f('ix_mandates_status'), table_name='mandates')
-    op.drop_index(op.f('ix_mandates_owner_scope'), table_name='mandates')
-    op.drop_index(op.f('ix_mandates_character_id'), table_name='mandates')
-    op.drop_index(op.f('ix_mandates_capability_id'), table_name='mandates')
-    op.drop_table('mandates')
-    op.drop_index('uq_capabilities_owner_name', table_name='capabilities')
-    op.drop_index(op.f('ix_capabilities_owner_scope'), table_name='capabilities')
-    op.drop_table('capabilities')
-    # ### end Alembic commands ###

backend/alembic/versions/007_缘契域_契约与事件_铸魂分灵_河图境界与实体_实录作用域_.py

@@ -1,170 +0,0 @@
-"""缘契域_契约与事件_铸魂分灵_河图境界与实体_实录作用域_退役旧人格驱动演化世界表
-
-Revision ID: 007
-Revises: 006
-Create Date: 2026-08-27 19:32:08.478484
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '007'
-down_revision: Union[str, Sequence[str], None] = '006'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # 旧世界表退役重建（世界权威移交河图域 hetu；开发数据丢弃）
-    op.drop_table('world_entities')
-    op.drop_table('character_world_entities')
-    op.drop_table('world_relations')
-
-    # 缘契域
-    op.create_table('covenants',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('dimensions_json', sa.Text(), nullable=False),
-    sa.Column('primary_title', sa.String(length=120), nullable=True),
-    sa.Column('boundaries_json', sa.Text(), nullable=False),
-    sa.Column('adult_consent', sa.Boolean(), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('version', sa.Integer(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_covenants_character_id'), 'covenants', ['character_id'], unique=False)
-    op.create_index(op.f('ix_covenants_owner_scope'), 'covenants', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_covenants_status'), 'covenants', ['status'], unique=False)
-    op.create_table('covenant_events',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('covenant_id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('type', sa.String(length=20), nullable=False),
-    sa.Column('payload_json', sa.Text(), nullable=False),
-    sa.Column('actor', sa.String(length=20), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['covenant_id'], ['covenants.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_covenant_events_character_id'), 'covenant_events', ['character_id'], unique=False)
-    op.create_index(op.f('ix_covenant_events_covenant_id'), 'covenant_events', ['covenant_id'], unique=False)
-    op.create_index(op.f('ix_covenant_events_created_at'), 'covenant_events', ['created_at'], unique=False)
-    op.create_index(op.f('ix_covenant_events_type'), 'covenant_events', ['type'], unique=False)
-
-    # 铸魂
-    op.create_table('soul_forgings',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('proposed_anchor_json', sa.Text(), nullable=False),
-    sa.Column('reason', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('confirmed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_soul_forgings_character_id'), 'soul_forgings', ['character_id'], unique=False)
-    op.create_index(op.f('ix_soul_forgings_status'), 'soul_forgings', ['status'], unique=False)
-
-    # 河图境界
-    op.create_table('persistent_worlds',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('rules_json', sa.Text(), nullable=False),
-    sa.Column('lorebook_id', sa.String(length=80), nullable=True),
-    sa.Column('canon_count', sa.Integer(), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_persistent_worlds_lorebook_id'), 'persistent_worlds', ['lorebook_id'], unique=False)
-    op.create_index(op.f('ix_persistent_worlds_owner_scope'), 'persistent_worlds', ['owner_scope'], unique=False)
-    op.create_table('world_entities',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('world_id', sa.String(length=80), nullable=False),
-    sa.Column('kind', sa.String(length=30), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('attrs_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['world_id'], ['persistent_worlds.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_world_entities_world_id'), 'world_entities', ['world_id'], unique=False)
-    op.create_table('world_relations',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('world_id', sa.String(length=80), nullable=False),
-    sa.Column('source_entity_id', sa.String(length=80), nullable=False),
-    sa.Column('target_entity_id', sa.String(length=80), nullable=False),
-    sa.Column('relation', sa.String(length=80), nullable=False),
-    sa.Column('note', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['source_entity_id'], ['world_entities.id'], ),
-    sa.ForeignKeyConstraint(['target_entity_id'], ['world_entities.id'], ),
-    sa.ForeignKeyConstraint(['world_id'], ['persistent_worlds.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_world_relations_source_entity_id'), 'world_relations', ['source_entity_id'], unique=False)
-    op.create_index(op.f('ix_world_relations_target_entity_id'), 'world_relations', ['target_entity_id'], unique=False)
-    op.create_index(op.f('ix_world_relations_world_id'), 'world_relations', ['world_id'], unique=False)
-
-    # 实录作用域
-    with op.batch_alter_table('factual_records') as batch:
-        batch.add_column(sa.Column('scope', sa.String(length=40), nullable=False, server_default='reality'))
-        batch.create_index('ix_factual_records_scope', ['scope'])
-
-    # 旧人格/驱动/演化域退役（人格基线=道体锚点 identity_baseline_json + 魂籍版本链）
-    with op.batch_alter_table('characters') as batch:
-        batch.drop_column('current_personality_version_id')
-    op.drop_table('personality_versions')
-    op.drop_table('personality_proposals')
-    op.drop_table('curiosity_questions')
-    op.drop_table('exploratory_subgoals')
-    op.drop_table('evolution_candidates')
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    op.drop_table('evolution_candidates')
-    op.drop_table('exploratory_subgoals')
-    op.drop_table('curiosity_questions')
-    op.drop_table('personality_proposals')
-    op.drop_table('personality_versions')
-    with op.batch_alter_table('characters') as batch:
-        batch.add_column(sa.Column('current_personality_version_id', sa.String(length=80), nullable=True))
-    with op.batch_alter_table('factual_records') as batch:
-        batch.drop_index('ix_factual_records_scope')
-        batch.drop_column('scope')
-    op.drop_index(op.f('ix_world_relations_world_id'), table_name='world_relations')
-    op.drop_index(op.f('ix_world_relations_target_entity_id'), table_name='world_relations')
-    op.drop_index(op.f('ix_world_relations_source_entity_id'), table_name='world_relations')
-    op.drop_table('world_relations')
-    op.drop_index(op.f('ix_world_entities_world_id'), table_name='world_entities')
-    op.drop_table('world_entities')
-    op.drop_index(op.f('ix_persistent_worlds_owner_scope'), table_name='persistent_worlds')
-    op.drop_index(op.f('ix_persistent_worlds_lorebook_id'), table_name='persistent_worlds')
-    op.drop_table('persistent_worlds')
-    op.drop_index(op.f('ix_soul_forgings_status'), table_name='soul_forgings')
-    op.drop_index(op.f('ix_soul_forgings_character_id'), table_name='soul_forgings')
-    op.drop_table('soul_forgings')
-    op.drop_index(op.f('ix_covenant_events_type'), table_name='covenant_events')
-    op.drop_index(op.f('ix_covenant_events_created_at'), table_name='covenant_events')
-    op.drop_index(op.f('ix_covenant_events_covenant_id'), table_name='covenant_events')
-    op.drop_index(op.f('ix_covenant_events_character_id'), table_name='covenant_events')
-    op.drop_table('covenant_events')
-    op.drop_index(op.f('ix_covenants_status'), table_name='covenants')
-    op.drop_index(op.f('ix_covenants_owner_scope'), table_name='covenants')
-    op.drop_index(op.f('ix_covenants_character_id'), table_name='covenants')
-    op.drop_table('covenants')

backend/alembic/versions/008_形仪域_真形锚点_主仪化仪定相_声音档案与克隆授权.py

@@ -1,90 +0,0 @@
-"""形仪域_真形锚点_主仪化仪定相_声音档案与克隆授权
-
-Revision ID: 008
-Revises: 007
-Create Date: 2026-08-27 20:15:34.665285
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '008'
-down_revision: Union[str, Sequence[str], None] = '007'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('form_anchors',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('features_json', sa.Text(), nullable=False),
-    sa.Column('age_presentation', sa.String(length=40), nullable=False),
-    sa.Column('permissions_json', sa.Text(), nullable=False),
-    sa.Column('mutable_scope_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('updated_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_form_anchors_character_id'), 'form_anchors', ['character_id'], unique=False)
-    op.create_table('forms',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('kind', sa.String(length=20), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('source', sa.String(length=20), nullable=False),
-    sa.Column('description', sa.Text(), nullable=False),
-    sa.Column('media_ref', sa.String(length=500), nullable=True),
-    sa.Column('live2d_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('adopted_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_forms_character_id'), 'forms', ['character_id'], unique=False)
-    op.create_index(op.f('ix_forms_kind'), 'forms', ['kind'], unique=False)
-    op.create_index(op.f('ix_forms_status'), 'forms', ['status'], unique=False)
-    op.create_table('voice_profiles',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('source', sa.String(length=30), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('params_json', sa.Text(), nullable=False),
-    sa.Column('grant_purpose', sa.String(length=200), nullable=True),
-    sa.Column('grant_expires_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('grant_distribution', sa.String(length=200), nullable=True),
-    sa.Column('grant_revoked_at', sa.DateTime(timezone=True), nullable=True),
-    sa.Column('is_active', sa.Boolean(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_voice_profiles_character_id'), 'voice_profiles', ['character_id'], unique=False)
-    op.create_index(op.f('ix_voice_profiles_is_active'), 'voice_profiles', ['is_active'], unique=False)
-    op.add_column('pending_confirmations', sa.Column('expires_at', sa.DateTime(timezone=True), nullable=True))
-    op.add_column('pending_confirmations', sa.Column('brief_json', sa.Text(), server_default='{}', nullable=False))
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_column('pending_confirmations', 'brief_json')
-    op.drop_column('pending_confirmations', 'expires_at')
-    op.drop_index(op.f('ix_voice_profiles_is_active'), table_name='voice_profiles')
-    op.drop_index(op.f('ix_voice_profiles_character_id'), table_name='voice_profiles')
-    op.drop_table('voice_profiles')
-    op.drop_index(op.f('ix_forms_status'), table_name='forms')
-    op.drop_index(op.f('ix_forms_kind'), table_name='forms')
-    op.drop_index(op.f('ix_forms_character_id'), table_name='forms')
-    op.drop_table('forms')
-    op.drop_index(op.f('ix_form_anchors_character_id'), table_name='form_anchors')
-    op.drop_table('form_anchors')
-    # ### end Alembic commands ###

backend/alembic/versions/009_天工阁_受托任务_叩心候选与约束_退役旧目标计划感知大周天模块.py

@@ -1,87 +0,0 @@
-"""天工阁_受托任务_叩心候选与约束_退役旧目标计划感知大周天模块
-
-Revision ID: 009
-Revises: 008
-Create Date: 2026-08-27 20:31:23.297111
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '009'
-down_revision: Union[str, Sequence[str], None] = '008'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('backstage_tasks',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=True),
-    sa.Column('parent_task_id', sa.String(length=80), nullable=True),
-    sa.Column('title', sa.String(length=200), nullable=False),
-    sa.Column('brief', sa.Text(), nullable=False),
-    sa.Column('acceptance_criteria', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=30), nullable=False),
-    sa.Column('result_digest', sa.Text(), nullable=False),
-    sa.Column('evidence_json', sa.Text(), nullable=False),
-    sa.Column('run_id', sa.String(length=80), nullable=True),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('completed_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['parent_task_id'], ['backstage_tasks.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_backstage_tasks_character_id'), 'backstage_tasks', ['character_id'], unique=False)
-    op.create_index(op.f('ix_backstage_tasks_owner_scope'), 'backstage_tasks', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_backstage_tasks_parent_task_id'), 'backstage_tasks', ['parent_task_id'], unique=False)
-    op.create_index(op.f('ix_backstage_tasks_run_id'), 'backstage_tasks', ['run_id'], unique=False)
-    op.create_index(op.f('ix_backstage_tasks_status'), 'backstage_tasks', ['status'], unique=False)
-    op.create_table('knocking_candidates',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('character_id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('trigger', sa.String(length=20), nullable=False),
-    sa.Column('draft', sa.Text(), nullable=False),
-    sa.Column('channel', sa.String(length=20), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('ruling_json', sa.Text(), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('dispatched_at', sa.DateTime(timezone=True), nullable=True),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_knocking_candidates_character_id'), 'knocking_candidates', ['character_id'], unique=False)
-    op.create_index(op.f('ix_knocking_candidates_owner_scope'), 'knocking_candidates', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_knocking_candidates_status'), 'knocking_candidates', ['status'], unique=False)
-    # ### end Alembic commands ###
-
-    # 旧域退役：太一（goals）/洛书（plans）/天工阁旧 roster/感知/大周天
-    op.drop_table('goals')
-    op.drop_table('plans')
-    op.drop_table('agent_roster')
-    op.drop_table('perception_channels')
-    op.drop_table('big_cycles')
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(op.f('ix_knocking_candidates_status'), table_name='knocking_candidates')
-    op.drop_index(op.f('ix_knocking_candidates_owner_scope'), table_name='knocking_candidates')
-    op.drop_index(op.f('ix_knocking_candidates_character_id'), table_name='knocking_candidates')
-    op.drop_table('knocking_candidates')
-    op.drop_index(op.f('ix_backstage_tasks_status'), table_name='backstage_tasks')
-    op.drop_index(op.f('ix_backstage_tasks_run_id'), table_name='backstage_tasks')
-    op.drop_index(op.f('ix_backstage_tasks_parent_task_id'), table_name='backstage_tasks')
-    op.drop_index(op.f('ix_backstage_tasks_owner_scope'), table_name='backstage_tasks')
-    op.drop_index(op.f('ix_backstage_tasks_character_id'), table_name='backstage_tasks')
-    op.drop_table('backstage_tasks')
-    # ### end Alembic commands ###

backend/alembic/versions/010_器谱_设备配对与逐项授契.py

@@ -1,121 +0,0 @@
-"""器谱_设备配对与逐项授契
-
-Revision ID: 010
-Revises: 009
-Create Date: 2026-08-28 09:25:57.705846
-
-"""
-from typing import Sequence, Union
-
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision: str = '010'
-down_revision: Union[str, Sequence[str], None] = '009'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    """Upgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('device_grants',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('device_id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('capability', sa.String(length=60), nullable=False),
-    sa.Column('scope_json', sa.Text(), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('granted_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('revoked_at', sa.DateTime(timezone=True), nullable=True),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_device_grants_capability'), 'device_grants', ['capability'], unique=False)
-    op.create_index(op.f('ix_device_grants_device_id'), 'device_grants', ['device_id'], unique=False)
-    op.create_index(op.f('ix_device_grants_owner_scope'), 'device_grants', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_device_grants_status'), 'device_grants', ['status'], unique=False)
-    op.create_table('devices',
-    sa.Column('id', sa.String(length=80), nullable=False),
-    sa.Column('owner_scope', sa.String(length=80), nullable=False),
-    sa.Column('kind', sa.String(length=30), nullable=False),
-    sa.Column('name', sa.String(length=120), nullable=False),
-    sa.Column('key_fingerprint', sa.String(length=128), nullable=False),
-    sa.Column('status', sa.String(length=20), nullable=False),
-    sa.Column('created_at', sa.DateTime(timezone=True), nullable=False),
-    sa.Column('last_seen_at', sa.DateTime(timezone=True), nullable=True),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_devices_owner_scope'), 'devices', ['owner_scope'], unique=False)
-    op.create_index(op.f('ix_devices_status'), 'devices', ['status'], unique=False)
-    op.drop_index(op.f('ix_character_profile_candidates_character_id'), table_name='character_profile_candidates')
-    op.drop_index(op.f('ix_character_profile_candidates_import_job_id'), table_name='character_profile_candidates')
-    op.drop_index(op.f('ix_character_profile_candidates_status'), table_name='character_profile_candidates')
-    op.drop_table('character_profile_candidates')
-    op.drop_index(op.f('ix_memory_candidates_character_id'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_cycle_id'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_import_job_id'), table_name='memory_candidates')
-    op.drop_index(op.f('ix_memory_candidates_status'), table_name='memory_candidates')
-    op.drop_table('memory_candidates')
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade schema."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('memory_candidates',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('import_job_id', sa.VARCHAR(length=80), nullable=True),
-    sa.Column('cycle_id', sa.VARCHAR(length=80), nullable=True),
-    sa.Column('type', sa.VARCHAR(length=60), nullable=False),
-    sa.Column('title', sa.VARCHAR(length=200), nullable=False),
-    sa.Column('content', sa.TEXT(), nullable=False),
-    sa.Column('confidence', sa.FLOAT(), nullable=False),
-    sa.Column('importance', sa.FLOAT(), nullable=False),
-    sa.Column('sensitivity', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('evidence_ids_json', sa.TEXT(), nullable=False),
-    sa.Column('status', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('reason', sa.TEXT(), nullable=True),
-    sa.Column('reviewed_at', sa.DATETIME(), nullable=True),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['cycle_id'], ['big_cycles.id'], ),
-    sa.ForeignKeyConstraint(['import_job_id'], ['character_import_jobs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_memory_candidates_status'), 'memory_candidates', ['status'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_import_job_id'), 'memory_candidates', ['import_job_id'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_cycle_id'), 'memory_candidates', ['cycle_id'], unique=False)
-    op.create_index(op.f('ix_memory_candidates_character_id'), 'memory_candidates', ['character_id'], unique=False)
-    op.create_table('character_profile_candidates',
-    sa.Column('id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('character_id', sa.VARCHAR(length=80), nullable=False),
-    sa.Column('import_job_id', sa.VARCHAR(length=80), nullable=True),
-    sa.Column('field', sa.VARCHAR(length=60), nullable=False),
-    sa.Column('value', sa.TEXT(), nullable=False),
-    sa.Column('confidence', sa.FLOAT(), nullable=False),
-    sa.Column('evidence_ids_json', sa.TEXT(), nullable=False),
-    sa.Column('status', sa.VARCHAR(length=40), nullable=False),
-    sa.Column('reason', sa.TEXT(), nullable=True),
-    sa.Column('reviewed_at', sa.DATETIME(), nullable=True),
-    sa.Column('created_at', sa.DATETIME(), nullable=False),
-    sa.Column('updated_at', sa.DATETIME(), nullable=False),
-    sa.ForeignKeyConstraint(['character_id'], ['characters.id'], ),
-    sa.ForeignKeyConstraint(['import_job_id'], ['character_import_jobs.id'], ),
-    sa.PrimaryKeyConstraint('id')
-    )
-    op.create_index(op.f('ix_character_profile_candidates_status'), 'character_profile_candidates', ['status'], unique=False)
-    op.create_index(op.f('ix_character_profile_candidates_import_job_id'), 'character_profile_candidates', ['import_job_id'], unique=False)
-    op.create_index(op.f('ix_character_profile_candidates_character_id'), 'character_profile_candidates', ['character_id'], unique=False)
-    op.drop_index(op.f('ix_devices_status'), table_name='devices')
-    op.drop_index(op.f('ix_devices_owner_scope'), table_name='devices')
-    op.drop_table('devices')
-    op.drop_index(op.f('ix_device_grants_status'), table_name='device_grants')
-    op.drop_index(op.f('ix_device_grants_owner_scope'), table_name='device_grants')
-    op.drop_index(op.f('ix_device_grants_device_id'), table_name='device_grants')
-    op.drop_index(op.f('ix_device_grants_capability'), table_name='device_grants')
-    op.drop_table('device_grants')
-    # ### end Alembic commands ###

backend/app/ai_provider/__init__.py

@@ -0,0 +1,63 @@
+from app.ai_provider.config.loader import load_models_config, load_providers_config
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+
+# 嵌入 / 重排序
+from app.ai_provider.embedding import (
+    EmbeddingProtocol,
+    EmbeddingRequest,
+    EmbeddingResponse,
+    EmbeddingResult,
+    EmbeddingService,
+    EmbeddingServiceError,
+)
+from app.ai_provider.manager import ProviderManager, ProviderManagerFactory
+from app.ai_provider.reranker import (
+    RerankerProtocol,
+    RerankerService,
+    RerankerServiceError,
+    RerankRequest,
+    RerankResponse,
+    RerankResult,
+)
+from app.ai_provider.types.chat import ChatChunk, ChatResult, TokenUsage
+from app.ai_provider.types.errors import AIProviderError
+from app.ai_provider.types.messages import (
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    SystemMessage,
+    ToolMessage,
+)
+
+__all__ = [
+    # LLM
+    "ProviderManager",
+    "ProviderManagerFactory",
+    "BaseMessage",
+    "SystemMessage",
+    "HumanMessage",
+    "AIMessage",
+    "ToolMessage",
+    "ChatChunk",
+    "ChatResult",
+    "TokenUsage",
+    "AIProviderError",
+    "ModelConfig",
+    "ProviderConfig",
+    "load_models_config",
+    "load_providers_config",
+    # Embedding
+    "EmbeddingProtocol",
+    "EmbeddingRequest",
+    "EmbeddingResponse",
+    "EmbeddingResult",
+    "EmbeddingService",
+    "EmbeddingServiceError",
+    # Reranker
+    "RerankerProtocol",
+    "RerankRequest",
+    "RerankResponse",
+    "RerankResult",
+    "RerankerService",
+    "RerankerServiceError",
+]

backend/app/ai_provider/audio/__init__.py

@@ -0,0 +1,197 @@
+"""音频服务 — ASR / TTS 适配器外观。
+
+用法::
+
+    from app.ai_provider.audio import AudioService
+
+    service = AudioService(factory)
+    result = await service.transcribe(audio_bytes, format="wav")
+    result = await service.synthesize("你好，魂镜", voice="default")
+
+``AudioService`` 通过注册表中带有 ``asr`` / ``tts`` 能力标签的模型来解析
+使用哪个模型，然后将创建委托给 ``ModelFactory.create_audio()``。
+"""
+
+from __future__ import annotations
+
+from app.ai_provider.audio.base import (
+    ASRProtocol,
+    ASRRequest,
+    ASRResponse,
+    AudioServiceError,
+    TTSProtocol,
+    TTSRequest,
+    TTSResponse,
+)
+
+
+class AudioService:
+    """外观类，负责解析 ASR / TTS 模型并委托给 ProviderManager。
+
+    接受 ProviderManager 或实现了以下接口的适配器：
+    - ``.registry`` → 具有 ``list_capability_models(capability: str)`` 方法
+    - ``.create_audio(name: str)`` → 返回 ASRProtocol / TTSProtocol 实例
+    """
+
+    def __init__(self, manager) -> None:
+        self._manager = manager
+        self._asr_adapter: ASRProtocol | None = None
+        self._tts_adapter: TTSProtocol | None = None
+
+    # ── Registry 兼容适配 ─────────────────────────────────────────
+
+    @property
+    def _registry(self):
+        """按需获取 registry，兼容 adapter 和裸 ProviderManager/ModelRegistry。"""
+        mgr = self._manager
+        if hasattr(mgr, "registry"):
+            return mgr.registry
+        if hasattr(mgr, "model_registry"):
+            return mgr.model_registry
+        return mgr
+
+    def _list_capability_models(self, tag: str):
+        reg = self._registry
+        # 适配器接口（list_capability_models）vs  ModelRegistry 接口（list_by_capability）
+        if hasattr(reg, "list_capability_models"):
+            return reg.list_capability_models(tag)
+        if hasattr(reg, "list_by_capability"):
+            return reg.list_by_capability(tag)
+        return []
+
+    @property
+    def _factory(self):
+        mgr = self._manager
+        if hasattr(mgr, "create_audio"):
+            return mgr
+        return None
+
+    # ── ASR ──────────────────────────────────────────────────────────────
+
+    @property
+    def asr(self) -> ASRProtocol:
+        """解析并缓存 ASR 适配器（取注册表中第一个活跃 ASR 模型）。"""
+        if self._asr_adapter is None:
+            self._asr_adapter = self._resolve_asr()
+        return self._asr_adapter
+
+    def asr_for(self, model_name: str) -> ASRProtocol:
+        """解析并缓存指定模型名的 ASR 适配器（覆盖默认第一个）。"""
+        self._asr_adapter = self._factory.create_audio(model_name)
+        return self._asr_adapter
+
+    async def transcribe(
+        self,
+        audio_data: bytes,
+        format: str = "wav",
+        language: str | None = None,
+        model_name: str | None = None,
+    ) -> ASRResponse:
+        """快捷方法：构造请求并调用 ASR 适配器。
+
+        Args:
+            model_name: 可选，指定使用哪个 ASR 模型（按注册表逻辑名）。
+                省略时取注册表中第一个活跃的 ASR 模型。
+        """
+        if model_name is not None:
+            adapter = self.asr_for(model_name)
+        else:
+            adapter = self.asr
+        request = ASRRequest(
+            audio_data=audio_data,
+            format=format,
+            language=language,
+        )
+        return await adapter.transcribe(request)
+
+    # ── TTS ──────────────────────────────────────────────────────────────
+
+    @property
+    def tts(self) -> TTSProtocol:
+        """解析并缓存 TTS 适配器。"""
+        if self._tts_adapter is None:
+            self._tts_adapter = self._resolve_tts()
+        return self._tts_adapter
+
+    async def synthesize(
+        self,
+        text: str,
+        voice: str = "default",
+        response_format: str = "wav",
+        extra: dict | None = None,
+    ) -> TTSResponse:
+        """快捷方法：构造请求并调用 TTS 适配器。"""
+        request = TTSRequest(
+            text=text,
+            voice=voice,
+            response_format=response_format,
+            extra=extra,
+        )
+        return await self.tts.synthesize(request)
+
+    # ── 解析 ───────────────────────────────────────────────────────
+
+    def _resolve_asr(self) -> ASRProtocol:
+        """查找第一个活跃的 ASR 模型并通过工厂创建。"""
+        models = self._list_capability_models("asr")
+        if not models:
+            raise AudioServiceError(
+                status_code=503,
+                code="audio_asr_no_model",
+                message="No ASR model configured in the model registry.",
+            )
+        factory = self._factory
+        if factory is None:
+            raise AudioServiceError(
+                status_code=501,
+                code="audio_asr_no_factory",
+                message="Audio adapter factory not available (provider manager missing create_audio).",
+            )
+        return factory.create_audio(models[0].name)
+
+    def _resolve_tts(self) -> TTSProtocol:
+        """查找第一个活跃的 TTS 模型并通过工厂创建。"""
+        models = self._list_capability_models("tts")
+        if not models:
+            raise AudioServiceError(
+                status_code=503,
+                code="audio_tts_no_model",
+                message="No TTS model configured in the model registry.",
+            )
+        factory = self._factory
+        if factory is None:
+            raise AudioServiceError(
+                status_code=501,
+                code="audio_tts_no_factory",
+                message="Audio adapter factory not available (provider manager missing create_audio).",
+            )
+        return factory.create_audio(models[0].name)
+
+    # ── 生命周期 ────────────────────────────────────────────────────────
+
+    async def close(self) -> None:
+        """释放适配器持有的 HTTP 连接。"""
+        for adapter in (self._asr_adapter, self._tts_adapter):
+            if adapter is None:
+                continue
+            close = getattr(adapter, "close", None)
+            if close is not None:
+                await close()
+
+    async def __aenter__(self) -> AudioService:
+        return self
+
+    async def __aexit__(self, *exc_info: object) -> None:
+        await self.close()
+
+
+__all__ = [
+    "ASRProtocol",
+    "ASRRequest",
+    "ASRResponse",
+    "AudioService",
+    "AudioServiceError",
+    "TTSProtocol",
+    "TTSRequest",
+    "TTSResponse",
+]

backend/app/ai_provider/audio/asr.py

@@ -0,0 +1,263 @@
+"""MiMo ASR adapter — ``POST /v1/chat/completions`` with ``input_audio``.
+
+MiMo 的 ASR 不走独立音频端点，而是通过聊天补全接口扩展实现：
+
+    POST {base_url}/chat/completions
+    Content-Type: application/json
+    Authorization: Bearer {api_key}
+
+    {
+        "model": "mimo-v2.5-asr",
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "input_audio",
+                        "input_audio": {
+                            "data": "data:audio/wav;base64,<base64_encoded_audio>"
+                        }
+                    }
+                ]
+            }
+        ],
+        "asr_options": {
+            "language": "auto"
+        }
+    }
+
+响应：:
+
+    {
+      "choices": [{
+        "message": {
+          "content": "转写后的文本"
+        }
+      }]
+    }
+"""
+
+from __future__ import annotations
+
+import base64
+import hashlib
+import time
+
+import httpx
+
+from app.ai_provider.audio.base import (
+    ASRProtocol,
+    ASRRequest,
+    ASRResponse,
+    AudioAdapterBase,
+    AudioServiceError,
+)
+from app.core.logging import logger
+
+_MIME_MAP = {
+    "wav": "audio/wav",
+    "mp3": "audio/mpeg",
+    "m4a": "audio/mp4",
+    "flac": "audio/flac",
+}
+
+# ASR 缓存：默认最多 128 条，TTL 1 小时
+_ASR_CACHE_MAX_SIZE = 128
+_ASR_CACHE_TTL_SECONDS = 3600
+
+
+class _ASRCacheEntry:
+    __slots__ = ("text", "stored_at")
+
+    def __init__(self, text: str) -> None:
+        self.text = text
+        self.stored_at = time.monotonic()
+
+
+_asr_cache: dict[str, _ASRCacheEntry] = {}
+
+
+def _asr_cache_key(model: str, audio_data: bytes, language: str, fmt: str) -> str:
+    """生成 ASR 缓存键：SHA256(model + audio_bytes + language + format)。"""
+    raw = f"{model}\0{language}\0{fmt}\0"
+    raw_bytes = raw.encode() + audio_data
+    return hashlib.sha256(raw_bytes).hexdigest()
+
+
+def _asr_cache_get(key: str) -> str | None:
+    entry = _asr_cache.get(key)
+    if entry is None:
+        return None
+    if time.monotonic() - entry.stored_at > _ASR_CACHE_TTL_SECONDS:
+        del _asr_cache[key]
+        return None
+    return entry.text
+
+
+def _asr_cache_set(key: str, text: str) -> None:
+    if len(_asr_cache) >= _ASR_CACHE_MAX_SIZE:
+        sorted_keys = sorted(_asr_cache.keys(), key=lambda k: _asr_cache[k].stored_at)
+        for old_key in sorted_keys[: _ASR_CACHE_MAX_SIZE // 2]:
+            del _asr_cache[old_key]
+    _asr_cache[key] = _ASRCacheEntry(text)
+
+
+class HunjingASROpenAI(AudioAdapterBase, ASRProtocol):
+    """MiMo ASR 适配器，通过 ``POST /chat/completions`` 携带 ``input_audio`` 实现。
+
+    将音频字节包装为 chat 消息中的 ``input_audio`` 内容类型的 data URL，
+    然后从响应中提取转写文本。
+    """
+
+    _adapter_type = "asr"
+    _default_timeout = 300
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str = "mimo-v2.5-asr",
+        request_timeout_seconds: int = 300,
+    ) -> None:
+        self._base_url = base_url.rstrip("/")
+        self._api_key = api_key
+        self._model = model
+        self._timeout = request_timeout_seconds
+        self._client: httpx.AsyncClient | None = None
+
+    # ── 客户端 ───────────────────────────────────────────────────────────
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None or self._client.is_closed:
+            self._client = httpx.AsyncClient(timeout=httpx.Timeout(self._timeout))
+        return self._client
+
+    async def close(self) -> None:
+        if self._client is not None and not self._client.is_closed:
+            await self._client.aclose()
+
+    # ── ASRProtocol ──────────────────────────────────────────────────────
+
+    async def transcribe(self, request: ASRRequest) -> ASRResponse:
+        """通过 ``POST /chat/completions`` 转写音频。
+
+        将音频编码为 data URL 并以 ``input_audio`` 内容块的形式发送到 chat 消息中。
+        """
+        # ── 缓存查找 ──────────────────────────────────────────────────
+        cache_key = _asr_cache_key(
+            self._model, request.audio_data, request.language or "auto", request.format
+        )
+        cached = _asr_cache_get(cache_key)
+        if cached is not None:
+            logger.info("audio_asr.cache_hit", model=self._model, text_length=len(cached))
+            return ASRResponse(text=cached)
+
+        # ── 构造请求 ──────────────────────────────────────────────────
+        mime = _MIME_MAP.get(request.format, "audio/wav")
+        b64_audio = base64.b64encode(request.audio_data).decode()
+        data_url = f"data:{mime};base64,{b64_audio}"
+
+        payload: dict = {
+            "model": self._model,
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "input_audio",
+                            "input_audio": {
+                                "data": data_url,
+                            },
+                        },
+                    ],
+                },
+            ],
+            "asr_options": {
+                "language": request.language or "auto",
+            },
+        }
+
+        headers = {
+            "Authorization": f"Bearer {self._api_key}",
+            "Content-Type": "application/json",
+        }
+
+        url = f"{self._base_url}/chat/completions"
+
+        logger.info(
+            "audio_asr.request",
+            model=self._model,
+            format=request.format,
+            language=request.language,
+            url=url,
+            size_bytes=len(request.audio_data),
+        )
+
+        # ── API 调用 ────────────────────────────────────────────────
+        try:
+            response = await self._http.post(url, json=payload, headers=headers)
+        except httpx.TimeoutException as exc:
+            raise AudioServiceError(
+                status_code=504,
+                code="audio_asr_timeout",
+                message="ASR request timed out calling chat completions.",
+            ) from exc
+        except httpx.RequestError as exc:
+            raise AudioServiceError(
+                status_code=503,
+                code="audio_asr_connection_error",
+                message=f"ASR connection error: {exc}",
+            ) from exc
+
+        if response.status_code != 200:
+            body = response.text[:500]
+            raise AudioServiceError(
+                status_code=response.status_code,
+                code="audio_asr_api_error",
+                message=f"ASR API returned {response.status_code}: {body}",
+            )
+
+        # 解析响应，提取转写文本
+        text = self._extract_text(response.json())
+        if not text:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_asr_empty_response",
+                message="ASR API returned empty transcription.",
+            )
+
+        # ── 写入缓存 ────────────────────────────────────────────────
+        _asr_cache_set(cache_key, text)
+
+        logger.info(
+            "audio_asr.success",
+            model=self._model,
+            text_length=len(text),
+            cache_size=len(_asr_cache),
+        )
+        return ASRResponse(text=text)
+
+    # ── 辅助方法 ──────────────────────────────────────────────────────────
+
+    @staticmethod
+    def _extract_text(body: dict) -> str:
+        """从 chat completion 响应中提取转写文本。"""
+        try:
+            choices = body.get("choices", [])
+            if not choices:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_asr_no_choices",
+                    message="ASR response has no choices.",
+                )
+            return (choices[0].get("message") or {}).get("content") or ""
+        except AudioServiceError:
+            raise
+        except Exception as exc:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_asr_response_parse_error",
+                message=f"Failed to parse ASR response: {exc}",
+            ) from exc

backend/app/ai_provider/audio/base.py

@@ -0,0 +1,245 @@
+"""音频服务类型 — 请求/响应模型和协议定义。
+
+ASR（自动语音识别）和 TTS（文本转语音）适配器**不是** LangChain 的
+``BaseChatModel`` 子类 —— 它们是通过 HTTP 调用的服务，经由 ``AudioService``
+或直接从 ``ModelFactory`` 消费。
+
+用法::
+
+    service = AudioService(factory)
+    result = await service.transcribe(audio_data)
+    result = await service.synthesize("你好")
+
+    # 或通过工厂直接调用:
+    tts = factory.create_audio("mimo-v2.5-tts")
+    result = await tts.synthesize(TTSRequest(text="你好"))
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Protocol, runtime_checkable
+
+from app.ai_provider.types.errors import AIProviderError
+
+if TYPE_CHECKING:
+    from app.ai_provider.config.models import ModelConfig, ModelEndpointConfig
+
+
+class AudioServiceError(AIProviderError):
+    """ASR / TTS 服务失败的基础错误。"""
+
+
+# ── ASR ───────────────────────────────────────────────────────────────────
+
+
+class ASRRequest:
+    """将音频转写为文本的请求。
+
+    属性:
+        audio_data: 原始音频字节。
+        format: 音频容器格式（如 ``"wav"``、``"mp3"``、``"m4a"``）。
+        language: 可选的 ISO-639-1 语言提示（如 ``"zh"``、``"en"``）。
+    """
+
+    __slots__ = ("audio_data", "format", "language")
+
+    def __init__(
+        self,
+        audio_data: bytes,
+        format: str = "wav",
+        language: str | None = None,
+    ) -> None:
+        self.audio_data = audio_data
+        self.format = format
+        self.language = language
+
+
+@dataclass(frozen=True)
+class ASRResponse:
+    """成功转写的结果。"""
+
+    text: str
+
+
+@runtime_checkable
+class ASRProtocol(Protocol):
+    """ASR 适配器的协议。"""
+
+    async def transcribe(self, request: ASRRequest) -> ASRResponse:
+        """将音频字节转写为文本。
+
+        异常:
+            AudioServiceError: API 调用失败或响应异常时抛出。
+        """
+        ...
+
+
+# ── TTS ───────────────────────────────────────────────────────────────────
+
+
+class TTSRequest:
+    """将文本合成为语音的请求。
+
+    属性:
+        text: 待朗读的文本。
+        voice: 音色标识符（模型决定可用音色）。
+        response_format: 期望的音频格式（``"wav"``、``"mp3"``、``"opus"``）。
+        extra: 厂商特定的额外参数（如音色克隆/设计参数）。
+    """
+
+    __slots__ = ("text", "voice", "response_format", "extra")
+
+    def __init__(
+        self,
+        text: str,
+        voice: str = "default",
+        response_format: str = "wav",
+        extra: dict | None = None,
+    ) -> None:
+        self.text = text
+        self.voice = voice
+        self.response_format = response_format
+        self.extra = extra or {}
+
+
+@dataclass(frozen=True)
+class TTSResponse:
+    """成功合成的结果。"""
+
+    audio_data: bytes
+    format: str
+
+
+@runtime_checkable
+class TTSProtocol(Protocol):
+    """TTS 适配器的协议。"""
+
+    async def synthesize(self, request: TTSRequest) -> TTSResponse:
+        """将文本合成为音频字节。
+
+        异常:
+            AudioServiceError: API 调用失败或响应异常时抛出。
+        """
+        ...
+
+
+# ── 共享工厂基类 ──────────────────────────────────────────────────────────
+
+
+class AudioAdapterBase:
+    """ASR/TTS 适配器的基类，提供共享的工厂方法。
+
+    子类必须设置 ``_adapter_type``（如 ``"asr"``、``"tts"``），并在
+    ``__init__`` 中接受 ``base_url``、``api_key``、``model``、
+    ``request_timeout_seconds`` 参数。
+    """
+
+    _adapter_type: str = "audio"
+    _default_timeout: int = 120
+
+    @classmethod
+    def from_endpoint(
+        cls,
+        endpoint: ModelEndpointConfig,
+        *,
+        provider: ProviderConfig | None = None,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从已解析的端点配置构建适配器。
+
+        凭证解析优先级：
+        1. endpoint 直填的 ``base_url`` / ``api_key``
+        2. endpoint 的 ``base_url_env`` / ``api_key_env`` 指向的 settings 字段
+        3. provider 级凭证（调用方按需传入 ProviderConfig）
+        """
+        base_url = _resolve_base_url(endpoint, provider)
+        api_key = _resolve_api_key(endpoint, provider)
+        if not base_url:
+            raise AudioServiceError(
+                status_code=500,
+                code=f"audio_{cls._adapter_type}_endpoint_invalid",
+                message=(
+                    f"{cls._adapter_type.upper()} endpoint '{endpoint.name}' "
+                    "has no resolved base_url."
+                ),
+            )
+        return cls(
+            base_url=base_url,
+            api_key=api_key,
+            model=endpoint.model,
+            request_timeout_seconds=timeout_seconds
+            or endpoint.request_timeout_seconds
+            or cls._default_timeout,
+        )
+
+    @classmethod
+    def from_model_config(
+        cls,
+        config: ModelConfig,
+        *,
+        provider: ProviderConfig | None = None,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从逻辑模型配置构建适配器（使用第一个活跃端点）。"""
+        for ep in config.endpoints:
+            if ep.status == "active":
+                return cls.from_endpoint(
+                    ep, provider=provider, timeout_seconds=timeout_seconds
+                )
+        raise AudioServiceError(
+            status_code=500,
+            code=f"audio_{cls._adapter_type}_no_endpoint",
+            message=f"{cls._adapter_type.upper()} model '{config.name}' has no active endpoint.",
+        )
+
+
+def _resolve_base_url(
+    endpoint: ModelEndpointConfig,
+    provider: ProviderConfig | None,
+) -> str:
+    """端点 base_url → endpoint.base_url_env 对应 settings → provider.base_url(_env)。"""
+    if endpoint.base_url:
+        return endpoint.base_url
+    if endpoint.base_url_env:
+        val = _settings_get(endpoint.base_url_env)
+        if val:
+            return val
+    if provider is not None:
+        if provider.base_url:
+            return provider.base_url
+        if provider.base_url_env:
+            val = _settings_get(provider.base_url_env)
+            if val:
+                return val
+    return ""
+
+
+def _resolve_api_key(
+    endpoint: ModelEndpointConfig,
+    provider: ProviderConfig | None,
+) -> str:
+    """端点 api_key → endpoint.api_key_env 对应 settings → provider 级凭证。"""
+    if endpoint.api_key:
+        return endpoint.api_key
+    if endpoint.api_key_env:
+        val = _settings_get(endpoint.api_key_env)
+        if val:
+            return val
+    if provider is not None:
+        # ProviderConfig 的 api_key_env / base_url_env 也走 settings 解析
+        val = _settings_get(provider.api_key_env)
+        if val:
+            return val
+    return ""
+
+
+def _settings_get(env_name: str) -> str | None:
+    """按大写 env 名查 settings 上的小写字段（与现有 _resolve_credentials 约定一致）。"""
+    from app.core.config import settings
+
+    key = env_name.lower()
+    if hasattr(settings, key):
+        value = getattr(settings, key)
+        return value if isinstance(value, str) else None
+    return None

backend/app/ai_provider/audio/tts.py

@@ -0,0 +1,325 @@
+"""MiMo TTS adapter — ``POST /v1/chat/completions`` with ``audio`` parameter.
+
+MiMo 的 TTS 不走独立音频端点，而是通过聊天补全接口扩展实现：
+
+    POST {base_url}/chat/completions
+    Content-Type: application/json
+    Authorization: Bearer {api_key}
+
+    {
+        "model": "mimo-v2.5-tts",
+        "messages": [
+            {"role": "user", "content": "（可选）音色风格描述，voicedesign 必填"},
+            {"role": "assistant", "content": "要朗读的文本"}
+        ],
+        "audio": {
+            "format": "wav",
+            "voice": "mimo_default"
+        }
+    }
+
+响应：:
+
+    {
+      "choices": [{
+        "message": {
+          "audio": {
+            "data": "<base64 编码的音频数据>",
+            "id": "...",
+            "expires_at": null,
+            "transcript": null
+          }
+        }
+      }]
+    }
+
+模型差异：
+
+- ``mimo-v2.5-tts`` — ``voice`` 可选，默认 ``mimo_default``，仅支持预置音色
+- ``mimo-v2.5-tts-voiceclone`` — ``voice`` 必填，传入音频样本的 base64（mp3/wav）
+- ``mimo-v2.5-tts-voicedesign`` — 不支持 ``voice``，\n  ``user`` 消息必填（风格描述），支持 ``optimize_text_preview``
+"""
+
+from __future__ import annotations
+
+import base64
+import hashlib
+import time
+
+import httpx
+
+from app.ai_provider.audio.base import (
+    AudioAdapterBase,
+    AudioServiceError,
+    TTSProtocol,
+    TTSRequest,
+    TTSResponse,
+)
+from app.core.logging import logger
+
+# voicedesign 模型的默认风格描述（用户未提供时使用）
+_DEFAULT_VOICE_DESIGN_PROMPT = "自然、清晰的朗读风格，语气平和，语速适中，适合日常对话场景。"
+
+# TTS 音频缓存：默认最多 256 条，TTL 1 小时
+_TTS_CACHE_MAX_SIZE = 256
+_TTS_CACHE_TTL_SECONDS = 3600
+
+
+class _TTSCacheEntry:
+    __slots__ = ("data", "format", "stored_at")
+
+    def __init__(self, data: bytes, format: str) -> None:
+        self.data = data
+        self.format = format
+        self.stored_at = time.monotonic()
+
+
+_tts_cache: dict[str, _TTSCacheEntry] = {}
+
+
+def _tts_cache_key(model: str, voice: str, fmt: str, text: str, extra_json: str) -> str:
+    """生成 TTS 缓存键：SHA256(model + voice + format + text + extra)。"""
+    raw = f"{model}\0{voice}\0{fmt}\0{text}\0{extra_json}"
+    return hashlib.sha256(raw.encode()).hexdigest()
+
+
+def _tts_cache_get(key: str) -> _TTSCacheEntry | None:
+    entry = _tts_cache.get(key)
+    if entry is None:
+        return None
+    if time.monotonic() - entry.stored_at > _TTS_CACHE_TTL_SECONDS:
+        del _tts_cache[key]
+        return None
+    return entry
+
+
+def _tts_cache_set(key: str, entry: _TTSCacheEntry) -> None:
+    if len(_tts_cache) >= _TTS_CACHE_MAX_SIZE:
+        # 淘汰最旧的一半
+        sorted_keys = sorted(_tts_cache.keys(), key=lambda k: _tts_cache[k].stored_at)
+        for old_key in sorted_keys[: _TTS_CACHE_MAX_SIZE // 2]:
+            del _tts_cache[old_key]
+    _tts_cache[key] = entry
+
+
+class HunjingTTSOpenAI(AudioAdapterBase, TTSProtocol):
+    """MiMo TTS 适配器，通过 ``POST /chat/completions`` 携带 ``audio`` 参数实现。
+
+    调用兼容 OpenAI 格式的 chat completions 端点，在请求体中添加 ``audio`` 字段，
+    然后从响应中提取并解码 base64 音频数据。
+    """
+
+    _adapter_type = "tts"
+    _default_timeout = 120
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str = "mimo-v2.5-tts",
+        request_timeout_seconds: int = 120,
+    ) -> None:
+        self._base_url = base_url.rstrip("/")
+        self._api_key = api_key
+        self._model = model
+        self._timeout = request_timeout_seconds
+        self._client: httpx.AsyncClient | None = None
+
+    # ── 客户端 ───────────────────────────────────────────────────────────
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None or self._client.is_closed:
+            self._client = httpx.AsyncClient(timeout=httpx.Timeout(self._timeout))
+        return self._client
+
+    async def close(self) -> None:
+        if self._client is not None and not self._client.is_closed:
+            await self._client.aclose()
+
+    # ── TTSProtocol ──────────────────────────────────────────────────────
+
+    async def synthesize(self, request: TTSRequest) -> TTSResponse:
+        """通过 ``POST /chat/completions`` 将文本合成为音频。
+
+        构造 chat 消息和 ``audio`` 参数，匹配 MiMo 兼容 OpenAI 格式的 TTS，
+        然后从响应中解码 base64 音频。
+
+        结果按 ``(model, voice, format, text)`` 在进程内缓存，避免重复 API 调用。
+        """
+        # ── 缓存查找 ──────────────────────────────────────────────────────
+        cache_key = _tts_cache_key(
+            model=self._model,
+            voice=request.voice,
+            fmt=request.response_format,
+            text=request.text,
+            extra_json=str(sorted((request.extra or {}).items())),
+        )
+        cached = _tts_cache_get(cache_key)
+        if cached is not None:
+            logger.info("audio_tts.cache_hit", model=self._model, text_length=len(request.text))
+            return TTSResponse(audio_data=cached.data, format=cached.format)
+
+        # ── API 调用 ──────────────────────────────────────────────────────
+        url = f"{self._base_url}/chat/completions"
+
+        # 构造 messages
+        messages = self._build_messages(request)
+
+        # 构造 audio 参数
+        audio_params = self._build_audio_params(request)
+
+        payload: dict = {
+            "model": self._model,
+            "messages": messages,
+            "audio": audio_params,
+            "max_completion_tokens": 8192,
+        }
+        # 合并 extra（如 frequency_penalty, temperature 等）
+        if request.extra:
+            payload.update(request.extra)
+
+        headers = {
+            "Authorization": f"Bearer {self._api_key}",
+            "Content-Type": "application/json",
+        }
+
+        logger.info(
+            "audio_tts.request",
+            model=self._model,
+            voice=request.voice,
+            audio_format=request.response_format,
+            text_length=len(request.text),
+            url=url,
+        )
+
+        try:
+            response = await self._http.post(url, json=payload, headers=headers)
+        except httpx.TimeoutException as exc:
+            raise AudioServiceError(
+                status_code=504,
+                code="audio_tts_timeout",
+                message="TTS request timed out calling chat completions.",
+            ) from exc
+        except httpx.RequestError as exc:
+            raise AudioServiceError(
+                status_code=503,
+                code="audio_tts_connection_error",
+                message=f"TTS connection error: {exc}",
+            ) from exc
+
+        if response.status_code != 200:
+            body = response.text[:500]
+            raise AudioServiceError(
+                status_code=response.status_code,
+                code="audio_tts_api_error",
+                message=f"TTS API returned {response.status_code}: {body}",
+            )
+
+        # 解析响应，提取 base64 音频
+        audio_data = self._extract_audio(response.json())
+
+        # ── 写入缓存 ──────────────────────────────────────────────────────
+        _tts_cache_set(cache_key, _TTSCacheEntry(audio_data, request.response_format))
+
+        logger.info(
+            "audio_tts.success",
+            model=self._model,
+            audio_bytes=len(audio_data),
+            cache_size=len(_tts_cache),
+        )
+        return TTSResponse(audio_data=audio_data, format=request.response_format)
+
+    # ── 辅助方法 ──────────────────────────────────────────────────────────
+
+    def _build_messages(self, request: TTSRequest) -> list[dict]:
+        """构造 chat messages 数组。
+
+        - voicedesign 模型：user 消息必填（风格描述）
+        - 其他模型：user 消息可选，assistant 消息存放待朗读文本
+        """
+        is_voicedesign = "voicedesign" in self._model
+
+        if is_voicedesign:
+            # voicedesign：user 消息为风格提示，assistant 消息为朗读文本
+            style_prompt = (request.extra or {}).pop("style_prompt", _DEFAULT_VOICE_DESIGN_PROMPT)
+            return [
+                {"role": "user", "content": style_prompt},
+                {"role": "assistant", "content": request.text},
+            ]
+        # 基础 TTS / voiceclone：只传 assistant 消息
+        return [
+            {"role": "assistant", "content": request.text},
+        ]
+
+    def _build_audio_params(self, request: TTSRequest) -> dict:
+        """构造 ``audio`` 参数字段，按模型处理 voice/format/optimize_text_preview 等。"""
+        params: dict = {
+            "format": _resolve_api_format(request.response_format),
+        }
+
+        is_voicedesign = "voicedesign" in self._model
+
+        if is_voicedesign:
+            # voicedesign 不支持 voice 字段
+            optimize = (request.extra or {}).pop("optimize_text_preview", None)
+            if optimize is not None:
+                params["optimize_text_preview"] = optimize
+        else:
+            # 基础 TTS / voiceclone：按需传 voice
+            if request.voice and request.voice != "default":
+                params["voice"] = request.voice
+            else:
+                params["voice"] = "mimo_default"
+
+        return params
+
+    @staticmethod
+    def _extract_audio(body: dict) -> bytes:
+        """从 chat completion 响应中提取并解码 base64 音频数据。"""
+        try:
+            choices = body.get("choices", [])
+            if not choices:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_tts_no_choices",
+                    message="TTS response has no choices.",
+                )
+            message = choices[0].get("message", {})
+            audio_info = message.get("audio")
+            if not audio_info:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_tts_no_audio_field",
+                    message="TTS response missing audio field in message.",
+                )
+            raw = audio_info.get("data")
+            if not raw:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_tts_empty_audio_data",
+                    message="TTS response has empty audio.data.",
+                )
+            return base64.b64decode(raw)
+        except AudioServiceError:
+            raise
+        except Exception as exc:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_tts_response_parse_error",
+                message=f"Failed to parse TTS response: {exc}",
+            ) from exc
+
+
+def _resolve_api_format(user_format: str) -> str:
+    """将用户层面的格式名映射为 API 期望的格式。
+
+    MiMo TTS API 接受：``wav``、``mp3``、``pcm``、``pcm16``。
+    """
+    fmt = user_format.lower()
+    if fmt in ("pcm", "pcm16"):
+        return "pcm16"
+    if fmt in ("wav", "mp3"):
+        return fmt
+    return "wav"

backend/app/ai_provider/audio/yuanqi_asr.py

@@ -0,0 +1,231 @@
+"""yuanqi 本地 ASR 适配器 — ``POST /v1/audio/transcriptions`` (multipart)。
+
+与 MiMo 走 ``/chat/completions`` + ``input_audio`` 不同，元炁本地推理引擎
+（yuanqi）对外暴露的是 OpenAI Whisper 兼容的 multipart 端点::
+
+    POST {base_url}/v1/audio/transcriptions
+    Content-Type: multipart/form-data
+    Authorization: Bearer {api_key}
+
+    file: <audio bytes>
+    language: zh  (可选)
+
+响应::
+
+    {"text": "转写后的文本"}
+
+模型实际为 FunASR SenseVoiceSmall，转写文本已在 yuanqi 侧剥离了
+``<|zh|><|NEUTRAL|><|Speech|><|withitn|>`` 等内部标签，此处无需二次清洗。
+"""
+
+from __future__ import annotations
+
+import hashlib
+import time
+
+import httpx
+
+from app.ai_provider.audio.base import (
+    ASRProtocol,
+    ASRRequest,
+    ASRResponse,
+    AudioAdapterBase,
+    AudioServiceError,
+)
+from app.core.logging import logger
+
+# multipart 使用的 MIME 映射（与 yuanqi _SUPPORTED_FORMATS 白名单对齐）
+_MIME_MAP = {
+    "wav": "audio/wav",
+    "mp3": "audio/mpeg",
+    "m4a": "audio/mp4",
+    "flac": "audio/flac",
+    "ogg": "audio/ogg",
+    "opus": "audio/opus",
+    "aac": "audio/aac",
+    "webm": "audio/webm",
+}
+
+# yuanqi ASR 路径前缀（与 src/endpoints/asr.py 的 router 前缀一致）
+_ASR_PATH = "/v1/audio/transcriptions"
+
+# ASR 缓存：默认最多 128 条，TTL 1 小时（与 MiMo ASR 适配器一致）
+_ASR_CACHE_MAX_SIZE = 128
+_ASR_CACHE_TTL_SECONDS = 3600
+
+
+class _ASRCacheEntry:
+    __slots__ = ("text", "stored_at")
+
+    def __init__(self, text: str) -> None:
+        self.text = text
+        self.stored_at = time.monotonic()
+
+
+_asr_cache: dict[str, _ASRCacheEntry] = {}
+
+
+def _asr_cache_key(model: str, audio_data: bytes, language: str, fmt: str) -> str:
+    """生成 ASR 缓存键：SHA256(model + audio_bytes + language + format)。"""
+    raw = f"{model}\0{language}\0{fmt}\0"
+    raw_bytes = raw.encode() + audio_data
+    return hashlib.sha256(raw_bytes).hexdigest()
+
+
+def _asr_cache_get(key: str) -> str | None:
+    entry = _asr_cache.get(key)
+    if entry is None:
+        return None
+    if time.monotonic() - entry.stored_at > _ASR_CACHE_TTL_SECONDS:
+        del _asr_cache[key]
+        return None
+    return entry.text
+
+
+def _asr_cache_set(key: str, text: str) -> None:
+    if len(_asr_cache) >= _ASR_CACHE_MAX_SIZE:
+        sorted_keys = sorted(_asr_cache.keys(), key=lambda k: _asr_cache[k].stored_at)
+        for old_key in sorted_keys[: _ASR_CACHE_MAX_SIZE // 2]:
+            del _asr_cache[old_key]
+    _asr_cache[key] = _ASRCacheEntry(text)
+
+
+class YuanqiASRWhisper(AudioAdapterBase, ASRProtocol):
+    """yuanqi 本地 ASR 适配器，走 OpenAI Whisper 兼容的 multipart 端点。
+
+    将音频字节以 ``multipart/form-data`` 的 ``file`` 字段上传到 yuanqi 的
+    ``/v1/audio/transcriptions``，从 JSON 响应中提取转写文本。
+    """
+
+    _adapter_type = "asr"
+    _default_timeout = 300
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str = "SenseVoiceSmall",
+        request_timeout_seconds: int = 300,
+    ) -> None:
+        self._base_url = base_url.rstrip("/")
+        self._api_key = api_key
+        self._model = model
+        self._timeout = request_timeout_seconds
+        self._client: httpx.AsyncClient | None = None
+
+    # ── 客户端 ───────────────────────────────────────────────────────────
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None or self._client.is_closed:
+            self._client = httpx.AsyncClient(timeout=httpx.Timeout(self._timeout))
+        return self._client
+
+    async def close(self) -> None:
+        if self._client is not None and not self._client.is_closed:
+            await self._client.aclose()
+
+    # ── ASRProtocol ──────────────────────────────────────────────────────
+
+    async def transcribe(self, request: ASRRequest) -> ASRResponse:
+        """通过 ``POST /v1/audio/transcriptions`` 转写音频。"""
+        # ── 缓存查找 ──────────────────────────────────────────────────
+        cache_key = _asr_cache_key(
+            self._model, request.audio_data, request.language or "auto", request.format
+        )
+        cached = _asr_cache_get(cache_key)
+        if cached is not None:
+            logger.info("audio_asr.cache_hit", model=self._model, text_length=len(cached))
+            return ASRResponse(text=cached)
+
+        # ── 构造 multipart 请求 ───────────────────────────────────────
+        mime = _MIME_MAP.get(request.format, "audio/wav")
+        filename = f"audio.{request.format}"
+        files = {"file": (filename, request.audio_data, mime)}
+        data: dict[str, str] = {}
+        if request.language:
+            data["language"] = request.language
+
+        # 本地 yuanqi 引擎通常无需鉴权；仅当配置了 api_key 才带 Authorization 头
+        headers: dict[str, str] = {}
+        if self._api_key:
+            headers["Authorization"] = f"Bearer {self._api_key}"
+
+        url = f"{self._base_url}{_ASR_PATH}"
+
+        logger.info(
+            "audio_asr.request",
+            model=self._model,
+            format=request.format,
+            language=request.language,
+            url=url,
+            size_bytes=len(request.audio_data),
+        )
+
+        # ── API 调用 ────────────────────────────────────────────────
+        try:
+            response = await self._http.post(url, files=files, data=data, headers=headers)
+        except httpx.TimeoutException as exc:
+            raise AudioServiceError(
+                status_code=504,
+                code="audio_asr_timeout",
+                message="ASR request timed out calling yuanqi transcriptions.",
+            ) from exc
+        except httpx.RequestError as exc:
+            raise AudioServiceError(
+                status_code=503,
+                code="audio_asr_connection_error",
+                message=f"ASR connection error: {exc}",
+            ) from exc
+
+        if response.status_code != 200:
+            body = response.text[:500]
+            raise AudioServiceError(
+                status_code=response.status_code,
+                code="audio_asr_api_error",
+                message=f"ASR API returned {response.status_code}: {body}",
+            )
+
+        # 解析响应，提取转写文本
+        text = self._extract_text(response.json())
+        if not text:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_asr_empty_response",
+                message="ASR API returned empty transcription.",
+            )
+
+        # ── 写入缓存 ────────────────────────────────────────────────
+        _asr_cache_set(cache_key, text)
+
+        logger.info(
+            "audio_asr.success",
+            model=self._model,
+            text_length=len(text),
+            cache_size=len(_asr_cache),
+        )
+        return ASRResponse(text=text)
+
+    # ── 辅助方法 ──────────────────────────────────────────────────────────
+
+    @staticmethod
+    def _extract_text(body: dict) -> str:
+        """从 Whisper 兼容响应中提取转写文本。"""
+        try:
+            text = body.get("text")
+            if text is None:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_asr_no_text",
+                    message="ASR response has no 'text' field.",
+                )
+            return text or ""
+        except AudioServiceError:
+            raise
+        except Exception as exc:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_asr_response_parse_error",
+                message=f"Failed to parse ASR response: {exc}",
+            ) from exc

backend/app/ai_provider/config/__init__.py

@@ -0,0 +1,31 @@
+from app.ai_provider.config.loader import (
+    get_models_config_path,
+    get_pricing_config_path,
+    get_providers_config_path,
+    load_models_config,
+    load_pricing_config,
+    load_providers_config,
+)
+from app.ai_provider.config.models import (
+    ModelConfig,
+    ModelEndpointConfig,
+    ParameterMapping,
+    ProviderConfig,
+    derive_capabilities,
+)
+from app.ai_provider.core.billing import PricingInfo
+
+__all__ = [
+    "ModelConfig",
+    "ModelEndpointConfig",
+    "PricingInfo",
+    "ProviderConfig",
+    "ParameterMapping",
+    "derive_capabilities",
+    "load_models_config",
+    "load_providers_config",
+    "load_pricing_config",
+    "get_models_config_path",
+    "get_providers_config_path",
+    "get_pricing_config_path",
+]

backend/app/ai_provider/config/loader.py

@@ -0,0 +1,80 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any
+
+import yaml
+from pydantic import BaseModel
+
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+from app.core.config import settings
+
+
+class _ModelsFile(BaseModel):
+    version: int = 1
+    models: list[ModelConfig]
+
+
+class _ProvidersFile(BaseModel):
+    version: int = 1
+    providers: dict[str, ProviderConfig]
+
+
+class _PricingFile(BaseModel):
+    """pricing.yaml 顶层结构。"""
+
+    version: int = 1
+    pricing: dict[str, dict] = {}
+
+
+def get_models_config_path() -> Path:
+    """返回已解析的 models.yaml 路径（project_root/config/models.yaml）。"""
+    return settings.project_root / "config" / "models.yaml"
+
+
+def get_providers_config_path() -> Path:
+    """返回已解析的 providers.yaml 路径（project_root/config/providers.yaml）。"""
+    return settings.project_root / "config" / "providers.yaml"
+
+
+def load_models_config(path: Path | None = None) -> list[ModelConfig]:
+    """从 YAML 文件加载模型配置。如果未指定路径，使用配置中的默认路径。"""
+    if path is None:
+        path = get_models_config_path()
+    if not path.exists():
+        raise FileNotFoundError(f"Models config not found: {path}")
+    raw: dict[str, Any] = yaml.safe_load(path.read_text(encoding="utf-8")) or {}
+    parsed = _ModelsFile.model_validate(raw)
+    return parsed.models
+
+
+def load_providers_config(path: Path | None = None) -> dict[str, ProviderConfig]:
+    """从 YAML 文件加载提供商配置。如果未指定路径，使用配置中的默认路径。"""
+    if path is None:
+        path = get_providers_config_path()
+    if not path.exists():
+        raise FileNotFoundError(f"Providers config not found: {path}")
+    raw: dict[str, Any] = yaml.safe_load(path.read_text(encoding="utf-8")) or {}
+    # 验证前将字典键注入为 provider 的 name 字段
+    providers_raw = raw.get("providers", {})
+    for name, cfg in providers_raw.items():
+        if isinstance(cfg, dict) and "name" not in cfg:
+            cfg["name"] = name
+    parsed = _ProvidersFile.model_validate(raw)
+    return parsed.providers
+
+
+def get_pricing_config_path() -> Path:
+    """返回 pricing.yaml 路径（project_root/config/pricing.yaml）。"""
+    return settings.project_root / "config" / "pricing.yaml"
+
+
+def load_pricing_config(path: Path | None = None) -> dict[str, dict]:
+    """从 YAML 文件加载定价配置。"""
+    if path is None:
+        path = get_pricing_config_path()
+    if not path.exists():
+        return {}
+    raw: dict[str, Any] = yaml.safe_load(path.read_text(encoding="utf-8")) or {}
+    parsed = _PricingFile.model_validate(raw)
+    return parsed.pricing

backend/app/ai_provider/config/models.py

@@ -0,0 +1,158 @@
+from __future__ import annotations
+
+from enum import StrEnum
+from typing import Any
+
+from pydantic import (  # noqa: TC002 — Pydantic 模型
+    BaseModel,
+    Field,
+    field_validator,
+    model_validator,
+)
+
+
+class SupportedFormats(StrEnum):
+    OPENAI = "openai"
+    ANTHROPIC = "anthropic"
+
+
+_BASE_CAPABILITIES = {
+    ("openai", "gpt"): {"chat", "tool_use", "structured_output"},
+    ("openai", "gpt-4"): {"chat", "tool_use", "structured_output", "vision", "reasoning"},
+    ("anthropic", "claude"): {
+        "chat",
+        "tool_use",
+        "structured_output",
+        "vision",
+        "reasoning",
+        "long_context",
+    },
+    ("deepseek", "deepseek"): {"chat", "tool_use", "structured_output", "reasoning"},
+    ("deepseek", "deepseek-v4"): {
+        "chat",
+        "tool_use",
+        "structured_output",
+        "reasoning",
+        "long_context",
+    },
+}
+
+
+def derive_capabilities(provider: str, model: str) -> set[str]:
+    """根据 provider + model 前缀自动推导能力。
+
+    调用者可以在调用此函数后，在 ModelConfig 上覆盖个别标记。
+    """
+    for (prov_prefix, model_prefix), caps in _BASE_CAPABILITIES.items():
+        if provider.startswith(prov_prefix) and model.startswith(model_prefix):
+            return set(caps)
+    return {"chat"}
+
+
+class ModelEndpointConfig(BaseModel):
+    name: str
+    model: str
+    base_url: str | None = None
+    base_url_env: str | None = None
+    api_key: str | None = None
+    api_key_env: str | None = None
+    weight: int = 100
+    priority: int = 100
+    rpm_limit: int | None = None
+    tpm_limit: int | None = None
+    max_concurrency: int | None = None
+    request_timeout_seconds: int | None = None
+    status: str = "active"
+    extra_params: dict[str, Any] = Field(default_factory=dict)
+
+
+class ModelConfig(BaseModel):
+    name: str
+    display_name: str | None = None
+    provider: str
+    model: str
+    format: SupportedFormats  # "openai" | "anthropic"
+    chat_format: str | None = None
+    tags: list[str] = Field(default_factory=list)
+    supports_tools: bool | None = None
+    supports_vision: bool | None = None
+    supports_reasoning_effort: bool | None = None
+    supports_thinking: bool | None = None
+    supports_streaming: bool | None = True
+    supports_structured_output: bool | None = None
+    context_window: int = 32000
+    response_reserve: int = 4096
+    max_output_tokens: int | None = None
+    max_thinking_tokens: int | None = None
+    reasoning_effort: str | None = None
+    timeout_seconds: int | None = 60
+    dimensions: int | None = None  # 向量维度（embedding 模型专用）
+    routing_strategy: str = "weighted_round_robin"
+    endpoint_pool_enabled: bool = False
+    weight: int = 100
+    endpoints: list[ModelEndpointConfig] = Field(default_factory=list)
+
+    @model_validator(mode="after")
+    def _validate_embedding_dimensions(self) -> ModelConfig:
+        """embedding 模型必须声明 dimensions。"""
+        if "embedding" in self.tags and self.dimensions is None:
+            raise ValueError(
+                f"Embedding 模型 '{self.name}' 必须设置 dimensions（如 dimensions: 1024）"
+            )
+        return self
+
+    def resolved_capabilities(self) -> dict[str, bool]:
+        base = derive_capabilities(self.provider, self.model)
+        return {
+            "chat": True,
+            "tool_use": self.supports_tools
+            if self.supports_tools is not None
+            else ("tool_use" in base),
+            "vision": self.supports_vision
+            if self.supports_vision is not None
+            else ("vision" in base),
+            "reasoning": self.supports_reasoning_effort
+            if self.supports_reasoning_effort is not None
+            else ("reasoning" in base),
+            "thinking": self.supports_thinking
+            if self.supports_thinking is not None
+            else ("reasoning" in base),
+            "streaming": self.supports_streaming if self.supports_streaming is not None else True,
+            "structured_output": self.supports_structured_output
+            if self.supports_structured_output is not None
+            else ("structured_output" in base),
+        }
+
+
+class ParameterMapping(BaseModel):
+    provider_param: str
+    min: float | None = None
+    max: float | None = None
+    default: Any = None
+    transform: str | None = None  # "multiply_1000", "int", "str"
+    alias_for: str | None = None  # map from another param name
+    handler: str | None = None  # named handler for complex param transform
+
+
+class ProviderConfig(BaseModel):
+    name: str
+    format: SupportedFormats
+    base_url_env: str
+    api_key_env: str
+    base_url: str | None = None
+    timeout_seconds: int = 60
+    max_retries: int = 1
+    parameter_mappings: dict[str, ParameterMapping] = Field(default_factory=dict)
+    parameter_handlers: list[str] = Field(
+        default_factory=list
+    )  # ordered global handlers per provider
+    extra_headers: dict[str, str] = Field(default_factory=dict)
+    supports_streaming: bool = True
+
+    @field_validator("format")
+    @classmethod
+    def _validate_format(cls, v: str) -> str:
+        allowed = {e.value for e in SupportedFormats}
+        if v not in allowed:
+            raise ValueError(f"format must be one of {allowed}, got '{v}'")
+        return v

backend/app/ai_provider/core/__init__.py

@@ -0,0 +1,17 @@
+from app.ai_provider.core.billing import PricingFactory, PricingInfo, PricingRegistry
+from app.ai_provider.core.registry import (
+    ModelRegistry,
+    ProviderRegistry,
+    RegistryFactory,
+    RegistryHolder,
+)
+
+__all__ = [
+    "ModelRegistry",
+    "ProviderRegistry",
+    "RegistryFactory",
+    "RegistryHolder",
+    "PricingInfo",
+    "PricingRegistry",
+    "PricingFactory",
+]

backend/app/ai_provider/core/billing.py

@@ -0,0 +1,253 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import date, datetime
+
+from pydantic import BaseModel
+
+from app.ai_provider.types.chat import TokenUsage
+
+
+@dataclass
+class CostBreakdown:
+    input_cost: float = 0.0
+    output_cost: float = 0.0
+    total: float = 0.0
+    currency: str = "CNY"
+
+
+class CostCalculator:
+    """根据价格信息和 token 数量计算成本。
+
+    保持厂商原始单位 —— 不做跨币种换算。
+
+    - 普通 input token 按 ``input_per_1m`` 计费。
+    - 缓存命中的 prompt token 优先按 ``input_cache_read_per_1m`` 计费
+      （若有配置），剩余按普通 input 费率。
+    - 若未配置 cache 费率，所有 prompt token 统一按 input_per_1m 计费。
+    """
+
+    @staticmethod
+    def calculate(
+        pricing: PricingInfo | None,
+        prompt_tokens: int,
+        completion_tokens: int,
+        prompt_tokens_cached: int = 0,
+    ) -> CostBreakdown:
+        if pricing is None:
+            return CostBreakdown(total=0.0)
+
+        # 缓存 token：优先走缓存费率
+        cached = min(prompt_tokens_cached, prompt_tokens)
+        uncached = prompt_tokens - cached
+
+        input_cost = 0.0
+        if uncached > 0 and pricing.input_per_1m is not None:
+            input_cost += (uncached / 1_000_000) * pricing.input_per_1m
+        if cached > 0 and pricing.input_cache_read_per_1m is not None:
+            input_cost += (cached / 1_000_000) * pricing.input_cache_read_per_1m
+        elif cached > 0 and pricing.input_per_1m is not None:
+            # 无缓存费率时统一按普通 input 计
+            input_cost += (cached / 1_000_000) * pricing.input_per_1m
+
+        output_cost = 0.0
+        if pricing.output_per_1m is not None and completion_tokens > 0:
+            output_cost = (completion_tokens / 1_000_000) * pricing.output_per_1m
+
+        return CostBreakdown(
+            input_cost=round(input_cost, 8),
+            output_cost=round(output_cost, 8),
+            total=round(input_cost + output_cost, 8),
+            currency=pricing.currency,
+        )
+
+
+@dataclass
+class UsageRecord:
+    model_name: str
+    provider: str
+    prompt_tokens: int = 0
+    completion_tokens: int = 0
+    total_tokens: int = 0
+    currency: str = "CNY"
+    cost: float = 0.0
+    timestamp: datetime = field(default_factory=datetime.now)
+    endpoint_name: str | None = None
+    status: str = "success"
+    error_message: str | None = None
+
+
+class BillingTracker:
+    """记录用量并按模型计算成本。"""
+
+    def __init__(self) -> None:
+        self._records: list[UsageRecord] = []
+
+    def record(
+        self,
+        model_name: str,
+        provider: str,
+        usage: TokenUsage | None,
+        pricing: PricingInfo | None = None,
+        endpoint_name: str | None = None,
+        status: str = "success",
+        error_message: str | None = None,
+    ) -> UsageRecord:
+        prompt_tokens = usage.prompt_tokens if usage else 0
+        completion_tokens = usage.completion_tokens if usage else 0
+        total = usage.total_tokens if usage else 0
+        cached = usage.prompt_tokens_cached if usage else 0
+
+        cost_info = CostCalculator.calculate(pricing, prompt_tokens, completion_tokens, cached)
+
+        record = UsageRecord(
+            model_name=model_name,
+            provider=provider,
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
+            total_tokens=total,
+            currency=cost_info.currency,
+            cost=cost_info.total,
+            endpoint_name=endpoint_name,
+            status=status,
+            error_message=error_message,
+        )
+        self._records.append(record)
+        return record
+
+    def get_records(
+        self,
+        since: datetime | None = None,
+        model_name: str | None = None,
+    ) -> list[UsageRecord]:
+        records = self._records
+        if since:
+            records = [r for r in records if r.timestamp >= since]
+        if model_name:
+            records = [r for r in records if r.model_name == model_name]
+        return records
+
+    def total_cost(self, currency: str | None = None) -> float:
+        if currency:
+            return sum(r.cost for r in self._records if r.currency == currency)
+        return sum(r.cost for r in self._records)
+
+
+class BudgetController:
+    """强制执行每日和每月预算限制。"""
+
+    def __init__(
+        self,
+        daily_budget_cny: float = 0.0,
+        monthly_budget_cny: float = 0.0,
+    ) -> None:
+        self.daily_budget_cny = daily_budget_cny
+        self.monthly_budget_cny = monthly_budget_cny
+        self._daily_cost_cny: float = 0.0
+        self._monthly_cost_cny: float = 0.0
+        self._current_date: date = date.today()
+
+    def add_cost_cny(self, cost: float) -> None:
+        self._daily_cost_cny += cost
+        self._monthly_cost_cny += cost
+
+    def allow_request(self) -> bool:
+        return not (
+            (self.daily_budget_cny > 0 and self._daily_cost_cny >= self.daily_budget_cny)
+            or (self.monthly_budget_cny > 0 and self._monthly_cost_cny >= self.monthly_budget_cny)
+        )
+
+    def reset_daily(self) -> None:
+        self._daily_cost_cny = 0.0
+        self._current_date = date.today()
+
+    def reset_monthly(self) -> None:
+        self._monthly_cost_cny = 0.0
+
+
+class BillingFactory:
+    """计费组件工厂。"""
+
+    @staticmethod
+    def create_tracker() -> BillingTracker:
+        return BillingTracker()
+
+    @staticmethod
+    def create_budget_controller(
+        daily_budget_cny: float = 0.0,
+        monthly_budget_cny: float = 0.0,
+    ) -> BudgetController:
+        return BudgetController(
+            daily_budget_cny=daily_budget_cny,
+            monthly_budget_cny=monthly_budget_cny,
+        )
+
+
+# ── 定价信息 ──────────────────────────────────────────────────────────
+
+
+class PricingInfo(BaseModel):
+    """模型定价信息。保持厂商原始单位，不转换不混合。
+
+    各厂商按各自币种/单位记录，展示时原生显示。
+    """
+
+    currency: str = "CNY"
+    input_per_1m: float | None = None
+    output_per_1m: float | None = None
+    input_cache_read_per_1m: float | None = None
+
+
+class PricingRegistry:
+    """模型定价注册表。以模型逻辑名为键查找定价。
+
+    与 ModelRegistry 解耦 —— 改价不影响模型注册，无定价的模型
+    也可以正常使用（不计费）。
+    """
+
+    def __init__(self, pricing_map: dict[str, PricingInfo] | None = None) -> None:
+        self._pricing: dict[str, PricingInfo] = dict(pricing_map or {})
+
+    def get(self, model_name: str) -> PricingInfo | None:
+        """获取指定模型的定价信息。无定价时返回 None。"""
+        return self._pricing.get(model_name)
+
+    def list_all(self) -> dict[str, PricingInfo]:
+        """返回全部定价数据的副本。"""
+        return dict(self._pricing)
+
+
+class PricingFactory:
+    """定价注册表工厂。"""
+
+    @staticmethod
+    def from_dict(data: dict[str, dict]) -> PricingRegistry:
+        """从 YAML 解析后的 dict 构建 PricingRegistry。
+
+        YAML 按厂商嵌套组织（自文档化），工厂将其摊平为按模型逻辑名索引：
+
+        ```yaml
+        pricing:
+          deepseek:
+            deepseek-v4-flash:
+              currency: CNY
+              input_per_1m: 1.0
+          anthropic:
+            claude-sonnet:
+              currency: USD
+              input_per_1m: 3.0
+        ```
+        """
+        pricing_map: dict[str, PricingInfo] = {}
+        for _provider_name, models_data in data.items():
+            if not isinstance(models_data, dict):
+                continue
+            for model_name, raw in models_data.items():
+                if raw is None:
+                    continue
+                # 跳过所有字段均为 null 的条目（如 mimo-v2.5-asr）
+                values = [v for v in raw.values() if not isinstance(v, bool)]
+                if all(v is None for v in values):
+                    continue
+                pricing_map[model_name] = PricingInfo(**raw)
+        return PricingRegistry(pricing_map)

backend/app/ai_provider/core/registry.py

@@ -0,0 +1,164 @@
+from __future__ import annotations
+
+import random
+
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+from app.ai_provider.core.billing import PricingFactory, PricingRegistry
+from app.ai_provider.types.errors import AIProviderError
+
+
+class ModelRegistry:
+    """内存模型索引。支持逻辑名和别名查找。"""
+
+    def __init__(
+        self,
+        models: list[ModelConfig],
+        aliases: dict[str, str] | None = None,
+    ) -> None:
+        self._models: dict[str, ModelConfig] = {}
+        self._aliases: dict[str, str] = dict(aliases or {})
+        self._default: str | None = None
+        self._fallback: str | None = None
+        self._capability_index: dict[str, list[ModelConfig]] = {}
+
+        for m in models:
+            self._models[m.name] = m
+            if "default" in m.tags and self._default is None:
+                self._default = m.name
+            if "fallback" in m.tags and self._fallback is None:
+                self._fallback = m.name
+            caps = m.resolved_capabilities()
+            for cap, supported in caps.items():
+                if supported:
+                    self._capability_index.setdefault(cap, []).append(m)
+            # 索引 tags（如 tts / asr / voice_clone）——这些不在
+            # resolved_capabilities() 中，但 AudioService 等模块依赖它们查找模型。
+            for tag in m.tags:
+                self._capability_index.setdefault(tag, []).append(m)
+
+        if self._default is None and models:
+            self._default = models[0].name
+
+    def get(self, name: str) -> ModelConfig:
+        model = self._models.get(name)
+        if model is None:
+            raise AIProviderError(
+                message=f"Model '{name}' not found in registry",
+                code="MODEL_NOT_FOUND",
+                status_code=404,
+            )
+        return model
+
+    def resolve(self, name_or_alias: str | None = None) -> ModelConfig:
+        """解析逻辑名或别名为 ModelConfig。
+
+        无参数时返回默认模型。
+        """
+        if name_or_alias is None:
+            return self._models[self.get_default_name()]
+        if name_or_alias in self._models:
+            return self._models[name_or_alias]
+        if name_or_alias in self._aliases:
+            logical = self._aliases[name_or_alias]
+            return self._models[logical]
+        raise AIProviderError(
+            message=f"Model or alias '{name_or_alias}' not found",
+            code="MODEL_NOT_FOUND",
+            status_code=404,
+        )
+
+    def resolve_name(self, name_or_alias: str) -> str:
+        """解析为规范逻辑名（不返回完整配置）。"""
+        if name_or_alias in self._models:
+            return name_or_alias
+        if name_or_alias in self._aliases:
+            return self._aliases[name_or_alias]
+        raise AIProviderError(
+            message=f"Model or alias '{name_or_alias}' not found",
+            code="MODEL_NOT_FOUND",
+            status_code=404,
+        )
+
+    def get_default_name(self) -> str:
+        if self._default is None:
+            raise AIProviderError(
+                message="No default model configured",
+                code="NO_DEFAULT_MODEL",
+                status_code=500,
+            )
+        return self._default
+
+    def get_fallback_name(self) -> str | None:
+        return self._fallback
+
+    def contains(self, name: str) -> bool:
+        return name in self._models
+
+    def list_all(self) -> list[ModelConfig]:
+        return list(self._models.values())
+
+    def list_by_capability(self, capability: str) -> list[ModelConfig]:
+        return list(self._capability_index.get(capability, []))
+
+    def resolve_by_capability(self, capability: str) -> str:
+        candidates = self._capability_index.get(capability)
+        if not candidates:
+            raise AIProviderError(
+                message=f"No active models with capability '{capability}'",
+                code="CAPABILITY_NOT_FOUND",
+                status_code=404,
+            )
+        weights = [max(c.weight, 1) for c in candidates]
+        chosen = random.choices(candidates, weights=weights, k=1)[0]
+        return chosen.name
+
+
+class ProviderRegistry:
+    """内存提供商配置索引。"""
+
+    def __init__(self, providers: dict[str, ProviderConfig]) -> None:
+        self._providers = dict(providers)
+
+    def get(self, name: str) -> ProviderConfig:
+        prov = self._providers.get(name)
+        if prov is None:
+            raise AIProviderError(
+                message=f"Provider '{name}' not configured",
+                code="PROVIDER_NOT_FOUND",
+                status_code=404,
+            )
+        return prov
+
+    def list_all(self) -> dict[str, ProviderConfig]:
+        return dict(self._providers)
+
+
+class RegistryFactory:
+    """工厂：从配置列表创建注册表。"""
+
+    @staticmethod
+    def create(
+        models: list[ModelConfig],
+        providers: dict[str, ProviderConfig],
+        aliases: dict[str, str] | None = None,
+        pricing_data: dict[str, dict] | None = None,
+    ) -> RegistryHolder:
+        return RegistryHolder(
+            model_registry=ModelRegistry(models, aliases=aliases),
+            provider_registry=ProviderRegistry(providers),
+            pricing_registry=PricingFactory.from_dict(pricing_data or {}),
+        )
+
+
+class RegistryHolder:
+    """同时持有所有注册表。"""
+
+    def __init__(
+        self,
+        model_registry: ModelRegistry,
+        provider_registry: ProviderRegistry,
+        pricing_registry: PricingRegistry | None = None,
+    ) -> None:
+        self.model_registry = model_registry
+        self.provider_registry = provider_registry
+        self.pricing_registry = pricing_registry or PricingRegistry()

backend/app/ai_provider/core/resilience.py

@@ -0,0 +1,133 @@
+from __future__ import annotations
+
+import time
+from enum import Enum
+
+
+class CircuitBreakerState(Enum):
+    CLOSED = "closed"
+    OPEN = "open"
+    HALF_OPEN = "half_open"
+
+
+class CircuitBreaker:
+    """标准断路器，冷却后自动半开。"""
+
+    def __init__(
+        self,
+        name: str,
+        failure_threshold: int = 5,
+        cooldown_seconds: float = 30.0,
+    ) -> None:
+        self.name = name
+        self.failure_threshold = failure_threshold
+        self.cooldown_seconds = cooldown_seconds
+        self._state = CircuitBreakerState.CLOSED
+        self._failure_count = 0
+        self._last_failure_time: float = 0.0
+
+    @property
+    def state(self) -> CircuitBreakerState:
+        if (
+            self._state == CircuitBreakerState.OPEN
+            and time.monotonic() - self._last_failure_time >= self.cooldown_seconds
+        ):
+            self._state = CircuitBreakerState.HALF_OPEN
+        return self._state
+
+    def record_success(self) -> None:
+        self._failure_count = 0
+        self._state = CircuitBreakerState.CLOSED
+
+    def record_failure(self) -> None:
+        self._failure_count += 1
+        self._last_failure_time = time.monotonic()
+        if self._failure_count >= self.failure_threshold:
+            self._state = CircuitBreakerState.OPEN
+
+    def allow_request(self) -> bool:
+        return self.state != CircuitBreakerState.OPEN
+
+
+class RetryStrategy:
+    """指数退避重试。"""
+
+    def __init__(
+        self,
+        max_retries: int = 3,
+        base_delay: float = 1.0,
+        max_delay: float = 60.0,
+        multiplier: float = 2.0,
+    ) -> None:
+        self.max_retries = max_retries
+        self.base_delay = base_delay
+        self.max_delay = max_delay
+        self.multiplier = multiplier
+
+    def should_retry(self, attempt_index: int) -> bool:
+        return attempt_index < self.max_retries
+
+    def get_delay(self, attempt_index: int) -> float:
+        delay = self.base_delay * (self.multiplier**attempt_index)
+        return min(delay, self.max_delay)
+
+
+class DowngradeAction:
+    """降级链中的一个步骤。"""
+
+    def __init__(self, type: str, target: str) -> None:  # noqa: A002
+        self.type = type  # "fallback_endpoint", "fallback_model", "cache", "degrade_quality"
+        self.target = target
+
+
+class DowngradeChain:
+    """当模型/端点失败时的降级动作链。"""
+
+    def __init__(self, actions: list[DowngradeAction]) -> None:
+        self._actions = actions
+        self._index = 0
+
+    def next_action(self) -> tuple[str, str] | None:
+        if self._index >= len(self._actions):
+            return None
+        action = self._actions[self._index]
+        return (action.type, action.target)
+
+    def advance(self) -> None:
+        self._index += 1
+
+    def is_exhausted(self) -> bool:
+        return self._index >= len(self._actions)
+
+    def reset(self) -> None:
+        self._index = 0
+
+
+class ResilienceFactory:
+    """弹性组件工厂。"""
+
+    @staticmethod
+    def create_circuit_breaker(
+        name: str,
+        failure_threshold: int = 5,
+        cooldown_seconds: float = 30.0,
+    ) -> CircuitBreaker:
+        return CircuitBreaker(
+            name=name,
+            failure_threshold=failure_threshold,
+            cooldown_seconds=cooldown_seconds,
+        )
+
+    @staticmethod
+    def create_retry_strategy(
+        max_retries: int = 3,
+        base_delay: float = 1.0,
+        max_delay: float = 60.0,
+        multiplier: float = 2.0,
+    ) -> RetryStrategy:
+        return RetryStrategy(
+            max_retries=max_retries,
+            base_delay=base_delay,
+            max_delay=max_delay,
+            multiplier=multiplier,
+        )

backend/app/ai_provider/embedding/__init__.py

@@ -0,0 +1,149 @@
+"""嵌入服务 — Embedding 适配器外观。
+
+用法::
+
+    from app.ai_provider.embedding import EmbeddingService
+
+    service = EmbeddingService(manager)
+    result = await service.embed("要嵌入的文本")
+    results = await service.embed(["文本1", "文本2"])
+"""
+
+from __future__ import annotations
+
+from app.ai_provider.embedding.base import (
+    EmbeddingProtocol,
+    EmbeddingRequest,
+    EmbeddingResponse,
+    EmbeddingResult,
+    EmbeddingServiceError,
+)
+from app.ai_provider.types.errors import AIProviderError
+
+
+class EmbeddingService:
+    """外观类，负责解析 Embedding 模型并委托给 ProviderManager。
+
+    接受 ProviderManager 或实现了以下接口的适配器：
+    - ``.model_registry`` → 具有 ``list_by_capability(capability)`` 方法
+    - ``.create_embedding(name)`` → 返回 EmbeddingProtocol 实例
+    """
+
+    def __init__(self, manager) -> None:
+        self._manager = manager
+        self._adapter: EmbeddingProtocol | None = None
+
+    # ── Registry 兼容适配 ─────────────────────────────────────────
+
+    @property
+    def _registry(self):
+        mgr = self._manager
+        if hasattr(mgr, "model_registry"):
+            return mgr.model_registry
+        return mgr
+
+    @property
+    def _factory(self):
+        mgr = self._manager
+        if hasattr(mgr, "create_embedding"):
+            return mgr
+        return None
+
+    # ── Embedding ──────────────────────────────────────────────────
+
+    @property
+    def adapter(self) -> EmbeddingProtocol:
+        """解析并缓存 Embedding 适配器。"""
+        if self._adapter is None:
+            self._adapter = self._resolve()
+        return self._adapter
+
+    async def embed(
+        self,
+        input: str | list[str],
+        model_hint: str | None = None,
+        dimensions: int | None = None,
+    ) -> EmbeddingResponse:
+        """快捷方法：构造请求并调用 Embedding 适配器。"""
+        model_name = self._resolve_model_name(model_hint)
+        # 优先从模型配置读 dimensions
+        effective_dimensions = dimensions
+        if effective_dimensions is None:
+            effective_dimensions = self._resolve_model_dimensions(model_hint)
+        request = EmbeddingRequest(
+            input=input if isinstance(input, list) else [input],
+            model=model_name,
+            dimensions=effective_dimensions,
+        )
+        return await self.adapter.embed(request)
+
+    # ── 解析 ───────────────────────────────────────────────────────
+
+    def _resolve(self) -> EmbeddingProtocol:
+        """查找第一个活跃的 Embedding 模型并通过工厂创建。"""
+        models = self._list_capability_models("embedding")
+        if not models:
+            raise AIProviderError(
+                status_code=503,
+                code="embedding_no_model",
+                message="No embedding model configured in the model registry.",
+            )
+        factory = self._factory
+        if factory is None:
+            raise AIProviderError(
+                status_code=501,
+                code="embedding_no_factory",
+                message="Embedding adapter factory not available (provider manager missing create_embedding).",
+            )
+        return factory.create_embedding(models[0].name)
+
+    def _resolve_model_name(self, model_hint: str | None) -> str:
+        models = self._list_capability_models("embedding")
+        if model_hint:
+            return model_hint
+        if models:
+            return models[0].name
+        return ""
+
+    def _resolve_model_dimensions(self, model_hint: str | None) -> int | None:
+        """从模型配置读取向量维度。"""
+        models = self._list_capability_models("embedding")
+        if model_hint:
+            for m in models:
+                if m.name == model_hint:
+                    return m.dimensions
+        if models:
+            return models[0].dimensions
+        return None
+
+    def _list_capability_models(self, tag: str):
+        reg = self._registry
+        if hasattr(reg, "list_capability_models"):
+            return reg.list_capability_models(tag)
+        if hasattr(reg, "list_by_capability"):
+            return reg.list_by_capability(tag)
+        return []
+
+    # ── 生命周期 ────────────────────────────────────────────────────
+
+    async def close(self) -> None:
+        if self._adapter is not None:
+            close = getattr(self._adapter, "close", None)
+            if close is not None:
+                await close()
+
+    async def __aenter__(self) -> EmbeddingService:
+        return self
+
+    async def __aexit__(self, *exc_info: object) -> None:
+        await self.close()
+
+
+__all__ = [
+    "EmbeddingProtocol",
+    "EmbeddingRequest",
+    "EmbeddingResponse",
+    "EmbeddingResult",
+    "EmbeddingService",
+    "EmbeddingServiceError",
+]

backend/app/ai_provider/embedding/base.py

@@ -0,0 +1,144 @@
+"""嵌入服务类型 — 请求/响应模型和协议定义。
+
+Embedding 适配器通过 HTTP 调用嵌入端点（通常是 OpenAI 兼容的 ``POST /v1/embeddings``），
+经由 ``EmbeddingService`` 或直接从 ``ProviderManager`` 消费。
+
+用法::
+
+    service = EmbeddingService(manager)
+    result = await service.embed("要嵌入的文本")
+
+    # 或通过工厂直接调用:
+    adapter = manager.create_embedding("text-embedding-3-small")
+    result = await adapter.embed(EmbeddingRequest(input=["文本"]))
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Protocol, runtime_checkable
+
+from app.ai_provider.types.errors import AIProviderError
+
+if TYPE_CHECKING:
+    from app.ai_provider.config.models import ModelConfig, ModelEndpointConfig
+
+
+class EmbeddingServiceError(AIProviderError):
+    """Embedding API 调用失败的基础错误。"""
+
+
+# ── 请求 / 响应 ────────────────────────────────────────────────────────
+
+
+@dataclass
+class EmbeddingRequest:
+    """将文本转换为向量的请求。
+
+    属性:
+        input: 待嵌入的文本字符串或字符串列表。
+        model: 模型标识符（如 ``"text-embedding-3-small"``）。
+        encoding_format: 返回编码格式（``"float"`` 或 ``"base64"``）。
+        dimensions: 输出向量的维度（仅部分模型支持）。
+        user: 终端用户标识（用于用量追踪）。
+    """
+
+    input: str | list[str]
+    model: str = ""
+    encoding_format: str = "float"
+    dimensions: int | None = None
+    user: str | None = None
+
+
+@dataclass
+class EmbeddingResult:
+    """单条文本的嵌入结果。"""
+
+    embedding: list[float]
+    index: int = 0
+
+
+@dataclass
+class EmbeddingResponse:
+    """嵌入 API 的完整响应。"""
+
+    data: list[EmbeddingResult]
+    model: str = ""
+    usage: dict[str, int] | None = None
+
+
+# ── Protocol ────────────────────────────────────────────────────────────
+
+
+@runtime_checkable
+class EmbeddingProtocol(Protocol):
+    """Embedding 适配器的协议。"""
+
+    async def embed(self, request: EmbeddingRequest) -> EmbeddingResponse:
+        """将文本转换为向量。
+
+        异常:
+            EmbeddingServiceError: API 调用失败或响应异常时抛出。
+        """
+        ...
+
+    async def close(self) -> None:
+        """释放适配器持有的 HTTP 连接。"""
+        ...
+
+
+# ── 共享工厂基类 ──────────────────────────────────────────────────────
+
+
+class EmbeddingAdapterBase:
+    """Embedding 适配器基类，提供共享的工厂方法。
+
+    子类应在 ``__init__`` 中接受 ``base_url``、``api_key``、``model``、
+    ``request_timeout_seconds`` 参数。
+    """
+
+    _adapter_type: str = "embedding"
+    _default_timeout: int = 60
+
+    @classmethod
+    def from_endpoint(
+        cls,
+        endpoint: ModelEndpointConfig,
+        *,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从已解析的端点配置构建适配器。"""
+        base_url = endpoint.base_url
+        api_key = endpoint.api_key
+        if not base_url:
+            raise EmbeddingServiceError(
+                status_code=500,
+                code="embedding_endpoint_invalid",
+                message="Embedding endpoint has no resolved base_url.",
+                details={"endpoint": endpoint.name},
+            )
+        return cls(
+            base_url=base_url,
+            api_key=api_key,
+            model=endpoint.model,
+            request_timeout_seconds=timeout_seconds
+            or endpoint.request_timeout_seconds
+            or cls._default_timeout,
+        )
+
+    @classmethod
+    def from_model_config(
+        cls,
+        config: ModelConfig,
+        *,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从逻辑模型配置构建适配器（使用第一个活跃端点）。"""
+        for ep in config.endpoints:
+            if ep.status == "active":
+                return cls.from_endpoint(ep, timeout_seconds=timeout_seconds)
+        raise EmbeddingServiceError(
+            status_code=500,
+            code="embedding_no_endpoint",
+            message=f"Embedding model '{config.name}' has no active endpoint.",
+        )

backend/app/ai_provider/embedding/openai_format.py

@@ -0,0 +1,169 @@
+"""OpenAI 兼容格式的 Embedding 适配器 — ``POST /v1/embeddings``。
+
+覆盖 OpenAI、DeepSeek、以及任何兼容 OpenAI 嵌入端点的提供商。
+
+请求::
+
+    POST {base_url}/v1/embeddings
+    Authorization: Bearer {api_key}
+    Content-Type: application/json
+
+    {
+        "model": "text-embedding-3-small",
+        "input": ["要嵌入的文本"],
+        "encoding_format": "float"
+    }
+
+响应::
+
+    {
+        "object": "list",
+        "data": [
+            {"object": "embedding", "index": 0, "embedding": [0.xxx, ...]}
+        ],
+        "model": "text-embedding-3-small",
+        "usage": {"prompt_tokens": 5, "total_tokens": 5}
+    }
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+
+from app.ai_provider.embedding.base import (
+    EmbeddingAdapterBase,
+    EmbeddingProtocol,
+    EmbeddingRequest,
+    EmbeddingResponse,
+    EmbeddingResult,
+    EmbeddingServiceError,
+)
+from app.core.logging import logger
+
+
+class OpenAIFormatEmbeddingAdapter(EmbeddingAdapterBase, EmbeddingProtocol):
+    """OpenAI 兼容嵌入适配器，覆盖 95%+ 的嵌入服务提供商。"""
+
+    _adapter_type = "embedding"
+    _default_timeout = 60
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str = "text-embedding-3-small",
+        request_timeout_seconds: int = 60,
+    ) -> None:
+        self._base_url = base_url.rstrip("/")
+        self._api_key = api_key
+        self._model = model
+        self._timeout = request_timeout_seconds
+        self._client: httpx.AsyncClient | None = None
+
+    # ── 客户端 ───────────────────────────────────────────────────────────
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None or self._client.is_closed:
+            self._client = httpx.AsyncClient(timeout=httpx.Timeout(self._timeout))
+        return self._client
+
+    async def close(self) -> None:
+        if self._client is not None and not self._client.is_closed:
+            await self._client.aclose()
+
+    # ── EmbeddingProtocol ────────────────────────────────────────────────
+
+    async def embed(self, request: EmbeddingRequest) -> EmbeddingResponse:
+        """通过 ``POST /v1/embeddings`` 将文本转换为向量。"""
+        url = f"{self._base_url}/v1/embeddings"
+
+        payload: dict[str, Any] = {
+            "model": request.model or self._model,
+            "input": request.input,
+            "encoding_format": request.encoding_format,
+        }
+        if request.dimensions is not None:
+            payload["dimensions"] = request.dimensions
+        if request.user is not None:
+            payload["user"] = request.user
+
+        headers = {
+            "Content-Type": "application/json",
+        }
+        if self._api_key:
+            headers["Authorization"] = f"Bearer {self._api_key}"
+
+        logger.info(
+            "embedding.request",
+            model=payload["model"],
+            input_count=len(request.input) if isinstance(request.input, list) else 1,
+            dimensions=request.dimensions,
+            url=url,
+        )
+
+        try:
+            response = await self._http.post(url, json=payload, headers=headers)
+        except httpx.TimeoutException as exc:
+            raise EmbeddingServiceError(
+                status_code=504,
+                code="embedding_timeout",
+                message="Embedding request timed out.",
+            ) from exc
+        except httpx.RequestError as exc:
+            raise EmbeddingServiceError(
+                status_code=503,
+                code="embedding_connection_error",
+                message=f"Embedding connection error: {exc}",
+            ) from exc
+
+        if response.status_code != 200:
+            body = response.text[:500]
+            raise EmbeddingServiceError(
+                status_code=response.status_code,
+                code="embedding_api_error",
+                message=f"Embedding API returned {response.status_code}: {body}",
+            )
+
+        result = self._parse_response(response.json())
+
+        logger.info(
+            "embedding.success",
+            model=payload["model"],
+            total_vectors=len(result.data),
+            usage=result.usage,
+        )
+        return result
+
+    # ── 辅助方法 ──────────────────────────────────────────────────────────
+
+    @staticmethod
+    def _parse_response(body: dict) -> EmbeddingResponse:
+        """从 OpenAI 格式的嵌入响应中提取结果。"""
+        try:
+            raw_data = body.get("data", [])
+            results = []
+            for item in raw_data:
+                results.append(
+                    EmbeddingResult(
+                        embedding=item.get("embedding", []),
+                        index=item.get("index", 0),
+                    )
+                )
+            # 按 index 排序确保顺序
+            results.sort(key=lambda r: r.index)
+
+            return EmbeddingResponse(
+                data=results,
+                model=body.get("model", ""),
+                usage=body.get("usage"),
+            )
+        except Exception as exc:
+            raise EmbeddingServiceError(
+                status_code=500,
+                code="embedding_response_parse_error",
+                message=f"Failed to parse embedding response: {exc}",
+            ) from exc

backend/app/ai_provider/llm/__init__.py

@@ -0,0 +1,18 @@
+from __future__ import annotations
+
+from app.ai_provider.llm.anthropic_format import (
+    AnthropicFormatAdapter,
+    AnthropicFormatAdapterFactory,
+)
+from app.ai_provider.llm.openai_format import OpenAIFormatAdapter, OpenAIFormatAdapterFactory
+from app.ai_provider.llm.stream import StreamFactory, StreamHandler, ToolCallAccumulator
+
+__all__ = [
+    "AnthropicFormatAdapter",
+    "AnthropicFormatAdapterFactory",
+    "OpenAIFormatAdapter",
+    "OpenAIFormatAdapterFactory",
+    "StreamFactory",
+    "StreamHandler",
+    "ToolCallAccumulator",
+]

backend/app/ai_provider/llm/anthropic_format.py

@@ -0,0 +1,433 @@
+from __future__ import annotations
+
+import json
+from collections.abc import AsyncIterator
+from typing import Any
+
+import httpx
+
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+from app.ai_provider.pipeline import ParameterPipeline, PipelineContext, PipelineFactory
+from app.ai_provider.types.chat import ChatChunk, ChatResult, TokenUsage
+from app.ai_provider.types.errors import AIProviderError
+from app.ai_provider.types.messages import (
+    AIMessage,
+    BaseMessage,
+    SystemMessage,
+    ToolMessage,
+)
+from app.core.logging import logger
+
+
+class AnthropicFormatAdapter:
+    """兼容 Anthropic Messages API 格式的适配器。
+
+    覆盖通过 Anthropic API 访问的 Claude 模型，以及任何镜像
+    Anthropic 消息格式的提供商。
+    """
+
+    API_VERSION = "2023-06-01"
+
+    def __init__(
+        self,
+        provider_config: ProviderConfig,
+        pipeline: ParameterPipeline | None = None,
+    ) -> None:
+        self._provider = provider_config
+        self._pipeline = pipeline or PipelineFactory.create(provider_config)
+        self._client: httpx.AsyncClient | None = None
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None:
+            self._client = httpx.AsyncClient(
+                base_url=self._provider.base_url or "",
+                timeout=self._provider.timeout_seconds,
+            )
+        return self._client
+
+    # ------------------------------------------------------------------
+    # 内部方法：消息转换
+    # ------------------------------------------------------------------
+
+    def _convert_message(self, msg: BaseMessage) -> dict[str, Any]:
+        """将单条消息转换为 Anthropic 消息格式。
+
+        Anthropic 使用 content blocks 数组而非纯字符串。
+        System 消息**不在此处处理** —— 它们由 :meth:`build_request`
+        提取到顶层的 ``system`` 字段中。
+        """
+        if isinstance(msg, ToolMessage):
+            return {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": msg.tool_call_id,
+                        "content": msg.content,
+                    }
+                ],
+            }
+
+        if isinstance(msg, AIMessage):
+            if msg.raw_content_blocks:
+                return {"role": "assistant", "content": msg.raw_content_blocks}
+            blocks: list[dict[str, Any]] = []
+            if msg.content:
+                blocks.append({"type": "text", "text": msg.content})
+            for tc in msg.tool_calls:
+                blocks.append(
+                    {
+                        "type": "tool_use",
+                        "id": tc.get("id", f"tu_{tc['name']}"),
+                        "name": tc["name"],
+                        "input": tc.get("args", {}),
+                    }
+                )
+            return {"role": "assistant", "content": blocks}
+
+        # HumanMessage
+        return {
+            "role": "user",
+            "content": [{"type": "text", "text": msg.content}],
+        }
+
+    @staticmethod
+    def _convert_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
+        """将 OpenAI 兼容格式的工具转换为 Anthropic 格式。
+
+        OpenAI 格式::
+
+            {"type": "function", "function": {"name": ..., "parameters": ...}}
+
+        Anthropic 格式::
+
+            {"name": ..., "input_schema": ...}
+        """
+        result: list[dict[str, Any]] = []
+        for tool in tools:
+            fn = tool.get("function", tool)
+            result.append(
+                {
+                    "name": fn.get("name", ""),
+                    "description": fn.get("description", ""),
+                    "input_schema": fn.get("parameters", {"type": "object"}),
+                }
+            )
+        return result
+
+    # ------------------------------------------------------------------
+    # 请求构建
+    # ------------------------------------------------------------------
+
+    def build_request(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+        stream: bool = False,
+    ) -> dict[str, Any]:
+        ctx = PipelineContext(
+            params=params or {},
+            model_config=model,
+            provider_config=self._provider,
+        )
+        pipe_result = self._pipeline.run(ctx)
+
+        # Extract system messages — Anthropic uses a top-level "system" field
+        system_parts: list[str] = []
+        non_system: list[BaseMessage] = []
+        for m in messages:
+            if isinstance(m, SystemMessage):
+                system_parts.append(m.content)
+            else:
+                non_system.append(m)
+
+        body: dict[str, Any] = {
+            "model": model.model,
+            "messages": [self._convert_message(m) for m in non_system],
+            "stream": stream,
+        }
+
+        if system_parts:
+            body["system"] = "\n".join(system_parts)
+
+        body.update(pipe_result.params)
+
+        if tools:
+            body["tools"] = self._convert_tools(tools)
+            if tool_choice:
+                body["tool_choice"] = tool_choice
+
+        # Anthropic requires explicit max_tokens
+        if "max_tokens" not in body:
+            body["max_tokens"] = model.max_output_tokens or 4096
+
+        return body
+
+    def bind_tools(
+        self,
+        request_body: dict[str, Any],
+        tools: list[dict[str, Any]],
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> None:
+        request_body["tools"] = self._convert_tools(tools)
+        if tool_choice:
+            request_body["tool_choice"] = tool_choice
+
+    # ------------------------------------------------------------------
+    # 认证头
+    # ------------------------------------------------------------------
+
+    def _headers(self, api_key: str) -> dict[str, str]:
+        return {
+            "x-api-key": api_key,
+            "anthropic-version": self.API_VERSION,
+            "Content-Type": "application/json",
+        }
+
+    # ------------------------------------------------------------------
+    # 响应解析 —— 非流式
+    # ------------------------------------------------------------------
+
+    @staticmethod
+    def _parse_content_blocks(raw: dict[str, Any]) -> tuple[str, list[dict[str, Any]], str]:
+        """解析 Anthropic content blocks 为 (text, tool_calls, reasoning)。"""
+        content_blocks = raw.get("content", [])
+        text_parts: list[str] = []
+        tool_calls: list[dict[str, Any]] = []
+        reasoning = ""
+
+        for block in content_blocks:
+            block_type = block.get("type", "")
+            if block_type == "text":
+                text_parts.append(block.get("text", ""))
+            elif block_type == "tool_use":
+                tool_calls.append(
+                    {
+                        "name": block.get("name", ""),
+                        "args": block.get("input", {}),
+                        "id": block.get("id", ""),
+                    }
+                )
+            elif block_type == "thinking":
+                reasoning += block.get("thinking", "")
+            # signature 块是 thinking 的加密签名，不是 reasoning 内容，忽略
+
+        return "".join(text_parts), tool_calls, reasoning
+
+    def parse_nonstreaming_response(
+        self,
+        raw: dict[str, Any],
+        model_name: str,
+    ) -> ChatResult:
+        content, tool_calls, reasoning = self._parse_content_blocks(raw)
+
+        result = ChatResult(
+            content=content,
+            model_name=model_name,
+        )
+        if tool_calls:
+            result.tool_calls = tool_calls
+        if reasoning:
+            result.reasoning = reasoning
+
+        usage = raw.get("usage")
+        if usage:
+            result.usage = TokenUsage(
+                prompt_tokens=usage.get("input_tokens", 0),
+                prompt_tokens_cached=usage.get("cache_read_input_tokens", 0),
+                completion_tokens=usage.get("output_tokens", 0),
+                total_tokens=usage.get("input_tokens", 0) + usage.get("output_tokens", 0),
+            )
+
+        return result
+
+    # ------------------------------------------------------------------
+    # 响应解析 —— 流式（SSE 事件行协议）
+    # ------------------------------------------------------------------
+
+    @staticmethod
+    def _parse_stream_event(event_type: str, data: dict[str, Any]) -> ChatChunk:
+        """解析单条 SSE 流事件为 ChatChunk。"""
+        chunk = ChatChunk()
+
+        if event_type == "message_start":
+            message = data.get("message", {})
+            usage = message.get("usage")
+            if usage:
+                chunk.usage = TokenUsage(
+                    prompt_tokens=usage.get("input_tokens", 0),
+                    prompt_tokens_cached=usage.get("cache_read_input_tokens", 0),
+                    completion_tokens=usage.get("output_tokens", 0),
+                )
+
+        elif event_type == "content_block_start":
+            block = data.get("content_block", {})
+            chunk.content_block_index = data.get("index", 0)
+            chunk.content_block_start = block
+            block_type = block.get("type", "")
+            if block_type == "text":
+                chunk.delta_content = block.get("text", "")
+            elif block_type == "thinking":
+                chunk.delta_reasoning = block.get("thinking", "")
+            elif block_type == "tool_use":
+                chunk.tool_call_chunks.append(
+                    {
+                        "index": data.get("index", 0),
+                        "id": block.get("id"),
+                        "name": block.get("name"),
+                        "args": "",
+                    }
+                )
+
+        elif event_type == "content_block_delta":
+            delta = data.get("delta", {})
+            chunk.content_block_index = data.get("index", 0)
+            chunk.content_block_delta = delta
+            delta_type = delta.get("type", "")
+            if delta_type == "text_delta":
+                chunk.delta_content = delta.get("text", "")
+            elif delta_type == "thinking_delta":
+                chunk.delta_reasoning = delta.get("thinking", "")
+            elif delta_type == "signature_delta":
+                # signature 不展示，但由 Agent Runtime 原样保留供下一轮回放。
+                pass
+            elif delta_type == "input_json_delta":
+                chunk.tool_call_chunks.append(
+                    {
+                        "index": data.get("index", 0),
+                        "id": None,
+                        "name": None,
+                        "args": delta.get("partial_json", ""),
+                    }
+                )
+
+        elif event_type == "message_delta":
+            delta = data.get("delta", {})
+            finish_reason_map = {
+                "end_turn": "stop",
+                "max_tokens": "length",
+                "stop_sequence": "stop",
+                "tool_use": "tool_calls",
+            }
+            stop_reason = delta.get("stop_reason")
+            if stop_reason:
+                chunk.finish_reason = finish_reason_map.get(stop_reason, stop_reason)
+
+            usage = data.get("usage")
+            if usage:
+                chunk.usage = TokenUsage(
+                    prompt_tokens=0,
+                    completion_tokens=usage.get("output_tokens", 0),
+                )
+
+        # content_block_stop, message_stop, ping — no content to extract
+
+        return chunk
+
+    # ------------------------------------------------------------------
+    # 公开 API：chat
+    # ------------------------------------------------------------------
+
+    async def chat(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        api_key: str,
+        base_url: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> ChatResult:
+        url = f"{base_url or self._provider.base_url}/v1/messages"
+        body = self.build_request(
+            model,
+            messages,
+            params=params,
+            tools=tools,
+            tool_choice=tool_choice,
+        )
+
+        try:
+            response = await self._http.post(url, json=body, headers=self._headers(api_key))
+            response.raise_for_status()
+            data = response.json()
+            return self.parse_nonstreaming_response(data, model.name)
+        except httpx.HTTPStatusError as exc:
+            raise AIProviderError.from_provider(
+                message=f"Anthropic API error: {exc.response.status_code} {exc.response.text[:200]}",
+                code="PROVIDER_ERROR",
+                provider=self._provider.name,
+                original=exc,
+            ) from exc
+
+    async def chat_stream(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        api_key: str,
+        base_url: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> AsyncIterator[ChatChunk]:
+        url = f"{base_url or self._provider.base_url}/v1/messages"
+        body = self.build_request(
+            model,
+            messages,
+            params=params,
+            tools=tools,
+            tool_choice=tool_choice,
+            stream=True,
+        )
+
+        async with self._http.stream(
+            "POST",
+            url,
+            json=body,
+            headers=self._headers(api_key),
+        ) as response:
+            if response.status_code != 200:
+                error_text = await response.aread()
+                raise AIProviderError.from_provider(
+                    message=f"Anthropic stream error: {response.status_code} {error_text[:200]}",
+                    code="PROVIDER_ERROR",
+                    provider=self._provider.name,
+                )
+
+            current_event = ""
+            async for line in response.aiter_lines():
+                line = line.strip()
+                if not line:
+                    continue
+                if line.startswith("event: "):
+                    current_event = line[7:]
+                elif line.startswith("data: "):
+                    data_str = line[6:]
+                    if data_str and current_event:
+                        try:
+                            raw = json.loads(data_str)
+                            yield self._parse_stream_event(current_event, raw)
+                        except json.JSONDecodeError:
+                            logger.warning(
+                                "anthropic_stream_parse_error",
+                                event=current_event,
+                                raw=data_str[:100],
+                            )
+                    current_event = ""
+
+    async def close(self) -> None:
+        if self._client:
+            await self._client.aclose()
+            self._client = None
+
+
+class AnthropicFormatAdapterFactory:
+    """工厂：创建 Anthropic 格式适配器。"""
+
+    @staticmethod
+    def create(provider_config: ProviderConfig) -> AnthropicFormatAdapter:
+        return AnthropicFormatAdapter(provider_config=provider_config)

backend/app/ai_provider/llm/openai_format.py

@@ -0,0 +1,251 @@
+from __future__ import annotations
+
+import json
+from collections.abc import AsyncIterator
+from typing import Any
+
+import httpx
+
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+from app.ai_provider.pipeline import ParameterPipeline, PipelineContext, PipelineFactory
+from app.ai_provider.types.chat import ChatChunk, ChatResult, TokenUsage
+from app.ai_provider.types.errors import AIProviderError
+from app.ai_provider.types.messages import AIMessage, BaseMessage, ToolMessage
+from app.core.logging import logger
+
+
+class OpenAIFormatAdapter:
+    """兼容 OpenAI API 格式的适配器（覆盖 deepseek、xiaomi 等）。"""
+
+    def __init__(
+        self,
+        provider_config: ProviderConfig,
+        pipeline: ParameterPipeline | None = None,
+    ) -> None:
+        self._provider = provider_config
+        self._pipeline = pipeline or PipelineFactory.create(provider_config)
+        self._client: httpx.AsyncClient | None = None
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None:
+            self._client = httpx.AsyncClient(
+                base_url=self._provider.base_url or "",
+                timeout=self._provider.timeout_seconds,
+            )
+        return self._client
+
+    def _convert_message(self, msg: BaseMessage) -> dict[str, Any]:
+        if isinstance(msg, ToolMessage):
+            return {
+                "role": "tool",
+                "content": msg.content,
+                "tool_call_id": msg.tool_call_id,
+            }
+        if isinstance(msg, AIMessage):
+            d: dict[str, Any] = {"role": "assistant", "content": msg.content}
+            if msg.tool_calls:
+                d["tool_calls"] = [
+                    {
+                        "id": tc.get("id", f"call_{i}"),
+                        "type": "function",
+                        "function": {
+                            "name": tc["name"],
+                            "arguments": json.dumps(tc.get("args", {})),
+                        },
+                    }
+                    for i, tc in enumerate(msg.tool_calls)
+                ]
+            return d
+        return {"role": msg.role, "content": msg.content}
+
+    def build_request(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+        stream: bool = False,
+    ) -> dict[str, Any]:
+        ctx = PipelineContext(
+            params=params or {},
+            model_config=model,
+            provider_config=self._provider,
+        )
+        pipe_result = self._pipeline.run(ctx)
+
+        body: dict[str, Any] = {
+            "model": model.model,
+            "messages": [self._convert_message(m) for m in messages],
+            "stream": stream,
+        }
+        body.update(pipe_result.params)
+
+        if tools:
+            body["tools"] = tools
+            if tool_choice:
+                body["tool_choice"] = tool_choice
+
+        return body
+
+    def bind_tools(
+        self,
+        request_body: dict[str, Any],
+        tools: list[dict[str, Any]],
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> None:
+        request_body["tools"] = tools
+        if tool_choice:
+            request_body["tool_choice"] = tool_choice
+
+    def parse_chunk(self, raw: dict[str, Any]) -> ChatChunk:
+        chunk = ChatChunk()
+        choices = raw.get("choices", [])
+        if choices:
+            delta = choices[0].get("delta", {})
+            chunk.delta_content = delta.get("content") or ""
+            chunk.delta_reasoning = delta.get("reasoning_content") or ""
+            chunk.finish_reason = choices[0].get("finish_reason")
+
+            if delta.get("tool_calls"):
+                for tc in delta["tool_calls"]:
+                    fn = tc.get("function", {})
+                    chunk.tool_call_chunks.append(
+                        {
+                            "index": tc.get("index", 0),
+                            "id": tc.get("id"),
+                            "name": fn.get("name"),
+                            "args": fn.get("arguments", ""),
+                        }
+                    )
+        usage = raw.get("usage")
+        if usage:
+            chunk.usage = TokenUsage(
+                prompt_tokens=usage.get("prompt_tokens", 0),
+                completion_tokens=usage.get("completion_tokens", 0),
+                total_tokens=usage.get("total_tokens", 0),
+                prompt_tokens_cached=usage.get("prompt_tokens_cached", 0),
+            )
+        return chunk
+
+    def parse_nonstreaming_response(
+        self,
+        raw: dict[str, Any],
+        model_name: str,
+    ) -> ChatResult:
+        choice = raw.get("choices", [{}])[0]
+        message = choice.get("message", {})
+        content = message.get("content", "")
+        tool_calls_raw = message.get("tool_calls", [])
+
+        result = ChatResult(
+            content=content,
+            reasoning=message.get("reasoning_content", ""),
+            model_name=model_name,
+        )
+        if tool_calls_raw:
+            result.tool_calls = [
+                {
+                    "name": tc["function"]["name"],
+                    "args": json.loads(tc["function"].get("arguments", "{}")),
+                    "id": tc["id"],
+                }
+                for tc in tool_calls_raw
+            ]
+
+        usage = raw.get("usage")
+        if usage:
+            result.usage = TokenUsage(
+                prompt_tokens=usage.get("prompt_tokens", 0),
+                completion_tokens=usage.get("completion_tokens", 0),
+                total_tokens=usage.get("total_tokens", 0),
+                prompt_tokens_cached=usage.get("prompt_tokens_cached", 0),
+            )
+        return result
+
+    async def chat(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        api_key: str,
+        base_url: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> ChatResult:
+        url = f"{base_url or self._provider.base_url}/chat/completions"
+        body = self.build_request(
+            model, messages, params=params, tools=tools, tool_choice=tool_choice
+        )
+
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+
+        try:
+            response = await self._http.post(url, json=body, headers=headers)
+            response.raise_for_status()
+            data = response.json()
+            return self.parse_nonstreaming_response(data, model.name)
+        except httpx.HTTPStatusError as exc:
+            raise AIProviderError.from_provider(
+                message=f"OpenAI API error: {exc.response.status_code} {exc.response.text[:200]}",
+                code="PROVIDER_ERROR",
+                provider=self._provider.name,
+                original=exc,
+            ) from exc
+
+    async def chat_stream(
+        self,
+        model: ModelConfig,
+        messages: list[BaseMessage],
+        api_key: str,
+        base_url: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> AsyncIterator[ChatChunk]:
+        url = f"{base_url or self._provider.base_url}/chat/completions"
+        body = self.build_request(
+            model, messages, params=params, tools=tools, tool_choice=tool_choice, stream=True
+        )
+
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+
+        async with self._http.stream("POST", url, json=body, headers=headers) as response:
+            if response.status_code != 200:
+                error_text = await response.aread()
+                raise AIProviderError.from_provider(
+                    message=f"OpenAI stream error: {response.status_code} {error_text[:200]}",
+                    code="PROVIDER_ERROR",
+                    provider=self._provider.name,
+                )
+            async for line in response.aiter_lines():
+                if line.startswith("data: "):
+                    data_str = line[6:].strip()
+                    if data_str == "[DONE]":
+                        break
+                    if data_str:
+                        try:
+                            raw = json.loads(data_str)
+                            yield self.parse_chunk(raw)
+                        except json.JSONDecodeError:
+                            logger.warning("openai_stream_parse_error", raw=data_str[:100])
+
+    async def close(self) -> None:
+        if self._client:
+            await self._client.aclose()
+            self._client = None
+
+
+class OpenAIFormatAdapterFactory:
+    """工厂：创建 OpenAI 格式适配器。"""
+
+    @staticmethod
+    def create(provider_config: ProviderConfig) -> OpenAIFormatAdapter:
+        return OpenAIFormatAdapter(provider_config=provider_config)

backend/app/ai_provider/llm/pool.py

@@ -0,0 +1,164 @@
+from __future__ import annotations
+
+import random
+from collections.abc import Callable
+from dataclasses import dataclass, field
+from typing import Any, Protocol
+
+
+@dataclass
+class PoolContext:
+    request_id: str = ""
+    excluded_endpoints: set[str] = field(default_factory=set)
+
+
+class SchedulingStrategy(Protocol):
+    def select(self, excluded: set[str]) -> dict[str, Any] | None: ...
+
+
+class WeightedRoundRobinStrategy:
+    """策略 1：在所有活跃端点间加权轮询。"""
+
+    def __init__(self, endpoints: list[dict[str, Any]]) -> None:
+        self._endpoints = endpoints
+        self._index = 0
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        available = [
+            e
+            for e in self._endpoints
+            if e.get("name") not in excluded and e.get("status", "active") == "active"
+        ]
+        if not available:
+            return None
+        weights = [e.get("weight", 100) for e in available]
+        self._index = (self._index + 1) % len(available)
+        return random.choices(available, weights=weights, k=1)[0]
+
+
+class PriorityFailoverStrategy:
+    """策略 2：选择最高优先级；当排除时顺延。"""
+
+    def __init__(self, endpoints: list[dict[str, Any]]) -> None:
+        self._endpoints = sorted(endpoints, key=lambda e: e.get("priority", 100))
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        for ep in self._endpoints:
+            if ep.get("name") not in excluded and ep.get("status", "active") == "active":
+                return ep
+        return None
+
+
+class LowestLatencyStrategy:
+    """策略 3：选择最近延迟最低的端点。"""
+
+    def __init__(self, endpoints: list[dict[str, Any]]) -> None:
+        self._endpoints = endpoints
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        available = [
+            e
+            for e in self._endpoints
+            if e.get("name") not in excluded and e.get("status", "active") == "active"
+        ]
+        if not available:
+            return None
+        return min(available, key=lambda e: e.get("latency_ms", 1000))
+
+
+class LeastConnectionsStrategy:
+    """策略 4：选择活跃连接数最少的端点。"""
+
+    def __init__(self, endpoints: list[dict[str, Any]]) -> None:
+        self._endpoints = endpoints
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        available = [
+            e
+            for e in self._endpoints
+            if e.get("name") not in excluded and e.get("status", "active") == "active"
+        ]
+        if not available:
+            return None
+        return min(available, key=lambda e: e.get("connections", 0))
+
+
+class CostAwareStrategy:
+    """策略 5：按每 token 成本选择最便宜的端点。"""
+
+    def __init__(
+        self, endpoints: list[dict[str, Any]], get_cost: Callable[[str], float] | None = None
+    ) -> None:
+        self._endpoints = endpoints
+        self._get_cost = get_cost or (lambda _: 0.0)
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        available = [
+            e
+            for e in self._endpoints
+            if e.get("name") not in excluded and e.get("status", "active") == "active"
+        ]
+        if not available:
+            return None
+        return min(available, key=lambda e: self._get_cost(e.get("name", "")))
+
+
+_STRATEGIES = {
+    "weighted_round_robin": WeightedRoundRobinStrategy,
+    "priority_failover": PriorityFailoverStrategy,
+    "lowest_latency": LowestLatencyStrategy,
+    "least_connections": LeastConnectionsStrategy,
+    "cost_aware": CostAwareStrategy,
+}
+
+
+class EndpointPool:
+    """模型池，带可插拔的调度策略。"""
+
+    def __init__(
+        self,
+        logical_model_name: str,
+        endpoints_configs: list[dict[str, Any]],
+        strategy: str = "weighted_round_robin",
+    ) -> None:
+        self.logical_model_name = logical_model_name
+        self._endpoints = endpoints_configs
+        strategy_cls = _STRATEGIES.get(strategy, WeightedRoundRobinStrategy)
+        self.strategy = (
+            strategy_cls(endpoints_configs)
+            if strategy == "priority_failover"
+            else strategy_cls(endpoints_configs)
+        )
+
+    def select(self, excluded: set[str]) -> dict[str, Any] | None:
+        """使用配置的策略选择一个端点。"""
+        return self.strategy.select(excluded)
+
+    def list_endpoints(self) -> list[dict[str, Any]]:
+        return list(self._endpoints)
+
+
+class PoolFactory:
+    """工厂：创建端点池。"""
+
+    @staticmethod
+    def create_pool(
+        logical_model_name: str,
+        endpoints: list[dict[str, Any]],
+        strategy_name: str = "weighted_round_robin",
+    ) -> EndpointPool:
+        return EndpointPool(
+            logical_model_name=logical_model_name,
+            endpoints_configs=endpoints,
+            strategy=strategy_name,
+        )
+
+    @staticmethod
+    def create_strategy(
+        name: str,
+        endpoints: list[dict[str, Any]],
+    ) -> SchedulingStrategy:
+        strategy_cls = _STRATEGIES.get(name)
+        if strategy_cls is None:
+            raise ValueError(f"Unknown scheduling strategy: {name}")
+        return strategy_cls(endpoints)

backend/app/ai_provider/llm/stream.py

@@ -0,0 +1,115 @@
+from __future__ import annotations
+
+import json
+from collections import defaultdict
+from typing import Any
+
+from app.ai_provider.types.chat import ChatChunk, ChatResult, TokenUsage
+
+
+class ToolCallAccumulator:
+    """将流式 tool call 分片累积为完整的 tool call。
+
+    处理流式场景中常见的多分片 tool call 参数，
+    按索引拼接部分 JSON 字符串。
+    """
+
+    def __init__(self) -> None:
+        self.content: str = ""
+        self.reasoning: str = ""
+        self._tool_call_slots: dict[int, dict[str, Any]] = defaultdict(
+            lambda: {"index": 0, "id": "", "name": "", "args": ""}
+        )
+        self.usage: TokenUsage | None = None
+
+    def add_chunk(self, chunk: ChatChunk) -> None:
+        """处理一个 ChatChunk，累积 content/reasoning/tool-calls/usage。"""
+        if chunk.delta_content:
+            self.content += chunk.delta_content
+        if chunk.delta_reasoning:
+            self.reasoning += chunk.delta_reasoning
+        if chunk.usage is not None:
+            self.usage = chunk.usage
+        for tc in chunk.tool_call_chunks:
+            idx = tc.get("index", 0)
+            if idx not in self._tool_call_slots:
+                self._tool_call_slots[idx] = {"index": idx, "id": "", "name": "", "args": ""}
+            slot = self._tool_call_slots[idx]
+            # The first chunk for a given index carries id/name; subsequent
+            # arg-only chunks have them as None and should NOT overwrite.
+            if tc.get("id"):
+                slot["id"] = tc["id"]
+            if tc.get("name"):
+                slot["name"] = tc["name"]
+            slot["args"] += tc.get("args", "")
+
+    def drain(self) -> list[dict[str, Any]]:
+        """返回所有已累积的 tool call 并重置内部槽位。"""
+        result: list[dict[str, Any]] = []
+        for idx in sorted(self._tool_call_slots.keys()):
+            slot = self._tool_call_slots[idx]
+            result.append(
+                {
+                    "index": slot["index"],
+                    "id": slot["id"] or f"call_{idx}",
+                    "name": slot["name"],
+                    "args": slot["args"],
+                }
+            )
+        self._tool_call_slots.clear()
+        return result
+
+
+class StreamHandler:
+    """收集流式分片并生成最终的 ChatResult。"""
+
+    def __init__(self) -> None:
+        self._accumulator = ToolCallAccumulator()
+        self._chunks: list[ChatChunk] = []
+
+    def add_chunk(self, chunk: ChatChunk) -> None:
+        """收集一个流式分片。"""
+        self._chunks.append(chunk)
+        self._accumulator.add_chunk(chunk)
+
+    @property
+    def chunks(self) -> list[ChatChunk]:
+        """返回所有已收集分片的副本。"""
+        return list(self._chunks)
+
+    def to_result(self, model_name: str = "") -> ChatResult:
+        """从所有累积分片构建最终的 ChatResult。"""
+        raw_tool_calls = self._accumulator.drain()
+        parsed_calls: list[dict[str, Any]] = []
+        for tc in raw_tool_calls:
+            args_raw = tc.get("args", "{}")
+            try:
+                parsed_args = json.loads(args_raw)
+            except json.JSONDecodeError:
+                parsed_args = {"_raw": args_raw}
+            parsed_calls.append(
+                {
+                    "name": tc["name"],
+                    "args": parsed_args,
+                    "id": tc["id"],
+                }
+            )
+        return ChatResult(
+            content=self._accumulator.content,
+            reasoning=self._accumulator.reasoning,
+            tool_calls=parsed_calls,
+            usage=self._accumulator.usage,
+            model_name=model_name,
+        )
+
+
+class StreamFactory:
+    """流处理器和累积器的工厂。"""
+
+    @staticmethod
+    def create_handler() -> StreamHandler:
+        return StreamHandler()
+
+    @staticmethod
+    def create_accumulator() -> ToolCallAccumulator:
+        return ToolCallAccumulator()

backend/app/ai_provider/manager.py

@@ -0,0 +1,463 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any
+
+from app.ai_provider.config.loader import (
+    load_models_config,
+    load_pricing_config,
+    load_providers_config,
+)
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+from app.ai_provider.core.billing import (
+    BillingFactory,
+    BillingTracker,
+    BudgetController,
+    PricingInfo,
+    PricingRegistry,
+)
+from app.ai_provider.core.registry import ModelRegistry, ProviderRegistry
+from app.ai_provider.core.resilience import CircuitBreaker
+from app.ai_provider.llm.anthropic_format import (
+    AnthropicFormatAdapter,
+    AnthropicFormatAdapterFactory,
+)
+from app.ai_provider.llm.openai_format import OpenAIFormatAdapter, OpenAIFormatAdapterFactory
+from app.ai_provider.llm.stream import StreamHandler
+from app.ai_provider.routing import (
+    CapabilityPermissionController,
+    ModelSelector,
+    MultiModalRouter,
+)
+from app.ai_provider.types.chat import ChatResult, TokenUsage
+from app.ai_provider.types.errors import AIProviderError
+from app.ai_provider.types.messages import (
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    SystemMessage,
+)
+from app.core.config import settings
+
+
+@dataclass
+class _ResolvedEndpoint:
+    """端点到适配器和凭证的解析结果。"""
+
+    adapter: OpenAIFormatAdapter | AnthropicFormatAdapter
+    model: ModelConfig
+    provider: ProviderConfig
+    api_key: str
+    base_url: str | None
+    breaker: CircuitBreaker | None = None
+
+
+class ProviderManager:
+    """所有 AI 提供商操作的统一入口。
+
+    取代旧的 ModelRouter + get_model_router() 模式。
+    组合了注册表、适配器、池、计费、弹性和路由。
+    """
+
+    def __init__(
+        self,
+        model_registry: ModelRegistry,
+        provider_registry: ProviderRegistry,
+        billing_tracker: BillingTracker | None = None,
+        budget_controller: BudgetController | None = None,
+        pricing_registry: PricingRegistry | None = None,
+    ) -> None:
+        self.model_registry = model_registry
+        self.provider_registry = provider_registry
+        self._billing = billing_tracker or BillingFactory.create_tracker()
+        self._budget = budget_controller
+        self._pricing_registry = pricing_registry or PricingRegistry()
+        self._adapter_cache: dict[str, OpenAIFormatAdapter | AnthropicFormatAdapter] = {}
+        self._model_selector = ModelSelector(model_registry)
+        self._multi_modal_router = MultiModalRouter()
+        self._permission_controller = CapabilityPermissionController()
+
+    # ── 模型解析 ──────────────────────────────────────────────
+
+    def resolve_model(self, model_hint: str | None = None) -> str:
+        if model_hint is None:
+            return self.model_registry.get_default_name()
+        return self.model_registry.resolve_name(model_hint)
+
+    def get_model_config(self, name: str) -> ModelConfig:
+        return self.model_registry.get(name)
+
+    def get_provider_config(self, name: str) -> ProviderConfig:
+        return self.provider_registry.get(name)
+
+    # ── 适配器解析 ────────────────────────────────────────────
+
+    def get_adapter(self, model_name: str) -> OpenAIFormatAdapter | AnthropicFormatAdapter:
+        if model_name in self._adapter_cache:
+            return self._adapter_cache[model_name]
+
+        model = self.model_registry.get(model_name)
+        provider = self.provider_registry.get(model.provider)
+
+        if model.format.value == "openai":
+            adapter = OpenAIFormatAdapterFactory.create(provider)
+        else:
+            adapter = AnthropicFormatAdapterFactory.create(provider)
+
+        self._adapter_cache[model_name] = adapter
+        return adapter
+
+    # ── 消息辅助 ───────────────────────────────────────────────
+
+    @staticmethod
+    def to_message_list(
+        system_messages: list[str],
+        history: list[tuple[str, str]],
+    ) -> list[BaseMessage]:
+        messages: list[BaseMessage] = []
+        for msg in system_messages:
+            if msg:
+                messages.append(SystemMessage(content=msg))
+        for role, content in history:
+            if role == "system":
+                messages.append(SystemMessage(content=content))
+            elif role == "user":
+                messages.append(HumanMessage(content=content))
+            elif role == "assistant":
+                messages.append(AIMessage(content=content))
+        return messages
+
+    # ── Embedding ──────────────────────────────────────────────────────
+
+    def create_embedding(self, model_name: str) -> Any:
+        """按模型名创建 Embedding 适配器。
+
+        优先读取 model endpoint 级 base_url/api_key 覆盖；无 endpoint 时
+        回退 provider 级凭证。
+        """
+        from app.ai_provider.embedding.openai_format import OpenAIFormatEmbeddingAdapter
+
+        model = self.model_registry.get(model_name)
+        provider = self.provider_registry.get(model.provider)
+
+        # 尝试从 model endpoint 读取 base_url / api_key 覆盖
+        base_url: str | None = None
+        api_key: str = ""
+        if model.endpoints and len(model.endpoints) > 0:
+            ep = model.endpoints[0]  # 取第一个活跃 endpoint
+            if ep.base_url:
+                base_url = ep.base_url
+            elif ep.base_url_env and hasattr(settings, ep.base_url_env.lower()):
+                base_url = getattr(settings, ep.base_url_env.lower())
+            if ep.api_key:
+                api_key = ep.api_key
+            elif ep.api_key_env and hasattr(settings, ep.api_key_env.lower()):
+                api_key = getattr(settings, ep.api_key_env.lower(), "")
+
+        if not base_url:
+            _, base_url = self._resolve_credentials(provider)
+        if not base_url:
+            base_url = provider.base_url
+        if not api_key:
+            api_key, _ = self._resolve_credentials(provider)
+
+        return OpenAIFormatEmbeddingAdapter(
+            base_url=base_url or "",
+            api_key=api_key or "",
+            model=model.model,
+            request_timeout_seconds=model.timeout_seconds,
+        )
+
+    # ── Reranker ───────────────────────────────────────────────────────
+
+    def create_reranker(self, model_name: str) -> Any:
+        """按模型名创建 Reranker 适配器。"""
+        from app.ai_provider.reranker.cohere_format import CohereFormatRerankerAdapter
+
+        model = self.model_registry.get(model_name)
+        provider = self.provider_registry.get(model.provider)
+        api_key, base_url = self._resolve_credentials(provider)
+        if not base_url:
+            base_url = provider.base_url
+        return CohereFormatRerankerAdapter(
+            base_url=base_url or "",
+            api_key=api_key,
+            model=model.model,
+            request_timeout_seconds=model.timeout_seconds,
+        )
+
+    # ── 对话 ──────────────────────────────────────────────────────────
+
+    def _resolve_endpoint(self, model_name: str) -> _ResolvedEndpoint:
+        """解析模型名→(适配器, 凭证, 熔断器)。
+
+        处理池选择、熔断初始化、凭证回退。
+        """
+        model = self.model_registry.get(model_name)
+        provider = self.provider_registry.get(model.provider)
+        adapter = self.get_adapter(model_name)
+
+        breaker: CircuitBreaker | None = None
+
+        if model.endpoint_pool_enabled and model.endpoints:
+            from app.ai_provider.llm.pool import PoolFactory
+
+            pool = PoolFactory.create_pool(
+                logical_model_name=model_name,
+                endpoints=[ep.model_dump(exclude_none=True) for ep in model.endpoints],
+                strategy_name=model.routing_strategy,
+            )
+            selected = pool.select(set())
+            if selected is not None:
+                api_key = selected.get("api_key") or (
+                    settings.__getattribute__(provider.api_key_env.lower())
+                    if hasattr(settings, provider.api_key_env.lower())
+                    else ""
+                )
+                base_url_env = selected.get("base_url_env") or provider.base_url_env
+                base_url = selected.get("base_url") or (
+                    settings.__getattribute__(base_url_env.lower())
+                    if hasattr(settings, base_url_env.lower())
+                    else None
+                )
+                # 熔断器
+                from app.ai_provider.core.resilience import ResilienceFactory
+
+                breaker = ResilienceFactory.create_circuit_breaker(
+                    name=f"{model_name}@{selected.get('name', 'default')}",
+                    failure_threshold=3,
+                    cooldown_seconds=30,
+                )
+                if not breaker.allow_request():
+                    raise AIProviderError(
+                        message=f"Circuit breaker open for {selected.get('name', 'unknown')}",
+                        code="CIRCUIT_BREAKER_OPEN",
+                        status_code=503,
+                    )
+                return _ResolvedEndpoint(
+                    adapter=adapter,
+                    model=model,
+                    provider=provider,
+                    api_key=api_key,
+                    base_url=base_url,
+                    breaker=breaker,
+                )
+            # 无活跃 endpoint，回退 provider 凭证（无熔断）
+            api_key, base_url = self._resolve_credentials(provider)
+            return _ResolvedEndpoint(
+                adapter=adapter,
+                model=model,
+                provider=provider,
+                api_key=api_key,
+                base_url=base_url,
+            )
+
+        # 无池，直接走 provider 凭证
+        api_key, base_url = self._resolve_credentials(provider)
+        return _ResolvedEndpoint(
+            adapter=adapter,
+            model=model,
+            provider=provider,
+            api_key=api_key,
+            base_url=base_url,
+        )
+
+    async def chat(
+        self,
+        messages: list[BaseMessage],
+        model_hint: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ) -> ChatResult:
+        model_name = self.resolve_model(model_hint)
+        if self._budget and not self._budget.allow_request():
+            raise AIProviderError(
+                message="Budget limit exceeded", code="BUDGET_EXCEEDED", status_code=429
+            )
+
+        ep = self._resolve_endpoint(model_name)
+
+        try:
+            result = await ep.adapter.chat(
+                model=ep.model,
+                messages=messages,
+                api_key=ep.api_key,
+                base_url=ep.base_url,
+                params=params,
+                tools=tools,
+                tool_choice=tool_choice,
+            )
+            if ep.breaker:
+                ep.breaker.record_success()
+        except Exception:
+            if ep.breaker:
+                ep.breaker.record_failure()
+            raise
+
+        self._record_usage(
+            model_name, ep.provider.name, result.usage, self._pricing_registry.get(model_name)
+        )
+        return result
+
+    async def chat_stream(
+        self,
+        messages: list[BaseMessage],
+        model_hint: str | None = None,
+        params: dict[str, Any] | None = None,
+        tools: list[dict[str, Any]] | None = None,
+        tool_choice: str | dict[str, Any] | None = None,
+    ):
+        model_name = self.resolve_model(model_hint)
+        if self._budget and not self._budget.allow_request():
+            raise AIProviderError(
+                message="Budget limit exceeded", code="BUDGET_EXCEEDED", status_code=429
+            )
+
+        ep = self._resolve_endpoint(model_name)
+
+        try:
+            stream = ep.adapter.chat_stream(
+                model=ep.model,
+                messages=messages,
+                api_key=ep.api_key,
+                base_url=ep.base_url,
+                params=params,
+                tools=tools,
+                tool_choice=tool_choice,
+            )
+            handler = StreamHandler()
+            async for chunk in stream:
+                handler.add_chunk(chunk)
+                yield chunk
+
+            if ep.breaker:
+                ep.breaker.record_success()
+        except Exception:
+            if ep.breaker:
+                ep.breaker.record_failure()
+            raise
+
+        result = handler.to_result(model_name=model_name)
+        self._record_usage(
+            model_name, ep.provider.name, result.usage, self._pricing_registry.get(model_name)
+        )
+
+    def _resolve_credentials(self, provider: ProviderConfig) -> tuple[str, str | None]:
+        """从 settings 解析 provider 级别的 API key 和 base URL。"""
+        api_key = (
+            settings.__getattribute__(provider.api_key_env.lower())
+            if hasattr(settings, provider.api_key_env.lower())
+            else ""
+        )
+        base_url = (
+            settings.__getattribute__(provider.base_url_env.lower())
+            if hasattr(settings, provider.base_url_env.lower())
+            else None
+        )
+        return api_key, base_url
+
+    # ── 路由辅助 ───────────────────────────────────────────────
+
+    def select_model_for_context(
+        self,
+        needs_vision: bool = False,
+        needs_thinking: bool = False,
+    ) -> str:
+        capabilities: set[str] = set()
+        if needs_vision:
+            capabilities.add("vision")
+        if needs_thinking:
+            capabilities.add("thinking")
+        model = self._model_selector.select({"capabilities": capabilities})
+        return model.name
+
+    def get_adapter_for_tool_binding(
+        self,
+        model_name: str,
+        tools: list[dict[str, Any]],
+        tool_choice: str | dict[str, Any] | None = None,
+    ):
+        """返回 (adapter, request_body_base) 用于工具绑定。
+
+        为 Agent 运行时保留独立的 bind_tools 步骤。
+        """
+        adapter = self.get_adapter(model_name)
+        body = {"model": self.model_registry.get(model_name).model}
+        adapter.bind_tools(body, tools, tool_choice=tool_choice)
+        return adapter, body
+
+    # ── 用量与计费 ───────────────────────────────────────────────
+
+    def _record_usage(
+        self,
+        model_name: str,
+        provider: str,
+        usage: TokenUsage | None,
+        pricing: PricingInfo | None = None,
+    ) -> None:
+        record = self._billing.record(
+            model_name=model_name,
+            provider=provider,
+            usage=usage,
+            pricing=pricing,
+        )
+        if self._budget and record.cost > 0:
+            self._budget.add_cost_cny(
+                record.cost if record.currency == "CNY" else record.cost * 7.3
+            )
+
+    def get_usage_records(self, **kwargs) -> list:
+        return self._billing.get_records(**kwargs)
+
+    def get_budget_status(self) -> dict[str, bool]:
+        if self._budget:
+            return {"within_daily": self._budget.allow_request()}
+        return {"within_daily": True}
+
+    # ── 生命周期 ─────────────────────────────────────────────────────
+
+    async def close(self) -> None:
+        for adapter in self._adapter_cache.values():
+            await adapter.close()
+
+    async def __aenter__(self) -> ProviderManager:
+        return self
+
+    async def __aexit__(self, *exc_info: object) -> None:
+        await self.close()
+
+
+class ProviderManagerFactory:
+    """工厂：从配置文件创建 ProviderManager。"""
+
+    @staticmethod
+    def create(
+        models_path: str | None = None,
+        providers_path: str | None = None,
+        aliases: dict[str, str] | None = None,
+        daily_budget_cny: float = 0.0,
+    ) -> ProviderManager:
+        from pathlib import Path
+
+        models = load_models_config(Path(models_path) if models_path else None)
+        providers = load_providers_config(Path(providers_path) if providers_path else None)
+        pricing_data = load_pricing_config()
+        from app.ai_provider.core.registry import RegistryFactory
+
+        registries = RegistryFactory.create(
+            models, providers, aliases=aliases, pricing_data=pricing_data
+        )
+        billing = BillingFactory.create_tracker()
+        budget = (
+            BillingFactory.create_budget_controller(daily_budget_cny=daily_budget_cny)
+            if daily_budget_cny > 0
+            else None
+        )
+        return ProviderManager(
+            model_registry=registries.model_registry,
+            provider_registry=registries.provider_registry,
+            billing_tracker=billing,
+            budget_controller=budget,
+            pricing_registry=registries.pricing_registry,
+        )

backend/app/ai_provider/pipeline.py

@@ -0,0 +1,172 @@
+"""配置驱动的 AI 提供商五阶段参数管道。
+
+根据 ProviderConfig.parameter_mappings 在分发前对参数进行
+转换、归一化、过滤和注入。第五阶段 HandlerStep 处理跨参数
+依赖等复杂场景。
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+from app.ai_provider.config.models import ModelConfig, ProviderConfig
+
+
+@dataclass
+class PipelineContext:
+    """管道的输入上下文。"""
+
+    params: dict[str, Any] = field(default_factory=dict)
+    model_config: ModelConfig | None = None
+    provider_config: ProviderConfig | None = None
+    messages: list[dict[str, Any]] | None = None
+    tools: list[dict[str, Any]] | None = None
+
+
+@dataclass
+class PipelineResult:
+    """经过管道处理后的结果。"""
+
+    params: dict[str, Any] = field(default_factory=dict)
+    filtered_params: dict[str, Any] = field(default_factory=dict)
+    messages: list[dict[str, Any]] | None = None
+    tools: list[dict[str, Any]] | None = None
+
+
+class PipelineStep:
+    """管道步骤的基类。"""
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        raise NotImplementedError
+
+
+class NormalizeStep(PipelineStep):
+    """步骤 1：归一化参数范围（夹紧到 min/max）。"""
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        mappings = ctx.provider_config.parameter_mappings if ctx.provider_config else {}
+        for key, value in ctx.params.items():
+            mapping = mappings.get(key)
+            if mapping:
+                if mapping.min is not None:
+                    value = max(mapping.min, value)
+                if mapping.max is not None:
+                    value = min(mapping.max, value)
+                result.params[key] = value
+            else:
+                result.params[key] = value
+
+
+class FilterStep(PipelineStep):
+    """步骤 2：过滤模型/提供商不支持的参数。"""
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        allowed = (
+            set(ctx.provider_config.parameter_mappings.keys())
+            if ctx.provider_config
+            else set(result.params.keys())
+        )
+        filtered = {}
+        for key in list(result.params.keys()):
+            if key not in allowed:
+                filtered[key] = result.params.pop(key)
+        result.filtered_params = filtered
+
+
+class TransformStep(PipelineStep):
+    """步骤 3：转换参数名称和值为提供商所需格式。"""
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        mappings = ctx.provider_config.parameter_mappings if ctx.provider_config else {}
+        remapped: dict[str, Any] = {}
+        for key, value in result.params.items():
+            mapping = mappings.get(key)
+            if mapping:
+                provider_key = mapping.provider_param
+                if mapping.transform == "int":
+                    value = int(value)
+                elif mapping.transform == "str":
+                    value = str(value)
+                elif mapping.transform == "multiply_1000":
+                    value = int(value * 1000)
+                remapped[provider_key] = value
+            else:
+                remapped[key] = value
+        result.params = remapped
+
+
+class InjectStep(PipelineStep):
+    """步骤 4：为缺失参数注入提供商默认值。"""
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        mappings = ctx.provider_config.parameter_mappings if ctx.provider_config else {}
+        for mapping in mappings.values():
+            provider_key = mapping.provider_param
+            if provider_key not in result.params and mapping.default is not None:
+                result.params[provider_key] = mapping.default
+
+
+class HandlerStep(PipelineStep):
+    """步骤 5：执行已注册的参数处理器。
+
+    处理 YAML 映射规则无法表达的跨参数依赖和复杂变换：
+    - Anthropic thinking 参数要求 max_tokens > budget_tokens
+    - 根据模型能力过滤不支持的参数
+    - 结构性参数重组
+    """
+
+    def apply(self, ctx: PipelineContext, result: PipelineResult) -> None:
+        if not ctx.provider_config:
+            return
+        from app.ai_provider.pipeline_handlers import ParameterHandlerRegistry
+
+        registry = ParameterHandlerRegistry
+
+        # 阶段 A：逐参数处理器（来自 ParameterMapping.handler）
+        for key, mapping in ctx.provider_config.parameter_mappings.items():
+            if mapping.handler:
+                handler = registry.get(mapping.handler)
+                handler(ctx, result, key)  # key is the param key
+
+        # 阶段 B：全局处理器（来自 ProviderConfig.parameter_handlers）
+        for handler_name in ctx.provider_config.parameter_handlers:
+            handler = registry.get(handler_name)
+            handler(ctx, result, None)  # global handler: no param_key
+
+
+class ParameterPipeline:
+    """配置驱动的五阶段参数管道。"""
+
+    def __init__(
+        self,
+        steps: list[PipelineStep],
+        provider_config: ProviderConfig | None = None,
+    ) -> None:
+        self._steps = steps
+        self._provider_config = provider_config
+
+    def run(self, ctx: PipelineContext) -> PipelineResult:
+        if ctx.provider_config is None and self._provider_config is not None:
+            ctx.provider_config = self._provider_config
+        result = PipelineResult(params=dict(ctx.params))
+        for step in self._steps:
+            step.apply(ctx, result)
+        return result
+
+
+class PipelineFactory:
+    """工厂：从提供商配置构建管道。"""
+
+    @staticmethod
+    def create(provider_config: ProviderConfig) -> ParameterPipeline:
+        return ParameterPipeline(
+            provider_config=provider_config,
+            steps=[
+                NormalizeStep(),
+                FilterStep(),
+                TransformStep(),
+                InjectStep(),
+                HandlerStep(),
+            ],
+        )

backend/app/ai_provider/pipeline_handlers.py

@@ -0,0 +1,153 @@
+"""参数处理器注册中心与内置 handlers。
+
+处理跨参数依赖、结构性转换等复杂场景——这些无法通过
+YAML ParameterMapping 的 min/max/transform/default 表达。
+
+使用方式（在 providers.yaml 中）：
+```yaml
+parameter_mappings:
+  thinking: { provider_param: thinking, handler: anthropic_thinking }
+
+parameter_handlers:
+  - strip_unsupported_capability_params
+```
+"""
+
+from __future__ import annotations
+
+from collections.abc import Callable
+
+from app.ai_provider.pipeline import PipelineContext, PipelineResult
+
+# Type alias for a parameter handler function.
+# param_key is passed for per-param handlers (from ParameterMapping.handler);
+# for global handlers (from ProviderConfig.parameter_handlers), param_key is None.
+ParameterHandler = Callable[[PipelineContext, PipelineResult, str | None], None]
+
+
+class ParameterHandlerRegistry:
+    """全局参数处理器注册中心。
+
+    使用 register() 装饰器注册 handler，名称字符串即可在 YAML 中引用。
+    """
+
+    _handlers: dict[str, ParameterHandler] = {}
+
+    @classmethod
+    def register(cls, name: str) -> Callable[[ParameterHandler], ParameterHandler]:
+        """装饰器：将函数注册为命名 handler。"""
+
+        def decorator(handler: ParameterHandler) -> ParameterHandler:
+            cls._handlers[name] = handler
+            return handler
+
+        return decorator
+
+    @classmethod
+    def get(cls, name: str) -> ParameterHandler:
+        """按名称获取 handler。未找到时抛出 KeyError。"""
+        if name not in cls._handlers:
+            msg = f"Unknown parameter handler: '{name}'. "
+            msg += f"Available: {', '.join(sorted(cls._handlers))}"
+            raise KeyError(msg)
+        return cls._handlers[name]
+
+    @classmethod
+    def list(cls) -> list[str]:
+        """返回所有已注册的 handler 名称。"""
+        return list(cls._handlers.keys())
+
+
+# ── 内建 Handlers ──────────────────────────────────────────────
+
+
+@ParameterHandlerRegistry.register("anthropic_thinking")
+def handle_anthropic_thinking(
+    _ctx: PipelineContext,
+    result: PipelineResult,
+    _param_key: str | None = None,
+) -> None:
+    """处理 Anthropic thinking 参数的跨参数约束。
+
+    Anthropic API 要求：
+    - max_tokens 必须大于 thinking.budget_tokens
+    - 开启 thinking 时 temperature 必须为 1（不应传此参数）
+    - thinking 参数自身需转换为 {type, budget_tokens} 结构
+    """
+    thinking = result.params.get("thinking")
+    if thinking is None:
+        return
+
+    # 将标量 thinking=True 转换为启用 extended thinking
+    if thinking is True:
+        result.params["thinking"] = {"type": "enabled"}
+
+    # 提取 budget_tokens
+    if isinstance(thinking, dict):
+        budget = thinking.get("budget_tokens", 0)
+        # 确保 max_tokens > budget_tokens
+        max_tokens = result.params.get("max_tokens", 0)
+        if budget > 0 and max_tokens <= budget:
+            result.params["max_tokens"] = budget + 1
+
+    # 开启 thinking 时移除 temperature 参数（Anthropic 静默忽略，
+    # 但显式移除更安全干净）
+    result.params.pop("temperature", None)
+
+
+@ParameterHandlerRegistry.register("validate_max_tokens")
+def validate_max_tokens(
+    ctx: PipelineContext,
+    result: PipelineResult,
+    _param_key: str | None = None,
+) -> None:
+    """校验 max_tokens 不超过模型上限。"""
+    model_config = ctx.model_config
+    if model_config is None:
+        return
+    max_tokens = result.params.get("max_tokens")
+    if max_tokens is None:
+        return
+    limit = model_config.max_output_tokens
+    if limit and max_tokens > limit:
+        result.params["max_tokens"] = limit
+
+
+@ParameterHandlerRegistry.register("validate_temperature")
+def validate_temperature(
+    _ctx: PipelineContext,
+    _result: PipelineResult,
+    _param_key: str | None = None,
+) -> None:
+    """温度参数跨提供商规范校验。
+
+    非 reasoning/thinking 模式下强制温度 1.0 不是必需的规则，
+    OpenAI/DeepSeek 无此要求，此 handler 留作扩展点。
+    """
+    # 预留：可为特定 provider 添加温度校验逻辑
+    pass
+
+
+@ParameterHandlerRegistry.register("strip_unsupported_capability_params")
+def strip_unsupported_capability_params(
+    ctx: PipelineContext,
+    result: PipelineResult,
+    _param_key: str | None = None,
+) -> None:
+    """根据模型能力过滤不支持的参数。
+
+    当模型不支持 vision 时，移除 image_url 等视觉参数。
+    当模型不支持 tool_use 时，移除 tools 相关参数。
+    """
+    model_config = ctx.model_config
+    if model_config is None:
+        return
+
+    caps = model_config.resolved_capabilities()
+
+    if not caps.get("vision", False):
+        result.params.pop("image_url", None)
+        result.params.pop("image", None)
+
+    if not caps.get("thinking", False):
+        result.params.pop("thinking", None)

backend/app/ai_provider/reranker/__init__.py

@@ -0,0 +1,135 @@
+"""重排序服务 — Reranker 适配器外观。
+
+用法::
+
+    from app.ai_provider.reranker import RerankerService
+
+    service = RerankerService(manager)
+    result = await service.rerank("查询", ["文档1", "文档2"])
+"""
+
+from __future__ import annotations
+
+from app.ai_provider.reranker.base import (
+    RerankerProtocol,
+    RerankerServiceError,
+    RerankRequest,
+    RerankResponse,
+    RerankResult,
+)
+from app.ai_provider.types.errors import AIProviderError
+
+
+class RerankerService:
+    """外观类，负责解析 Reranker 模型并委托给 ProviderManager。
+
+    接受 ProviderManager 或实现了以下接口的适配器：
+    - ``.model_registry`` → 具有 ``list_by_capability(capability)`` 方法
+    - ``.create_reranker(name)`` → 返回 RerankerProtocol 实例
+    """
+
+    def __init__(self, manager) -> None:
+        self._manager = manager
+        self._adapter: RerankerProtocol | None = None
+
+    # ── Registry 兼容适配 ─────────────────────────────────────────
+
+    @property
+    def _registry(self):
+        mgr = self._manager
+        if hasattr(mgr, "model_registry"):
+            return mgr.model_registry
+        return mgr
+
+    @property
+    def _factory(self):
+        mgr = self._manager
+        if hasattr(mgr, "create_reranker"):
+            return mgr
+        return None
+
+    # ── Reranker ───────────────────────────────────────────────────
+
+    @property
+    def adapter(self) -> RerankerProtocol:
+        """解析并缓存 Reranker 适配器。"""
+        if self._adapter is None:
+            self._adapter = self._resolve()
+        return self._adapter
+
+    async def rerank(
+        self,
+        query: str,
+        documents: list[str],
+        model_hint: str | None = None,
+        top_n: int | None = None,
+    ) -> RerankResponse:
+        """快捷方法：构造请求并调用 Reranker 适配器。"""
+        model = self._resolve_model_name(model_hint)
+        request = RerankRequest(
+            query=query,
+            documents=documents,
+            model=model,
+            top_n=top_n,
+        )
+        return await self.adapter.rerank(request)
+
+    # ── 解析 ───────────────────────────────────────────────────────
+
+    def _resolve(self) -> RerankerProtocol:
+        """查找第一个活跃的 Reranker 模型并通过工厂创建。"""
+        models = self._list_capability_models("reranker")
+        if not models:
+            raise AIProviderError(
+                status_code=503,
+                code="reranker_no_model",
+                message="No reranker model configured in the model registry.",
+            )
+        factory = self._factory
+        if factory is None:
+            raise AIProviderError(
+                status_code=501,
+                code="reranker_no_factory",
+                message="Reranker adapter factory not available (provider manager missing create_reranker).",
+            )
+        return factory.create_reranker(models[0].name)
+
+    def _resolve_model_name(self, model_hint: str | None) -> str:
+        models = self._list_capability_models("reranker")
+        if model_hint:
+            return model_hint
+        if models:
+            return models[0].name
+        return ""
+
+    def _list_capability_models(self, tag: str):
+        reg = self._registry
+        if hasattr(reg, "list_capability_models"):
+            return reg.list_capability_models(tag)
+        if hasattr(reg, "list_by_capability"):
+            return reg.list_by_capability(tag)
+        return []
+
+    # ── 生命周期 ────────────────────────────────────────────────────
+
+    async def close(self) -> None:
+        if self._adapter is not None:
+            close = getattr(self._adapter, "close", None)
+            if close is not None:
+                await close()
+
+    async def __aenter__(self) -> RerankerService:
+        return self
+
+    async def __aexit__(self, *exc_info: object) -> None:
+        await self.close()
+
+
+__all__ = [
+    "RerankerProtocol",
+    "RerankRequest",
+    "RerankResponse",
+    "RerankResult",
+    "RerankerService",
+    "RerankerServiceError",
+]

backend/app/ai_provider/reranker/base.py

@@ -0,0 +1,147 @@
+"""重排序服务类型 — 请求/响应模型和协议定义。
+
+Reranker 适配器通过 HTTP 调用重排序端点，经由 ``RerankerService``
+或直接从 ``ProviderManager`` 消费。
+
+用法::
+
+    service = RerankerService(manager)
+    result = await service.rerank("查询", ["文档1", "文档2"])
+
+    # 或通过工厂直接调用:
+    adapter = manager.create_reranker("rerank-model")
+    result = await adapter.rerank(RerankRequest(query="...", documents=["..."]))
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Protocol, runtime_checkable
+
+from app.ai_provider.types.errors import AIProviderError
+
+if TYPE_CHECKING:
+    from app.ai_provider.config.models import ModelConfig, ModelEndpointConfig
+
+
+class RerankerServiceError(AIProviderError):
+    """Reranker API 调用失败的基础错误。"""
+
+
+# ── 请求 / 响应 ────────────────────────────────────────────────────────
+
+
+@dataclass
+class RerankRequest:
+    """重排序请求。
+
+    属性:
+        query: 查询文本。
+        documents: 待重排序的文档列表。
+        model: 模型标识符。
+        top_n: 返回的最相关文档数量（nil 表示全部）。
+        max_chunks_per_doc: 每个文档最多切分为多少块。
+        return_documents: 返回结果中是否包含文档文本。
+    """
+
+    query: str
+    documents: list[str]
+    model: str = ""
+    top_n: int | None = None
+    max_chunks_per_doc: int | None = None
+    return_documents: bool = False
+
+
+@dataclass
+class RerankResult:
+    """单条重排序结果。"""
+
+    index: int
+    relevance_score: float
+    text: str | None = None
+
+
+@dataclass
+class RerankResponse:
+    """重排序 API 的完整响应。"""
+
+    results: list[RerankResult]
+    model: str = ""
+    usage: dict[str, int] | None = None
+
+
+# ── Protocol ────────────────────────────────────────────────────────────
+
+
+@runtime_checkable
+class RerankerProtocol(Protocol):
+    """Reranker 适配器的协议。"""
+
+    async def rerank(self, request: RerankRequest) -> RerankResponse:
+        """对文档进行重排序。
+
+        异常:
+            RerankerServiceError: API 调用失败或响应异常时抛出。
+        """
+        ...
+
+    async def close(self) -> None:
+        """释放适配器持有的 HTTP 连接。"""
+        ...
+
+
+# ── 共享工厂基类 ──────────────────────────────────────────────────────
+
+
+class RerankerAdapterBase:
+    """Reranker 适配器基类，提供共享的工厂方法。
+
+    子类应在 ``__init__`` 中接受 ``base_url``、``api_key``、``model``、
+    ``request_timeout_seconds`` 参数。
+    """
+
+    _adapter_type: str = "reranker"
+    _default_timeout: int = 60
+
+    @classmethod
+    def from_endpoint(
+        cls,
+        endpoint: ModelEndpointConfig,
+        *,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从已解析的端点配置构建适配器。"""
+        base_url = endpoint.base_url
+        api_key = endpoint.api_key
+        if not base_url:
+            raise RerankerServiceError(
+                status_code=500,
+                code="reranker_endpoint_invalid",
+                message="Reranker endpoint has no resolved base_url.",
+                details={"endpoint": endpoint.name},
+            )
+        return cls(
+            base_url=base_url,
+            api_key=api_key,
+            model=endpoint.model,
+            request_timeout_seconds=timeout_seconds
+            or endpoint.request_timeout_seconds
+            or cls._default_timeout,
+        )
+
+    @classmethod
+    def from_model_config(
+        cls,
+        config: ModelConfig,
+        *,
+        timeout_seconds: int | None = None,
+    ) -> Any:
+        """从逻辑模型配置构建适配器（使用第一个活跃端点）。"""
+        for ep in config.endpoints:
+            if ep.status == "active":
+                return cls.from_endpoint(ep, timeout_seconds=timeout_seconds)
+        raise RerankerServiceError(
+            status_code=500,
+            code="reranker_no_endpoint",
+            message=f"Reranker model '{config.name}' has no active endpoint.",
+        )

backend/app/ai_provider/reranker/cohere_format.py

@@ -0,0 +1,186 @@
+"""Cohere 兼容格式的 Reranker 适配器 — ``POST /v1/rerank``。
+
+覆盖 Cohere、mixedbread、Jina AI 等采用 Cohere 兼容重排序端点的提供商。
+
+请求::
+
+    POST {base_url}/v1/rerank
+    Authorization: Bearer {api_key}
+    Content-Type: application/json
+
+    {
+        "model": "rerank-model",
+        "query": "查询文本",
+        "documents": ["文档1", "文档2"],
+        "top_n": 3,
+        "return_documents": false
+    }
+
+响应::
+
+    {
+        "results": [
+            {"index": 0, "relevance_score": 0.99, "document": {"text": "文档..."}},
+            {"index": 1, "relevance_score": 0.85, "document": {"text": "文档..."}}
+        ],
+        "meta": {"billed_units": {"search_units": 2}}
+    }
+
+另见:
+
+    - Cohere Rerank API: https://docs.cohere.com/reference/rerank
+    - Jina Reranker: https://api.jina.ai/redoc#tag/rerank
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+
+from app.ai_provider.reranker.base import (
+    RerankerAdapterBase,
+    RerankerProtocol,
+    RerankerServiceError,
+    RerankRequest,
+    RerankResponse,
+    RerankResult,
+)
+from app.core.logging import logger
+
+
+class CohereFormatRerankerAdapter(RerankerAdapterBase, RerankerProtocol):
+    """Cohere 兼容重排序适配器，覆盖多数重排序服务提供商。"""
+
+    _adapter_type = "reranker"
+    _default_timeout = 60
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str,
+        model: str = "rerank-model",
+        request_timeout_seconds: int = 60,
+    ) -> None:
+        self._base_url = base_url.rstrip("/")
+        self._api_key = api_key
+        self._model = model
+        self._timeout = request_timeout_seconds
+        self._client: httpx.AsyncClient | None = None
+
+    # ── 客户端 ───────────────────────────────────────────────────────────
+
+    @property
+    def _http(self) -> httpx.AsyncClient:
+        if self._client is None or self._client.is_closed:
+            self._client = httpx.AsyncClient(timeout=httpx.Timeout(self._timeout))
+        return self._client
+
+    async def close(self) -> None:
+        if self._client is not None and not self._client.is_closed:
+            await self._client.aclose()
+
+    # ── RerankerProtocol ────────────────────────────────────────────────
+
+    async def rerank(self, request: RerankRequest) -> RerankResponse:
+        """通过 ``POST /v1/rerank`` 对文档进行重排序。"""
+        url = f"{self._base_url}/v1/rerank"
+
+        payload: dict[str, Any] = {
+            "model": request.model or self._model,
+            "query": request.query,
+            "documents": request.documents,
+            "return_documents": request.return_documents,
+        }
+        if request.top_n is not None:
+            payload["top_n"] = request.top_n
+        if request.max_chunks_per_doc is not None:
+            payload["max_chunks_per_doc"] = request.max_chunks_per_doc
+
+        headers = {
+            "Authorization": f"Bearer {self._api_key}",
+            "Content-Type": "application/json",
+        }
+
+        logger.info(
+            "reranker.request",
+            model=payload["model"],
+            query_length=len(request.query),
+            document_count=len(request.documents),
+            top_n=request.top_n,
+            url=url,
+        )
+
+        try:
+            response = await self._http.post(url, json=payload, headers=headers)
+        except httpx.TimeoutException as exc:
+            raise RerankerServiceError(
+                status_code=504,
+                code="reranker_timeout",
+                message="Reranker request timed out.",
+            ) from exc
+        except httpx.RequestError as exc:
+            raise RerankerServiceError(
+                status_code=503,
+                code="reranker_connection_error",
+                message=f"Reranker connection error: {exc}",
+            ) from exc
+
+        if response.status_code != 200:
+            body = response.text[:500]
+            raise RerankerServiceError(
+                status_code=response.status_code,
+                code="reranker_api_error",
+                message=f"Reranker API returned {response.status_code}: {body}",
+            )
+
+        result = self._parse_response(response.json())
+
+        logger.info(
+            "reranker.success",
+            model=payload["model"],
+            total_results=len(result.results),
+        )
+        return result
+
+    # ── 辅助方法 ──────────────────────────────────────────────────────────
+
+    @staticmethod
+    def _parse_response(body: dict) -> RerankResponse:
+        """从 Cohere 格式的重排序响应中提取结果。"""
+        try:
+            raw_results = body.get("results", [])
+            results = []
+            for item in raw_results:
+                results.append(
+                    RerankResult(
+                        index=item.get("index", 0),
+                        relevance_score=float(item.get("relevance_score", 0.0)),
+                        text=item.get("document", {}).get("text")
+                        if isinstance(item.get("document"), dict)
+                        else None,
+                    )
+                )
+            # 按相关性分数降序排列
+            results.sort(key=lambda r: r.relevance_score, reverse=True)
+
+            # 提取用量信息（不同提供商格式各异）
+            usage: dict[str, int] | None = None
+            meta = body.get("meta")
+            if isinstance(meta, dict):
+                billed = meta.get("billed_units")
+                if isinstance(billed, dict):
+                    usage = {k: int(v) for k, v in billed.items() if isinstance(v, (int, float))}
+
+            return RerankResponse(
+                results=results,
+                model=body.get("model") or body.get("id", ""),
+                usage=usage,
+            )
+        except Exception as exc:
+            raise RerankerServiceError(
+                status_code=500,
+                code="reranker_response_parse_error",
+                message=f"Failed to parse reranker response: {exc}",
+            ) from exc

backend/app/ai_provider/routing/__init__.py

@@ -0,0 +1,14 @@
+from app.ai_provider.routing.multimodal import MultiModalDecision, MultiModalRouter
+from app.ai_provider.routing.permissions import (
+    CapabilityPermissionController,
+    PermissionRule,
+)
+from app.ai_provider.routing.selector import ModelSelector
+
+__all__ = [
+    "MultiModalDecision",
+    "MultiModalRouter",
+    "ModelSelector",
+    "PermissionRule",
+    "CapabilityPermissionController",
+]

backend/app/ai_provider/routing/multimodal.py

@@ -0,0 +1,81 @@
+from __future__ import annotations
+
+from enum import StrEnum
+from typing import Any
+
+
+class MultiModalDecision(StrEnum):
+    """基于消息内容分析的选路决策。
+
+    每个值代表所选模型必须满足的一项能力需求。
+    PLAIN_TEXT 表示不需要特殊能力。
+    """
+
+    PLAIN_TEXT = "plain_text"
+    VISION = "vision"
+    THINKING = "thinking"
+    TOOL_USE = "tool_use"
+    STRUCTURED_OUTPUT = "structured_output"
+
+
+class MultiModalRouter:
+    """分析消息列表以确定所需的模型能力。
+
+    用法::
+
+        messages = [{"role": "user", "content": "Hello"}]
+        decisions = MultiModalRouter.decide_from_messages(messages)
+        # -> {MultiModalDecision.PLAIN_TEXT}
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "What's in this image?"},
+                    {"type": "image_url", "image_url": {"url": "..."}},
+                ],
+            },
+        ]
+        decisions = MultiModalRouter.decide_from_messages(messages)
+        # -> {MultiModalDecision.VISION}
+    """
+
+    @staticmethod
+    def decide_from_messages(messages: list[dict[str, Any]]) -> set[MultiModalDecision]:
+        """分析消息并返回所需能力的集合。
+
+        参数:
+            messages: 消息字典列表，每个字典至少包含 ``role`` 和 ``content`` 键（兼容 OpenAI 格式）。
+
+        返回:
+            :class:`MultiModalDecision` 值的集合。如果未检测到特殊能力，
+            返回 ``{PLAIN_TEXT}``。
+        """
+        if not messages:
+            return {MultiModalDecision.PLAIN_TEXT}
+
+        decisions: set[MultiModalDecision] = set()
+
+        for msg in messages:
+            role = msg.get("role", "")
+            content = msg.get("content", "")
+
+            # --- VISION: content is a list of blocks with image type ---
+            if isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict):
+                        block_type = block.get("type", "")
+                        if block_type in ("image_url", "image"):
+                            decisions.add(MultiModalDecision.VISION)
+
+            # --- TOOL_USE: assistant sent tool_calls, or message is tool result ---
+            if msg.get("tool_calls"):
+                decisions.add(MultiModalDecision.TOOL_USE)
+            if role == "tool":
+                decisions.add(MultiModalDecision.TOOL_USE)
+
+            # --- THINKING: assistant included reasoning ---
+            if msg.get("reasoning"):
+                decisions.add(MultiModalDecision.THINKING)
+
+        return decisions if decisions else {MultiModalDecision.PLAIN_TEXT}

backend/app/ai_provider/routing/permissions.py

@@ -0,0 +1,100 @@
+from __future__ import annotations
+
+import fnmatch
+from typing import Any
+
+
+class PermissionRule:
+    """模型能力访问控制的单条权限规则。
+
+    规则使用 ``fnmatch`` 风格的通配符模式匹配模型名称。
+
+    参数:
+        model_pattern: ``fnmatch`` 模式，用于匹配模型名（如 ``"deepseek-*"``）。
+        capability: 此规则管控的能力（如 ``"vision"``）。
+        allowed: 能力是否允许（``True`` 允许，``False`` 拒绝）。
+
+    示例::
+
+        # 拒绝 "basic-*" 模型上的 vision 能力
+        PermissionRule(model_pattern="basic-*", capability="vision", allowed=False)
+
+        # 允许所有模型的 thinking 能力
+        PermissionRule(model_pattern="*", capability="thinking", allowed=True)
+    """
+
+    def __init__(
+        self,
+        model_pattern: str,
+        capability: str,
+        allowed: bool = True,
+    ) -> None:
+        self.model_pattern = model_pattern
+        self.capability = capability
+        self.allowed = allowed
+
+    def match(self, model_name: str) -> bool:
+        """检查此规则是否适用于给定的模型名。"""
+        return fnmatch.fnmatch(model_name, self.model_pattern)
+
+    def __repr__(self) -> str:
+        verb = "ALLOW" if self.allowed else "DENY"
+        return f"PermissionRule({verb} {self.capability} on {self.model_pattern!r})"
+
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, PermissionRule):
+            return NotImplemented
+        return (
+            self.model_pattern == other.model_pattern
+            and self.capability == other.capability
+            and self.allowed == other.allowed
+        )
+
+    def __hash__(self) -> int:
+        return hash((self.model_pattern, self.capability, self.allowed))
+
+
+class CapabilityPermissionController:
+    """控制哪些模型允许哪些能力。
+
+    按顺序评估 :class:`PermissionRule` 列表。
+    **最后匹配的规则** 胜出（最具体的规则应放在较宽泛的规则之后）。
+    如果没有规则匹配某个模型/能力对，该能力**默认允许**。
+
+    用法::
+
+        controller = CapabilityPermissionController([
+            PermissionRule(model_pattern="*", capability="vision", allowed=False),
+            PermissionRule(model_pattern="vision-*", capability="vision", allowed=True),
+        ])
+
+        controller.check("fast-model", "vision")  # False
+        controller.check("vision-model", "vision")  # True
+    """
+
+    def __init__(self, rules: list[PermissionRule] | None = None) -> None:
+        self._rules = list(rules) if rules else []
+
+    def check(self, model_name: str, capability: str) -> bool:
+        """检查 *capability* 是否在 *model_name* 上被允许。
+
+        返回 ``True`` 表示允许，``False`` 表示拒绝。
+        """
+        result: bool | None = None
+        for rule in self._rules:
+            if rule.capability == capability and rule.match(model_name):
+                result = rule.allowed
+        # Default: allow if no rule matched
+        return result if result is not None else True
+
+    def is_allowed(self, model_name: str, capability: str) -> bool:
+        """:meth:`check` 的别名。"""
+        return self.check(model_name, capability)
+
+    def filter_capabilities(
+        self,
+        model_name: str,
+        capabilities: set[str],
+    ) -> set[str]:
+        """返回 *capabilities* 中在 *model_name* 上允许的子集。"""
+        return {c for c in capabilities if self.check(model_name, c)}

backend/app/ai_provider/routing/selector.py

@@ -0,0 +1,111 @@
+from __future__ import annotations
+
+from typing import Any
+
+from app.ai_provider.config.models import ModelConfig
+from app.ai_provider.core.registry import ModelRegistry
+from app.ai_provider.routing.multimodal import MultiModalDecision
+from app.ai_provider.types.errors import AIProviderError
+
+_SELECTOR_CAPABILITY_MAP: dict[MultiModalDecision, str] = {
+    MultiModalDecision.VISION: "vision",
+    MultiModalDecision.THINKING: "thinking",
+    MultiModalDecision.TOOL_USE: "tool_use",
+    MultiModalDecision.STRUCTURED_OUTPUT: "structured_output",
+    MultiModalDecision.PLAIN_TEXT: "chat",
+}
+
+
+class ModelSelector:
+    """为给定上下文选择最佳模型。
+
+    用法::
+
+        selector = ModelSelector(registry)
+        model = selector.select({"capabilities": {"vision", "thinking"}})
+        model = selector.select({"preferred": "fast-model"})
+        model = selector.select_from_decisions({MultiModalDecision.VISION})
+    """
+
+    def __init__(self, registry: ModelRegistry) -> None:
+        self._registry = registry
+
+    def select(self, context: dict[str, Any]) -> ModelConfig:
+        """根据给定的上下文选择模型。
+
+        上下文键:
+
+        * ``capabilities`` (``set[str]``, 可选) — 必需的能力。
+        * ``preferred`` (``str``, 可选) — 偏好的模型名或别名。
+        * ``avoid`` (``set[str]``, 可选) — 要排除的模型名。
+
+        如果给了偏好模型但不能满足所有必需的能力，此方法会回退到
+        能满足要求的模型。
+        """
+        capabilities: set[str] = set(context.get("capabilities", set()))
+        preferred: str | None = context.get("preferred")
+        avoid: set[str] = set(context.get("avoid", set()))
+
+        # If preferred is given, resolve it and check capabilities
+        if preferred is not None:
+            model = self._registry.resolve(preferred)
+            if (
+                not capabilities or self._model_satisfies_all(model, capabilities)
+            ) and model.name not in avoid:
+                return model
+
+        # Find models that satisfy all required capabilities
+        if capabilities:
+            return self._select_by_capabilities(capabilities, avoid)
+
+        # Fall back to default
+        return self._registry.resolve()
+
+    def select_from_decisions(
+        self,
+        decisions: set[MultiModalDecision],
+    ) -> ModelConfig:
+        """基于 :class:`MultiModalDecision` 值选择模型。
+
+        将决策翻译为能力字符串并委托给 :meth:`select`。
+        """
+        capabilities: set[str] = set()
+        for d in decisions:
+            cap = _SELECTOR_CAPABILITY_MAP.get(d)
+            if cap and cap != "chat":
+                capabilities.add(cap)
+        return self.select({"capabilities": capabilities})
+
+    # ------------------------------------------------------------------
+
+    def _select_by_capabilities(
+        self,
+        capabilities: set[str],
+        avoid: set[str],
+    ) -> ModelConfig:
+        """找到支持所有必需能力的模型。"""
+        # Narrow down by each capability (ModelConfig is unhashable, use lists)
+        candidates: list[ModelConfig] = list(self._registry.list_all())
+
+        for cap in capabilities:
+            cap_models = list(self._registry.list_by_capability(cap))
+            cap_names = {m.name for m in cap_models}
+            candidates = [m for m in candidates if m.name in cap_names]
+
+        # Remove avoided models
+        candidates = [m for m in candidates if m.name not in avoid]
+
+        if not candidates:
+            raise AIProviderError(
+                message=f"No active model supports all capabilities: {capabilities}",
+                code="CAPABILITY_NOT_FOUND",
+                status_code=404,
+            )
+
+        # Prefer higher-weight models (higher = better)
+        return max(candidates, key=lambda m: m.weight)
+
+    @staticmethod
+    def _model_satisfies_all(model: ModelConfig, capabilities: set[str]) -> bool:
+        caps = model.resolved_capabilities()
+        return all(caps.get(cap, False) for cap in capabilities)

backend/app/ai_provider/types/__init__.py

@@ -0,0 +1,21 @@
+from app.ai_provider.types.chat import ChatChunk, ChatResult, TokenUsage
+from app.ai_provider.types.errors import AIProviderError
+from app.ai_provider.types.messages import (
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    SystemMessage,
+    ToolMessage,
+)
+
+__all__ = [
+    "AIMessage",
+    "BaseMessage",
+    "HumanMessage",
+    "SystemMessage",
+    "ToolMessage",
+    "ChatChunk",
+    "ChatResult",
+    "TokenUsage",
+    "AIProviderError",
+]

backend/app/ai_provider/types/chat.py

@@ -0,0 +1,41 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class TokenUsage:
+    prompt_tokens: int = 0
+    completion_tokens: int = 0
+    total_tokens: int = 0
+    prompt_tokens_cached: int = 0  # 缓存命中的 prompt token 数（按缓存费率计费）
+
+    def __add__(self, other: TokenUsage) -> TokenUsage:
+        return TokenUsage(
+            prompt_tokens=self.prompt_tokens + other.prompt_tokens,
+            completion_tokens=self.completion_tokens + other.completion_tokens,
+            total_tokens=self.total_tokens + other.total_tokens,
+            prompt_tokens_cached=self.prompt_tokens_cached + other.prompt_tokens_cached,
+        )
+
+
+@dataclass
+class ChatChunk:
+    delta_content: str = ""
+    delta_reasoning: str = ""
+    tool_call_chunks: list[dict[str, Any]] = field(default_factory=list)
+    usage: TokenUsage | None = None
+    finish_reason: str | None = None
+    content_block_index: int | None = None
+    content_block_start: dict[str, Any] | None = None
+    content_block_delta: dict[str, Any] | None = None
+
+
+@dataclass
+class ChatResult:
+    content: str = ""
+    reasoning: str = ""
+    tool_calls: list[dict[str, Any]] = field(default_factory=list)
+    usage: TokenUsage | None = None
+    model_name: str = ""

backend/app/ai_provider/types/errors.py

@@ -0,0 +1,33 @@
+from __future__ import annotations
+
+
+class AIProviderError(Exception):
+    def __init__(
+        self,
+        message: str,
+        code: str = "UNKNOWN",
+        status_code: int = 500,
+        provider: str | None = None,
+        original: Exception | None = None,
+    ) -> None:
+        self.message = message
+        self.code = code
+        self.status_code = status_code
+        self.provider = provider
+        self.original = original
+        super().__init__(message)
+
+    @classmethod
+    def from_provider(
+        cls,
+        message: str,
+        code: str = "PROVIDER_ERROR",
+        provider: str | None = None,
+        original: Exception | None = None,
+    ) -> AIProviderError:
+        return cls(
+            message=message, code=code, status_code=502, provider=provider, original=original
+        )
+
+    def __str__(self) -> str:
+        return self.message

backend/app/ai_provider/types/messages.py

@@ -0,0 +1,81 @@
+from __future__ import annotations
+
+from typing import Any, Literal
+
+Role = Literal["system", "user", "assistant", "tool"]
+
+
+class BaseMessage:
+    role: Role
+    content: str
+
+    def __init__(self, *, content: str, role: Role) -> None:
+        self.content = content
+        self.role = role
+
+    def to_dict(self) -> dict[str, Any]:
+        return {"role": self.role, "content": self.content}
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> BaseMessage:
+        role = d["role"]
+        content = d.get("content", "")
+        if role == "system":
+            return SystemMessage(content=content)
+        if role == "user":
+            return HumanMessage(content=content)
+        if role == "assistant":
+            return AIMessage(
+                content=content,
+                tool_calls=d.get("tool_calls"),
+                reasoning=d.get("reasoning"),
+                raw_content_blocks=d.get("raw_content_blocks"),
+            )
+        if role == "tool":
+            return ToolMessage(content=content, tool_call_id=d.get("tool_call_id", ""))
+        raise ValueError(f"Unknown role: {role}")
+
+
+class SystemMessage(BaseMessage):
+    def __init__(self, content: str) -> None:
+        super().__init__(content=content, role="system")
+
+
+class HumanMessage(BaseMessage):
+    def __init__(self, content: str) -> None:
+        super().__init__(content=content, role="user")
+
+
+class AIMessage(BaseMessage):
+    def __init__(
+        self,
+        content: str,
+        tool_calls: list[dict[str, Any]] | None = None,
+        reasoning: str | None = None,
+        raw_content_blocks: list[dict[str, Any]] | None = None,
+    ) -> None:
+        super().__init__(content=content, role="assistant")
+        self.tool_calls = tool_calls or []
+        self.reasoning = reasoning or ""
+        self.raw_content_blocks = raw_content_blocks or []
+
+    def to_dict(self) -> dict[str, Any]:
+        d = super().to_dict()
+        if self.tool_calls:
+            d["tool_calls"] = self.tool_calls
+        if self.reasoning:
+            d["reasoning"] = self.reasoning
+        if self.raw_content_blocks:
+            d["raw_content_blocks"] = self.raw_content_blocks
+        return d
+
+
+class ToolMessage(BaseMessage):
+    def __init__(self, content: str, tool_call_id: str) -> None:
+        super().__init__(content=content, role="tool")
+        self.tool_call_id = tool_call_id
+
+    def to_dict(self) -> dict[str, Any]:
+        d = super().to_dict()
+        d["tool_call_id"] = self.tool_call_id
+        return d

backend/app/api/router.py

@@ -4,36 +4,31 @@ from fastapi import APIRouter
 
 from app.api.v1.endpoints import (
     admin,
+    audio,
     auth,
+    avatar,
     character_import,
     characters,
-
+    chat,
+    drive,
     events,
+    evolution,
+    extraction,
+    goals,
     health,
     imports,
-    embryo_drafts,
-    jingsheng_characters,
-    kernel_runs,
     lorebooks,
-    me,
-    baigong,
-    hetu,
-    soul,
-    tianzai,
-    kouxin,
-    tiangong,
-    xingyi,
-    yuanqi,
-    mirror_trees,
     mcp,
-
+    memory,
+    personality,
     runs,
     safety,
     sandbox_files,
     settings,
+    skills,
+    time,
     tools,
-
+    world,
-    xirang,
 )
 
 api_router = APIRouter()
@@ -41,29 +36,25 @@ api_router.include_router(health.router)
 api_router.include_router(auth.router)
 api_router.include_router(characters.router)
 api_router.include_router(character_import.router)
+api_router.include_router(chat.router)
 api_router.include_router(runs.router)
-api_router.include_router(kernel_runs.router)
+api_router.include_router(memory.router)
-api_router.include_router(me.router)
-api_router.include_router(hetu.world_router)
-api_router.include_router(soul.soul_router)
-api_router.include_router(tiangong.task_router)
-api_router.include_router(kouxin.knock_router)
-api_router.include_router(tianzai.device_router)
-api_router.include_router(xingyi.form_router)
-api_router.include_router(yuanqi.cov_router)
-for _baigong_r in baigong.routers:
-    api_router.include_router(_baigong_r)
-api_router.include_router(embryo_drafts.router)
-api_router.include_router(jingsheng_characters.router)
-api_router.include_router(mirror_trees.router)
-api_router.include_router(xirang.router)
-api_router.include_router(mirror_trees.node_router)
 api_router.include_router(lorebooks.router)
+api_router.include_router(personality.router)
 api_router.include_router(tools.router)
+api_router.include_router(skills.router)
 api_router.include_router(mcp.router)
 api_router.include_router(safety.router)
 api_router.include_router(sandbox_files.router)
 api_router.include_router(settings.router)
+api_router.include_router(world.router)
 api_router.include_router(imports.router)
+api_router.include_router(evolution.router)
+api_router.include_router(drive.router)
 api_router.include_router(events.router)
+api_router.include_router(extraction.router)
+api_router.include_router(goals.router)
 api_router.include_router(admin.router)
+api_router.include_router(audio.router)
+api_router.include_router(avatar.router)
+api_router.include_router(time.router)

backend/app/api/v1/deps.py

@@ -1,6 +1,6 @@
 """API 层依赖注入。
 
-从 ``app.state`` 取 lifespan 装配的共享运行时（乾坤沙箱客户端 / EventStore）。
+从 ``app.state`` 取 lifespan 装配的共享运行时（ToolRuntime / ConfirmationStore / EventStore）。
 CRUD 类路由直接调用 ``services`` 函数（函数内部自管 ``AsyncSessionLocal``），不在此注入 session。
 """
 
@@ -11,10 +11,12 @@ import hmac
 from fastapi import Depends, HTTPException, Request
 from sqlalchemy.ext.asyncio import AsyncSession
 
+from app.application.agent.confirmation import ConfirmationRegistry
+from app.application.tool_runtime.runtime import ToolRuntime
 from app.core.config import settings
 from app.db.session import get_session
-from app.integrations.sandbox.client import SandboxClient
 from app.modules.runtime.events import EventStore
+from app.modules.safety.confirmation import ConfirmationStore
 from app.schemas.auth import CurrentUser as CurrentUserSchema
 from app.services.auth import decode_token, get_user_by_id, get_user_permissions
 
@@ -26,11 +28,30 @@ def _unavailable(message: str) -> HTTPException:
     )
 
 
-def get_sandbox_client(request: Request) -> SandboxClient:
+def get_tool_runtime(request: Request) -> ToolRuntime:
-    sandbox: SandboxClient | None = getattr(request.app.state, "baigong_sandbox", None)
+    runtime: ToolRuntime | None = getattr(request.app.state, "tool_runtime", None)
-    if sandbox is None:
+    if runtime is None:
-        raise _unavailable("乾坤沙箱未就绪（SANDBOX 未配置或未启动）")
+        raise _unavailable("工具运行时未就绪（沙箱未配置或未启动）")
-    return sandbox
+    return runtime
+
+
+def get_optional_tool_runtime(request: Request) -> ToolRuntime | None:
+    """宽松版：tool_runtime 未就绪时返回 None（不抛 503），供聚合视图降级呈现。"""
+    return getattr(request.app.state, "tool_runtime", None)
+
+
+def get_confirmation_store(request: Request) -> ConfirmationStore:
+    store = getattr(request.app.state, "confirmation_store", None)
+    if store is None:
+        raise _unavailable("确认存储未就绪")
+    return store
+
+
+def get_confirmation_registry(request: Request) -> ConfirmationRegistry:
+    registry: ConfirmationRegistry = getattr(request.app.state, "confirmation_registry", None)
+    if registry is None:
+        raise _unavailable("确认注册表未就绪")
+    return registry
 
 
 def get_event_store(request: Request) -> EventStore:

backend/app/api/v1/endpoints/admin.py

@@ -4,7 +4,7 @@
 + 五组治理对象 CRUD（§19.4）。治理写操作由 service 层记审计并入起居注。
 
 路由直接调用 ``services`` 函数（函数内部自管 ``AsyncSessionLocal``），不持有 session；
-聚合视图自持查询（百工域常驻），无注入运行时。
+``ToolRuntime`` / ``ConfirmationStore`` 等运行时对象经 ``deps`` 从 ``app.state`` 注入。
 """
 
 import json
@@ -13,29 +13,49 @@ from fastapi import APIRouter, Depends, Query
 from pydantic import BaseModel
 
 from app.api.v1.deps import (
+    get_confirmation_store,
     get_current_user,
+    get_optional_tool_runtime,
     require_admin,
 )
+from app.application.tool_runtime.runtime import ToolRuntime
 from app.models.runtime import Event
+from app.modules.safety.confirmation import ConfirmationStore
+from app.schemas.admin import (
+    AdminCreateUserRequest,
+    AdminUpdateUserRequest,
+    AdminUserResponse,
+    AgentRosterResponse,
+    AuditEntry,
+    CreateAgentRequest,
+    CreateGoalRequest,
+    CreatePerceptionChannelRequest,
+    CreatePlanRequest,
+    CreateWorldEntityRequest,
+    GoalNode,
+    PendingApproval,
+    PerceptionChannelResponse,
+    PivotHealthReport,
+    PlanSummaryResponse,
+    TimeEventListResponse,
+    TimeEventResponse,
+    TraceDetail,
+    TraceListResponse,
+    UpdateAgentRequest,
+    UpdateGoalRequest,
+    UpdatePerceptionChannelRequest,
+    UpdatePlanRequest,
+    UpdateWorldEntityRequest,
+    WorldEntityResponse,
+)
 from app.schemas.admin_character import (
     AdminCreateTemplateRequest,
     AdminTemplateSummaryResponse,
     AdminUpdateTemplateRequest,
 )
-from app.schemas.admin import (
-    AdminCreateUserRequest,
-    AdminUpdateUserRequest,
-    AdminUserResponse,
-    AuditEntry,
-    PendingApproval,
-    PivotHealthReport,
-    TimeEventListResponse,
-    TimeEventResponse,
-    TraceDetail,
-    TraceListResponse,
-)
 from app.schemas.auth import CurrentUser
 from app.schemas.common import Page
+from app.services import governance as governance_service
 from app.services.admin import (
     get_audit_timeline,
     get_pending_approvals,
@@ -60,9 +80,13 @@ router = APIRouter(prefix="/admin", tags=["admin"], dependencies=[Depends(requir
 
 @router.get("/pivots/health", response_model=PivotHealthReport)
 async def pivots_health(
+    confirmation_store: ConfirmationStore = Depends(get_confirmation_store),
+    tool_runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
     current_user: CurrentUser = Depends(get_current_user),
 ) -> PivotHealthReport:
     return await get_pivots_health(
+        confirmation_store=confirmation_store,
+        tool_runtime=tool_runtime,
         owner_scope=current_user.owner_scope,
     )
 
@@ -72,8 +96,12 @@ async def pivots_health(
 
 @router.get("/safety/pending", response_model=Page[PendingApproval])
 async def safety_pending(
+    confirmation_store: ConfirmationStore = Depends(get_confirmation_store),
+    tool_runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
 ) -> Page[PendingApproval]:
-    items = await get_pending_approvals()
+    items = await get_pending_approvals(
+        confirmation_store=confirmation_store, tool_runtime=tool_runtime
+    )
     return Page(items=items, page=1, page_size=len(items), total=len(items))
 
 
@@ -92,29 +120,139 @@ async def audit_timeline(
 # —— §19.4 太一枢 · 目标 ——
 
 
+@router.get("/goals", response_model=list[GoalNode])
+async def list_goals(
+    character_id: str | None = Query(default=None, description="按人物过滤。"),
+) -> list[GoalNode]:
+    if character_id:
+        return await governance_service.list_goals_by_character(character_id)
+    return await governance_service.list_goals()
 
 
+@router.post("/goals", response_model=GoalNode)
+async def create_goal(payload: CreateGoalRequest) -> GoalNode:
+    return await governance_service.create_goal(payload)
+
+
+@router.patch("/goals/{goal_id}", response_model=GoalNode)
+async def update_goal(
+    goal_id: str,
+    payload: UpdateGoalRequest,
+) -> GoalNode:
+    return await governance_service.update_goal(goal_id, payload)
+
+
+@router.delete("/goals/{goal_id}", status_code=204)
+async def delete_goal(goal_id: str) -> None:
+    await governance_service.delete_goal(goal_id)
 
 
 # —— §19.4 烛照枢 · 感知通道 ——
 
 
+@router.get("/perception/channels", response_model=list[PerceptionChannelResponse])
+async def list_perception_channels() -> list[PerceptionChannelResponse]:
+    return await governance_service.list_perception_channels()
 
 
+@router.post("/perception/channels", response_model=PerceptionChannelResponse)
+async def create_perception_channel(
+    payload: CreatePerceptionChannelRequest,
+) -> PerceptionChannelResponse:
+    return await governance_service.create_perception_channel(payload)
+
+
+@router.patch("/perception/channels/{channel}", response_model=PerceptionChannelResponse)
+async def update_perception_channel(
+    channel: str,
+    payload: UpdatePerceptionChannelRequest,
+) -> PerceptionChannelResponse:
+    return await governance_service.update_perception_channel(channel, payload)
+
+
+@router.delete("/perception/channels/{channel}", status_code=204)
+async def delete_perception_channel(channel: str) -> None:
+    await governance_service.delete_perception_channel(channel)
+
+
+# —— §19.4 河图枢 · 世界实体 ——
+
+
+@router.get("/world/entities", response_model=list[WorldEntityResponse])
+async def list_world_entities() -> list[WorldEntityResponse]:
+    return await governance_service.list_world_entities()
+
+
+@router.post("/world/entities", response_model=WorldEntityResponse)
+async def create_world_entity(
+    payload: CreateWorldEntityRequest,
+) -> WorldEntityResponse:
+    return await governance_service.create_world_entity(payload)
+
+
+@router.patch("/world/entities/{entity_id}", response_model=WorldEntityResponse)
+async def update_world_entity(
+    entity_id: str,
+    payload: UpdateWorldEntityRequest,
+) -> WorldEntityResponse:
+    return await governance_service.update_world_entity(entity_id, payload)
+
+
+@router.delete("/world/entities/{entity_id}", status_code=204)
+async def delete_world_entity(entity_id: str) -> None:
+    await governance_service.delete_world_entity(entity_id)
 
 
 # —— §19.4 洛书枢 · 计划 ——
 
 
+@router.get("/plans", response_model=list[PlanSummaryResponse])
+async def list_plans() -> list[PlanSummaryResponse]:
+    return await governance_service.list_plans()
 
 
+@router.post("/plans", response_model=PlanSummaryResponse)
+async def create_plan(payload: CreatePlanRequest) -> PlanSummaryResponse:
+    return await governance_service.create_plan(payload)
+
+
+@router.patch("/plans/{plan_id}", response_model=PlanSummaryResponse)
+async def update_plan(
+    plan_id: str,
+    payload: UpdatePlanRequest,
+) -> PlanSummaryResponse:
+    return await governance_service.update_plan(plan_id, payload)
+
+
+@router.delete("/plans/{plan_id}", status_code=204)
+async def delete_plan(plan_id: str) -> None:
+    await governance_service.delete_plan(plan_id)
 
 
 # —— §19.4 天工阁枢 · 角色在岗 ——
 
 
+@router.get("/agents/roster", response_model=list[AgentRosterResponse])
+async def list_agent_roster() -> list[AgentRosterResponse]:
+    return await governance_service.list_agent_roster()
 
 
+@router.post("/agents/roster", response_model=AgentRosterResponse)
+async def create_agent(payload: CreateAgentRequest) -> AgentRosterResponse:
+    return await governance_service.create_agent(payload)
+
+
+@router.patch("/agents/roster/{role}", response_model=AgentRosterResponse)
+async def update_agent(
+    role: str,
+    payload: UpdateAgentRequest,
+) -> AgentRosterResponse:
+    return await governance_service.update_agent(role, payload)
+
+
+@router.delete("/agents/roster/{role}", status_code=204)
+async def delete_agent(role: str) -> None:
+    await governance_service.delete_agent(role)
 
 
 # —— §19.5 链路追踪 ——
@@ -249,7 +387,7 @@ async def admin_tenants_overview() -> list[_TenantUserOverview]:
 
     from app.db.session import AsyncSessionLocal
     from app.models.character import Character
-    from app.models.xirang import Memory
+    from app.models.memory import Memory
     from app.models.user import User
 
     async with AsyncSessionLocal() as session:
@@ -268,7 +406,7 @@ async def admin_tenants_overview() -> list[_TenantUserOverview]:
             mem_count = await session.scalar(
                 select(func.count())
                 .select_from(Memory)
-                .join(Character, Memory.character_id == Character.id).where(Memory.status != "tombstoned")
+                .join(Character, Memory.character_id == Character.id)
                 .where(
                     Character.owner_scope == user.id,
                     Character.is_system_template.is_(False),
@@ -316,13 +454,13 @@ async def admin_tenant_memories(user_id: str) -> list[dict]:
 
     from app.db.session import AsyncSessionLocal
     from app.models.character import Character
-    from app.models.xirang import Memory
+    from app.models.memory import Memory
     from app.services.serializers import memory_to_response
 
     async with AsyncSessionLocal() as session:
         result = await session.execute(
             select(Memory)
-            .join(Character, Memory.character_id == Character.id).where(Memory.status != "tombstoned")
+            .join(Character, Memory.character_id == Character.id)
             .where(
                 Character.owner_scope == user_id,
                 Character.is_system_template.is_(False),

backend/app/api/v1/endpoints/audio.py

@@ -0,0 +1,275 @@
+"""音频相关 API 端点 — TTS（文本转语音）、ASR（语音转文本）等。
+
+音频端点使用神识的模型注册表查找可用的音频模型，并调用对应音频适配器合成 /
+转写。ASR 与 TTS 按 ``tags`` 中的 ``asr`` / ``tts`` 能力区分，ASR 内部再按
+``provider`` 区分协议：``yuanqi`` 走 multipart ``/v1/audio/transcriptions``，
+其他走 MiMo 风格的 ``/chat/completions`` + ``input_audio``。
+"""
+
+from __future__ import annotations
+
+from fastapi import APIRouter, File, Form, HTTPException, Response, UploadFile
+from pydantic import BaseModel, Field
+
+from app.ai_provider.audio import AudioService, AudioServiceError
+from app.ai_provider.manager import ProviderManagerFactory
+from app.core.logging import logger
+
+router = APIRouter(tags=["audio"])
+
+_MIME_MAP = {
+    "wav": "audio/wav",
+    "mp3": "audio/mpeg",
+    "opus": "audio/opus",
+    "flac": "audio/flac",
+}
+
+
+class _AudioModelFactory:
+    """Adapter: wraps ProviderManager to provide ModelFactory interface for AudioService.
+
+    ``create_audio(name)`` 按 ``tags`` 判断 ``asr`` / ``tts`` 能力：
+    - ``tts`` → ``HunjingTTSOpenAI``（``/chat/completions`` + ``audio``）
+    - ``asr`` → 按 ``provider`` 分派：
+        - ``yuanqi`` → ``YuanqiASRWhisper``（multipart ``/v1/audio/transcriptions``）
+        - 其他 → ``HunjingASROpenAI``（``/chat/completions`` + ``input_audio``）
+    """
+
+    def __init__(self, manager) -> None:
+        self._manager = manager
+
+    @property
+    def registry(self):
+        return self._manager.model_registry
+
+    def create_audio(self, name: str):
+        model = self._manager.get_model_config(name)
+        is_asr = "asr" in model.tags
+
+        if is_asr:
+            return self._create_asr(model)
+        return self._create_tts(model)
+
+    def _provider_or_none(self, model):
+        """安全获取 provider 配置（provider 未配置时返回 None，走纯端点解析）。"""
+        try:
+            return self._manager.get_provider_config(model.provider)
+        except Exception:
+            return None
+
+    # ── ASR ─────────────────────────────────────────────────────────────
+
+    def _create_asr(self, model):
+        """按 provider 选择 ASR 协议适配器。"""
+        # yuanqi 本地引擎走 multipart /v1/audio/transcriptions
+        if model.provider == "yuanqi":
+            from app.ai_provider.audio.yuanqi_asr import YuanqiASRWhisper
+
+            if model.endpoints:
+                return YuanqiASRWhisper.from_model_config(
+                    model, provider=self._provider_or_none(model)
+                )
+
+            provider = self._manager.get_provider_config(model.provider)
+            api_key, base_url = self._resolve_credentials(provider)
+            if not base_url:
+                raise AudioServiceError(
+                    status_code=500,
+                    code="audio_asr_no_base_url",
+                    message=f"Provider '{model.provider}' has no base_url configured.",
+                )
+            return YuanqiASRWhisper(
+                base_url=base_url,
+                api_key=api_key or "",
+                model=model.model,
+                request_timeout_seconds=model.timeout_seconds or 300,
+            )
+
+        # MiMo 等走 /chat/completions + input_audio
+        from app.ai_provider.audio.asr import HunjingASROpenAI
+
+        if model.endpoints:
+            return HunjingASROpenAI.from_model_config(
+                model, provider=self._provider_or_none(model)
+            )
+
+        provider = self._manager.get_provider_config(model.provider)
+        api_key, base_url = self._resolve_credentials(provider)
+        if not base_url:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_asr_no_base_url",
+                message=f"Provider '{model.provider}' has no base_url configured.",
+            )
+        return HunjingASROpenAI(
+            base_url=base_url,
+            api_key=api_key or "",
+            model=model.model,
+            request_timeout_seconds=model.timeout_seconds or 300,
+        )
+
+    # ── TTS ─────────────────────────────────────────────────────────────
+
+    def _create_tts(self, model):
+        from app.ai_provider.audio.tts import HunjingTTSOpenAI
+
+        # 有 endpoints 时交给 from_model_config（按端点的 status/model/超时）
+        if model.endpoints:
+            return HunjingTTSOpenAI.from_model_config(
+                model, provider=self._provider_or_none(model)
+            )
+
+        # 无 endpoint 时回退到 provider 级别凭证
+        provider = self._manager.get_provider_config(model.provider)
+        api_key, base_url = self._resolve_credentials(provider)
+        if not base_url:
+            raise AudioServiceError(
+                status_code=500,
+                code="audio_tts_no_base_url",
+                message=f"Provider '{model.provider}' has no base_url configured.",
+            )
+        return HunjingTTSOpenAI(
+            base_url=base_url,
+            api_key=api_key or "",
+            model=model.model,
+            request_timeout_seconds=model.timeout_seconds or 120,
+        )
+
+    def _resolve_credentials(self, provider):
+        """从 settings 解析 provider 级别的 API key 和 base URL。"""
+        from app.core.config import settings
+
+        api_key = (
+            settings.__getattribute__(provider.api_key_env.lower())
+            if hasattr(settings, provider.api_key_env.lower())
+            else ""
+        )
+        base_url = (
+            settings.__getattribute__(provider.base_url_env.lower())
+            if hasattr(settings, provider.base_url_env.lower())
+            else None
+        )
+        return api_key, base_url
+
+
+class TTSRequest(BaseModel):
+    """TTS 合成请求。"""
+
+    text: str = Field(..., min_length=1, max_length=4096, description="要合成语音的文本。")
+    voice: str = Field("default", description="语音角色标识（取决于模型，如 default 或声纹 ID）。")
+    format: str = Field("wav", description="音频格式：wav / mp3 / opus / flac。")
+
+
+@router.post("/audio/tts")
+async def synthesize_speech(body: TTSRequest) -> Response:
+    """合成文本为语音，返回音频二进制流。
+
+    使用神识注册表中第一个活跃的 TTS 模型（capability: tts）。
+    未配置 TTS 模型时返回 503。
+    """
+    if not body.text.strip():
+        raise HTTPException(status_code=400, detail="text 不能为空。")
+
+    mime = _MIME_MAP.get(body.format, "audio/wav")
+
+    try:
+        manager = ProviderManagerFactory.create()
+        service = AudioService(_AudioModelFactory(manager))
+        async with service:
+            result = await service.synthesize(
+                text=body.text,
+                voice=body.voice,
+                response_format=body.format,
+            )
+    except AudioServiceError as exc:
+        logger.error(
+            "audio.tts.api_error",
+            voice=body.voice,
+            format=body.format,
+            error_code=exc.code,
+            error_message=exc.message,
+        )
+        raise HTTPException(
+            status_code=exc.status_code or 502,
+            detail=exc.message,
+        ) from exc
+
+    logger.info(
+        "audio.tts.success",
+        voice=body.voice,
+        format=body.format,
+        audio_bytes=len(result.audio_data),
+    )
+
+    return Response(
+        content=result.audio_data,
+        media_type=mime,
+        headers={
+            "Content-Disposition": f'inline; filename="speech.{body.format}"',
+            "X-Audio-Format": body.format,
+            "Cache-Control": "public, max-age=3600",
+        },
+    )
+
+
+# ── ASR（语音转文本）───────────────────────────────────────────────────────
+
+
+class TranscriptionResponse(BaseModel):
+    """OpenAI Whisper 兼容的转写响应。"""
+
+    text: str = Field(description="转写后的文本")
+
+
+@router.post("/audio/transcriptions", response_model=TranscriptionResponse)
+async def transcribe_audio(
+    file: UploadFile = File(..., description="音频文件（wav/mp3/m4a/flac/ogg/opus/webm 等）"),
+    language: str | None = Form(default=None, description="语言提示（ISO-639-1：zh/en/ja/ko 等），省略则自动检测"),
+    model: str | None = Form(default=None, description="可选，指定使用的 ASR 模型逻辑名（如 funasr-sensevoice / mimo-v2.5-asr），省略则用注册表中第一个"),
+) -> TranscriptionResponse:
+    """转写音频为文本，返回 OpenAI Whisper 兼容的 JSON。
+
+    不指定 ``model`` 时用神识注册表中第一个活跃的 ASR 模型（capability: asr），
+    按其 ``provider`` 自动选择协议适配器：``yuanqi`` 走本地 multipart 端点，
+    其他走 MiMo 风格的 chat completions。未配置 ASR 模型时返回 503。
+    """
+    audio_bytes = await file.read()
+    if not audio_bytes:
+        raise HTTPException(status_code=400, detail="音频文件为空。")
+
+    fmt = (file.filename or "audio.wav").rsplit(".", 1)[-1].lower() if "." in (file.filename or "") else "wav"
+
+    try:
+        manager = ProviderManagerFactory.create()
+        service = AudioService(_AudioModelFactory(manager))
+        async with service:
+            result = await service.transcribe(
+                audio_data=audio_bytes,
+                format=fmt,
+                language=language,
+                model_name=model,
+            )
+    except AudioServiceError as exc:
+        logger.error(
+            "audio.asr.api_error",
+            filename=file.filename,
+            format=fmt,
+            language=language,
+            error_code=exc.code,
+            error_message=exc.message,
+        )
+        raise HTTPException(
+            status_code=exc.status_code or 502,
+            detail=exc.message,
+        ) from exc
+
+    logger.info(
+        "audio.asr.success",
+        filename=file.filename,
+        format=fmt,
+        language=language,
+        text_length=len(result.text),
+        text=result.text,
+    )
+
+    return TranscriptionResponse(text=result.text)

backend/app/api/v1/endpoints/avatar.py

@@ -0,0 +1,47 @@
+"""角色头像 API。
+
+上传与获取角色头像图片文件。
+"""
+
+from fastapi import APIRouter, Depends, File, UploadFile
+
+from app.api.v1.deps import get_current_user
+from app.schemas.auth import CurrentUser
+from app.services.avatar import (
+    get_avatar_response,
+    upload_avatar,
+)
+
+router = APIRouter(prefix="/characters", tags=["characters"])
+
+
+@router.post("/{character_id}/avatar")
+async def upload_character_avatar(
+    character_id: str,
+    file: UploadFile = File(..., description="头像图片，支持 JPG/PNG/WebP，最大 5MB。"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> dict:
+    """上传角色头像。
+
+    支持的格式：JPEG、PNG、WebP。最大 5MB。
+    新头像会替换旧头像（同角色只保留一张）。
+    """
+    content = await file.read()
+    avatar_url = await upload_avatar(
+        character_id=character_id,
+        content=content,
+        content_type=file.content_type or "image/jpeg",
+        owner_scope=current_user.owner_scope,
+    )
+    return {"avatar_url": avatar_url}
+
+
+@router.get("/{character_id}/avatar")
+async def get_character_avatar(
+    character_id: str,
+) -> object:
+    """获取角色头像图片。
+
+    返回原始图片文件。无头像时返回 404。
+    """
+    return await get_avatar_response(character_id)

backend/app/api/v1/endpoints/baigong.py

@@ -1,5 +0,0 @@
-"""百工与司命路由（域实现见 app/domains/baigong/api.py）。"""
-
-from app.domains.baigong.api import routers
-
-__all__ = ["routers"]

backend/app/api/v1/endpoints/character_import.py

@@ -1,49 +1,29 @@
-"""角色卡导入 / 导出 API。
+"""角色卡导入 / 导出 API。"""
-
-rewrite/1.0 M2b：导入产出**可审阅灵胚**（含 character_book 暂存），不再直接建人物；
-经照心编辑与启镜（POST /embryo-drafts/{id}/activate）后才物化人物与世谱。
-"""
 
 import json
 
 from fastapi import APIRouter, Depends, File, Response, UploadFile
 
 from app.api.v1.deps import get_current_user
-from app.domains import jingsheng
 from app.schemas.auth import CurrentUser
-from app.services.card_import import card_to_embryo_payload, export_character_card
+from app.schemas.character import ImportCardResponse
+from app.services.card_import import export_character_card, import_character_card_response
 
 router = APIRouter(prefix="/characters", tags=["characters"])
 
 
-@router.post("/import-card", status_code=201)
+@router.post("/import-card", response_model=ImportCardResponse)
 async def import_character_card_api(
     file: UploadFile = File(..., description="角色卡文件，支持 .png / .json / .charx。"),
     current_user: CurrentUser = Depends(get_current_user),
-) -> dict:
+) -> ImportCardResponse:
-    """导入酒馆角色卡（V1/V2/V3）→ 生成可审阅灵胚。
+    """导入酒馆角色卡（V1/V2/V3），建立人物 + 世谱（character_book）。
 
-    卡内容整体进入灵胚道体草稿（identity_baseline.import_card），
+    ``personality`` 写入道体 ``personality_summary`` 作初始值；
-    ``character_book`` 在启镜时物化为该人物的世谱书与条目。
+    ``character_book`` 转为该角色的世谱书 + 条目。
     """
     raw = await file.read()
-    payload = card_to_embryo_payload(raw)
+    return await import_character_card_response(raw, owner_scope=current_user.owner_scope)
-    book_entry_count = payload.pop("book_entry_count")
-    embryo = await jingsheng.create_embryo(
-        owner_scope=current_user.owner_scope,
-        source="imported",
-        name=payload["name"],
-        description=payload["description"],
-        identity_baseline=payload["identity_baseline"],
-    )
-    return {
-        "embryo_id": embryo.id,
-        "status": embryo.status,
-        "name": embryo.name,
-        "source": embryo.source,
-        "book_entry_count": book_entry_count,
-        "next": "照心编辑 PATCH /embryo-drafts/{id}，启镜 POST /embryo-drafts/{id}/activate",
-    }
 
 
 @router.get("/{character_id}/export-card")

backend/app/api/v1/endpoints/chat.py

@@ -0,0 +1,137 @@
+"""聊天 API。"""
+
+from fastapi import APIRouter, Depends, Header, Query, Request, Response, status
+
+from app.api.v1.deps import get_current_user
+from app.schemas.auth import CurrentUser
+from app.schemas.chat import (
+    ChatMessageListResponse,
+    ChatMessageResponse,
+    ChatSessionListResponse,
+    ChatSessionResponse,
+    CreateSessionRequest,
+    SelectVersionRequest,
+    SendMessageRequest,
+    SendMessageResponse,
+    UpdateSessionRequest,
+)
+from app.services.chat import (
+    create_session,
+    delete_session,
+    get_session_response,
+    list_message_responses,
+    list_session_responses,
+    select_message_version,
+    send_message,
+    update_session_response,
+)
+from app.services.idempotency import run_idempotent
+
+router = APIRouter(prefix="/chat", tags=["chat"])
+
+
+@router.post("/sessions", response_model=ChatSessionResponse)
+async def create_chat_session(
+    payload: CreateSessionRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ChatSessionResponse:
+    return await create_session(payload, owner_scope=current_user.owner_scope)
+
+
+@router.get("/sessions", response_model=ChatSessionListResponse)
+async def list_chat_sessions(
+    current_user: CurrentUser = Depends(get_current_user),
+    status: str | None = Query(default=None, description="按状态过滤：active / archived"),
+    limit: int = Query(default=50, ge=1, le=100),
+    offset: int = Query(default=0, ge=0),
+) -> ChatSessionListResponse:
+    return await list_session_responses(
+        owner_scope=current_user.owner_scope, status=status, limit=limit, offset=offset
+    )
+
+
+@router.get("/sessions/{session_id}", response_model=ChatSessionResponse)
+async def get_chat_session(
+    session_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ChatSessionResponse:
+    return await get_session_response(session_id, owner_scope=current_user.owner_scope)
+
+
+@router.patch("/sessions/{session_id}", response_model=ChatSessionResponse)
+async def update_chat_session(
+    session_id: str,
+    payload: UpdateSessionRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ChatSessionResponse:
+    return await update_session_response(session_id, payload, owner_scope=current_user.owner_scope)
+
+
+@router.delete("/sessions/{session_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_chat_session(
+    session_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> Response:
+    await delete_session(session_id, owner_scope=current_user.owner_scope)
+    return Response(status_code=status.HTTP_204_NO_CONTENT)
+
+
+@router.post("/sessions/{session_id}/messages", response_model=SendMessageResponse)
+async def send_chat_message(
+    session_id: str,
+    payload: SendMessageRequest,
+    request: Request,
+    idempotency_key: str | None = Header(default=None, alias="Idempotency-Key"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> SendMessageResponse:
+    return await run_idempotent(
+        key=idempotency_key,
+        method="POST",
+        path=str(request.url.path),
+        payload=payload,
+        response_type=SendMessageResponse,
+        resource_type="run",
+        handler=lambda session: send_message(
+            session,
+            session_id,
+            payload,
+            owner_scope=current_user.owner_scope,
+            tool_runtime=getattr(request.app.state, "tool_runtime", None),
+            confirmation_registry=getattr(request.app.state, "confirmation_registry", None),
+            confirmation_store=getattr(request.app.state, "confirmation_store", None),
+            event_store=getattr(request.app.state, "event_store", None),
+            agent_run_registry=getattr(request.app.state, "agent_run_registry", None),
+            python_skill_catalog=getattr(request.app.state, "python_skill_catalog", None),
+        ),
+    )
+
+
+@router.get("/sessions/{session_id}/messages", response_model=ChatMessageListResponse)
+async def list_chat_messages(
+    session_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+    limit: int = Query(default=100, ge=1, le=200),
+    offset: int = Query(default=0, ge=0),
+) -> ChatMessageListResponse:
+    return await list_message_responses(
+        session_id, owner_scope=current_user.owner_scope, limit=limit, offset=offset
+    )
+
+
+@router.patch(
+    "/sessions/{session_id}/messages/{message_id}/version",
+    response_model=ChatMessageResponse,
+)
+async def select_message_version_endpoint(
+    session_id: str,
+    message_id: str,
+    payload: SelectVersionRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ChatMessageResponse:
+    """选择/激活消息的某个历史版本。"""
+    return await select_message_version(
+        session_id,
+        message_id,
+        payload,
+        owner_scope=current_user.owner_scope,
+    )

backend/app/api/v1/endpoints/drive.py

@@ -0,0 +1,73 @@
+"""内驱力 /drive API。"""
+
+from fastapi import APIRouter, Query
+
+from app.schemas.common import Page
+from app.schemas.drive import CuriosityResponse, SubgoalResponse
+from app.services.drive import (
+    approve_subgoal,
+    defer_subgoal,
+    list_curiosities,
+    list_subgoals,
+    reject_subgoal,
+)
+
+router = APIRouter(tags=["drive"])
+
+
+@router.get(
+    "/characters/{character_id}/curiosities",
+    response_model=Page[CuriosityResponse],
+)
+async def list_curiosities_endpoint(
+    character_id: str,
+    source: str | None = Query(default=None, description="按来源过滤（契约字典内驱力 source）"),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[CuriosityResponse]:
+    """列出某人物的好奇问题（大周天内驱力生成）。"""
+    return await list_curiosities(
+        character_id=character_id,
+        source=source,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get(
+    "/characters/{character_id}/subgoals",
+    response_model=Page[SubgoalResponse],
+)
+async def list_subgoals_endpoint(
+    character_id: str,
+    status: str | None = Query(
+        default=None, description="按状态过滤：candidate/approved/deferred/rejected"
+    ),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[SubgoalResponse]:
+    """列出某人物的探索性次生目标。"""
+    return await list_subgoals(
+        character_id=character_id,
+        status=status,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.post("/subgoals/{subgoal_id}/approve", response_model=SubgoalResponse)
+async def approve_subgoal_endpoint(subgoal_id: str) -> SubgoalResponse:
+    """通过探索性次生目标（仅标记 approved，本期不自动执行）。"""
+    return await approve_subgoal(subgoal_id)
+
+
+@router.post("/subgoals/{subgoal_id}/defer", response_model=SubgoalResponse)
+async def defer_subgoal_endpoint(subgoal_id: str) -> SubgoalResponse:
+    """延后探索性次生目标（status → deferred）。"""
+    return await defer_subgoal(subgoal_id)
+
+
+@router.post("/subgoals/{subgoal_id}/reject", response_model=SubgoalResponse)
+async def reject_subgoal_endpoint(subgoal_id: str) -> SubgoalResponse:
+    """驳回探索性次生目标（status → rejected）。"""
+    return await reject_subgoal(subgoal_id)

backend/app/api/v1/endpoints/embryo_drafts.py

@@ -1,142 +0,0 @@
-"""灵胚 API（镜生域，rewrite/1.0 M1）。对应 api-contracts.md §3.2。"""
-
-from __future__ import annotations
-
-import json
-
-from fastapi import APIRouter, Depends, Request
-from pydantic import BaseModel, Field
-
-from app.api.v1.deps import get_current_user
-from app.domains import jingsheng
-from app.kernel import Kernel
-from app.schemas.auth import CurrentUser
-
-router = APIRouter(prefix="/embryo-drafts", tags=["jingsheng"])
-
-
-class EmbryoCreate(BaseModel):
-    source: str = Field(default="original", description="original/adopted/imported/serendipity")
-    name: str = Field(min_length=1, max_length=120)
-    description: str | None = Field(default=None, max_length=8000)
-    identity_baseline: dict = Field(default_factory=dict, description="道体锚点草稿")
-
-
-class EmbryoPatch(BaseModel):
-    name: str | None = Field(default=None, min_length=1, max_length=120)
-    description: str | None = Field(default=None, max_length=8000)
-    identity_baseline: dict | None = None
-
-
-class RehearseRequest(BaseModel):
-    prompt: str = Field(min_length=1, max_length=8000)
-
-
-def _embryo_view(embryo) -> dict:  # noqa: ANN001 — ORM 行
-    return {
-        "id": embryo.id,
-        "status": embryo.status,
-        "source": embryo.source,
-        "name": embryo.name,
-        "description": embryo.description,
-        "identity_baseline": json.loads(embryo.identity_baseline_json or "{}"),
-        "rehearsals": json.loads(embryo.rehearsals_json or "[]"),
-        "created_at": embryo.created_at.isoformat(),
-        "updated_at": embryo.updated_at.isoformat(),
-    }
-
-
-@router.get("")
-async def list_embryo_drafts(user: CurrentUser = Depends(get_current_user)) -> list[dict]:
-    return [_embryo_view(e) for e in await jingsheng.list_embryos(user.owner_scope)]
-
-
-@router.post("", status_code=201)
-async def create_embryo_draft(
-    payload: EmbryoCreate, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    embryo = await jingsheng.create_embryo(
-        owner_scope=user.owner_scope,
-        source=payload.source,
-        name=payload.name,
-        description=payload.description,
-        identity_baseline=payload.identity_baseline,
-    )
-    return _embryo_view(embryo)
-
-
-@router.get("/{embryo_id}")
-async def get_embryo_draft(
-    embryo_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return _embryo_view(await jingsheng.get_embryo(embryo_id, user.owner_scope))
-
-
-@router.patch("/{embryo_id}")
-async def patch_embryo_draft(
-    embryo_id: str, payload: EmbryoPatch, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    embryo = await jingsheng.patch_embryo(
-        embryo_id,
-        user.owner_scope,
-        name=payload.name,
-        description=payload.description,
-        identity_baseline=payload.identity_baseline,
-    )
-    return _embryo_view(embryo)
-
-
-@router.post("/{embryo_id}/rehearse")
-async def rehearse_embryo(
-    embryo_id: str,
-    payload: RehearseRequest,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    """照心试演：幻境 Run，不产生人物经历；事件流经 /runs/{run_id}/stream。"""
-    embryo = await jingsheng.get_embryo(embryo_id, user.owner_scope)
-    if embryo.status == "activated":
-        from app.core.errors import AppError
-
-        raise AppError("HJ-1103", "灵胚已启镜，无需再试演。", status_code=409)
-    kernel: Kernel | None = getattr(request.app.state, "kernel", None)
-    if kernel is None:
-        from app.core.errors import AppError
-
-        raise AppError("service_unavailable", "Kernel 运行时未就绪。", status_code=503)
-
-    baseline = json.loads(embryo.identity_baseline_json or "{}")
-    system_contract = (
-        f"你是一位尚未降生的灵胚「{embryo.name}」，正在幻境中试演。"
-        f"身份锚点：{json.dumps(baseline, ensure_ascii=False)}"
-    )
-    run = await kernel.start_rehearsal_run(
-        embryo_id=embryo_id, prompt=payload.prompt, system_contract=system_contract,
-        owner_id=user.owner_scope,
-    )
-    await jingsheng.record_rehearsal(
-        embryo_id, user.owner_scope, run_id=run.id, prompt=payload.prompt
-    )
-    return {"run_id": run.id, "kind": "rehearsal"}
-
-
-@router.post("/{embryo_id}/activate")
-async def activate_embryo_draft(
-    embryo_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    """启镜：签发正式人物 ID、魂籍、执镜关系与命台。"""
-    character = await jingsheng.activate_embryo(embryo_id, user.owner_scope)
-    return {
-        "character_id": character.id,
-        "name": character.name,
-        "status": character.status,
-        "source": character.source,
-        "identity_record_version": 1,
-    }
-
-
-@router.post("/{embryo_id}/abandon", status_code=204)
-async def abandon_embryo_draft(
-    embryo_id: str, user: CurrentUser = Depends(get_current_user)
-) -> None:
-    await jingsheng.abandon_embryo(embryo_id, user.owner_scope)

backend/app/api/v1/endpoints/evolution.py

@@ -0,0 +1,60 @@
+"""演化候选审核 API。"""
+
+from fastapi import APIRouter, Query
+
+from app.schemas.common import Page
+from app.schemas.evolution import EvolutionCandidateResponse
+from app.services.evolution import (
+    approve_evolution_candidate,
+    list_evolution_candidates,
+    reject_evolution_candidate,
+)
+
+router = APIRouter(tags=["evolution"])
+
+
+@router.get(
+    "/characters/{character_id}/evolution-candidates",
+    response_model=Page[EvolutionCandidateResponse],
+)
+async def list_evolution_candidates_endpoint(
+    character_id: str,
+    status: str | None = Query(
+        default=None, description="按状态过滤：pending/approved/rejected/applied"
+    ),
+    candidate_type: str | None = Query(
+        default=None, alias="type", description="按候选类型过滤（契约字典 §12.1）"
+    ),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[EvolutionCandidateResponse]:
+    """列出某人物的演化候选（大周天生成 + 审核状态）。"""
+    return await list_evolution_candidates(
+        character_id=character_id,
+        status=status,
+        candidate_type=candidate_type,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.post(
+    "/evolution-candidates/{candidate_id}/approve",
+    response_model=EvolutionCandidateResponse,
+)
+async def approve_candidate(
+    candidate_id: str,
+) -> EvolutionCandidateResponse:
+    """审核通过演化候选：派生到下游（人格版本/程序记忆等），status → applied。"""
+    return await approve_evolution_candidate(candidate_id)
+
+
+@router.post(
+    "/evolution-candidates/{candidate_id}/reject",
+    response_model=EvolutionCandidateResponse,
+)
+async def reject_candidate(
+    candidate_id: str,
+) -> EvolutionCandidateResponse:
+    """驳回演化候选：status → rejected，不派生下游。"""
+    return await reject_evolution_candidate(candidate_id)

backend/app/api/v1/endpoints/extraction.py

@@ -0,0 +1,90 @@
+"""大周天抽取候选审核 API（记忆候选 + 世界实体候选）。"""
+
+from fastapi import APIRouter, Query
+
+from app.schemas.candidates import MemoryCandidateResponse
+from app.schemas.common import Page
+from app.schemas.world import WorldEntityResponse
+from app.services.extraction import (
+    approve_memory_proposal,
+    approve_world_entity,
+    list_memory_proposals,
+    list_world_entities_pending,
+    reject_memory_proposal,
+    reject_world_entity,
+)
+
+router = APIRouter(tags=["extraction"])
+
+
+@router.get(
+    "/characters/{character_id}/memory-candidates",
+    response_model=Page[MemoryCandidateResponse],
+)
+async def list_memory_candidates_endpoint(
+    character_id: str,
+    source: str | None = Query(
+        default=None, description="来源过滤：cycle（大周天）/ import（资料导入）"
+    ),
+    status: str | None = Query(default=None),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[MemoryCandidateResponse]:
+    """列出记忆候选（大周天 + 资料导入统一）。"""
+    return await list_memory_proposals(
+        character_id=character_id,
+        source=source,
+        status=status,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.post(
+    "/memory-candidates/{candidate_id}/approve",
+    response_model=MemoryCandidateResponse,
+)
+async def approve_memory_candidate_endpoint(
+    candidate_id: str,
+) -> MemoryCandidateResponse:
+    """通过记忆候选：派生为 memories 记录（source=big_cycle）。"""
+    return await approve_memory_proposal(candidate_id)
+
+
+@router.post(
+    "/memory-candidates/{candidate_id}/reject",
+    response_model=MemoryCandidateResponse,
+)
+async def reject_memory_candidate_endpoint(
+    candidate_id: str,
+) -> MemoryCandidateResponse:
+    """驳回记忆候选。"""
+    return await reject_memory_proposal(candidate_id)
+
+
+@router.get(
+    "/characters/{character_id}/world/entity-proposals",
+    response_model=Page[WorldEntityResponse],
+)
+async def list_world_entity_proposals_endpoint(
+    character_id: str,
+    status: str | None = Query(default="pending", description="默认 pending（候选）"),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[WorldEntityResponse]:
+    """列出世界实体候选（大周天抽取，status=pending 待审核）。"""
+    return await list_world_entities_pending(
+        character_id=character_id, status=status, page=page, page_size=page_size
+    )
+
+
+@router.post("/world/entities/{entity_id}/approve", response_model=WorldEntityResponse)
+async def approve_world_entity_endpoint(entity_id: str) -> WorldEntityResponse:
+    """通过世界实体候选：status → confirmed 进入世界模型。"""
+    return await approve_world_entity(entity_id)
+
+
+@router.post("/world/entities/{entity_id}/reject", response_model=WorldEntityResponse)
+async def reject_world_entity_endpoint(entity_id: str) -> WorldEntityResponse:
+    """驳回世界实体候选。"""
+    return await reject_world_entity(entity_id)

backend/app/api/v1/endpoints/goals.py

@@ -0,0 +1,21 @@
+"""Per-Character 目标管理端点（非 admin，供 /drive 等前端使用）。"""
+
+from fastapi import APIRouter, Query
+
+from app.schemas.admin import CreateGoalRequest, GoalNode
+from app.services import governance as governance_service
+
+router = APIRouter(prefix="/goals", tags=["goals"])
+
+
+@router.get("", response_model=list[GoalNode])
+async def list_goals(
+    character_id: str = Query(..., description="按人物过滤。"),
+    status: str | None = Query(default=None, description="按状态过滤（§5.12）。"),
+) -> list[GoalNode]:
+    return await governance_service.list_goals_by_character(character_id, status_filter=status)
+
+
+@router.post("", response_model=GoalNode, status_code=201)
+async def create_goal(payload: CreateGoalRequest) -> GoalNode:
+    return await governance_service.create_goal(payload)

backend/app/api/v1/endpoints/hetu.py

@@ -1,5 +0,0 @@
-"""河图世界路由（域实现见 app/domains/hetu/api.py）。"""
-
-from app.domains.hetu.api import world_router
-
-__all__ = ["world_router"]

backend/app/api/v1/endpoints/imports.py

@@ -10,6 +10,12 @@ from fastapi import APIRouter, Depends, File, Form, Query, UploadFile
 
 from app.api.v1.deps import get_current_user
 from app.schemas.auth import CurrentUser
+from app.schemas.candidates import (
+    BatchReviewRequest,
+    BatchReviewResult,
+    MemoryCandidateResponse,
+    ProfileCandidateResponse,
+)
 from app.schemas.common import Page
 from app.schemas.imports import (
     CreateImportRequest,
@@ -17,11 +23,18 @@ from app.schemas.imports import (
     ImportJobResponse,
 )
 from app.services.imports import (
+    batch_review_memory_candidates,
+    batch_review_profile_candidates,
     create_import_from_json,
     create_import_from_upload,
     get_import,
     list_import_items,
     list_jobs_page,
+    list_memory_candidates,
+    list_profile_candidates,
+    trigger_memory_extraction,
+    trigger_personality_extraction,
+    trigger_profile_extraction,
 )
 
 router = APIRouter(tags=["imports"])
@@ -103,3 +116,109 @@ async def read_import_items(
         page_size=page_size,
         owner_scope=current_user.owner_scope,
     )
+
+
+# —— 候选抽取（5b，异步后台任务）——
+
+
+@router.post(
+    "/characters/{character_id}/imports/{import_id}/profile-candidates",
+    response_model=ImportJobResponse,
+)
+async def trigger_profile_candidates(
+    character_id: str,
+    import_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ImportJobResponse:
+    return await trigger_profile_extraction(
+        character_id, import_id, owner_scope=current_user.owner_scope
+    )
+
+
+@router.get(
+    "/characters/{character_id}/imports/{import_id}/profile-candidates",
+    response_model=list[ProfileCandidateResponse],
+)
+async def list_profile_candidates_api(
+    character_id: str,
+    import_id: str,
+    status: str | None = Query(default=None, description="按审核状态过滤。"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> list[ProfileCandidateResponse]:
+    return await list_profile_candidates(
+        character_id, import_id, status=status, owner_scope=current_user.owner_scope
+    )
+
+
+@router.post(
+    "/characters/{character_id}/imports/{import_id}/memory-candidates",
+    response_model=ImportJobResponse,
+)
+async def trigger_memory_candidates(
+    character_id: str,
+    import_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ImportJobResponse:
+    return await trigger_memory_extraction(
+        character_id, import_id, owner_scope=current_user.owner_scope
+    )
+
+
+@router.get(
+    "/characters/{character_id}/imports/{import_id}/memory-candidates",
+    response_model=list[MemoryCandidateResponse],
+)
+async def list_memory_candidates_api(
+    character_id: str,
+    import_id: str,
+    status: str | None = Query(default=None, description="按审核状态过滤。"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> list[MemoryCandidateResponse]:
+    return await list_memory_candidates(
+        character_id, import_id, status=status, owner_scope=current_user.owner_scope
+    )
+
+
+@router.post(
+    "/characters/{character_id}/imports/{import_id}/personality-proposals",
+    response_model=ImportJobResponse,
+)
+async def trigger_personality_proposals(
+    character_id: str,
+    import_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> ImportJobResponse:
+    return await trigger_personality_extraction(
+        character_id, import_id, owner_scope=current_user.owner_scope
+    )
+
+
+# —— 候选审核应用（5c）——
+
+
+@router.post(
+    "/characters/{character_id}/profile-candidates/batch-review",
+    response_model=BatchReviewResult,
+)
+async def batch_review_profile(
+    character_id: str,
+    payload: BatchReviewRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> BatchReviewResult:
+    return await batch_review_profile_candidates(
+        character_id, payload, owner_scope=current_user.owner_scope
+    )
+
+
+@router.post(
+    "/characters/{character_id}/memory-candidates/batch-review",
+    response_model=BatchReviewResult,
+)
+async def batch_review_memory(
+    character_id: str,
+    payload: BatchReviewRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> BatchReviewResult:
+    return await batch_review_memory_candidates(
+        character_id, payload, owner_scope=current_user.owner_scope
+    )

backend/app/api/v1/endpoints/jingsheng_characters.py

@@ -1,220 +0,0 @@
-"""镜生域人物端点：魂籍导出与校验、死亡请求/撤销/落定、命台租约（api-contracts.md §3.2）。"""
-
-from __future__ import annotations
-
-import json
-
-from fastapi import APIRouter, Depends
-from pydantic import BaseModel, Field
-from sqlalchemy import select
-
-from app.api.v1.deps import get_current_user
-from app.core.config import settings
-from app.core.errors import AppError
-from app.db.session import AsyncSessionLocal
-from app.domains import jingsheng
-from app.domains.jingsheng.identity import IdentityVerificationError, verify_identity_record
-from app.domains.jingsheng.seat import SeatConflict, acquire_lease, emit_seat_event, release_lease
-from app.models.character import Character
-from app.models.jingsheng import IdentityRecord
-from app.schemas.auth import CurrentUser
-
-router = APIRouter(prefix="/characters", tags=["jingsheng"])
-
-
-class DeathFinalizeRequest(BaseModel):
-    confirm_phrase: str = Field(description="须填入人物名以强确认")
-
-
-class SeatLeaseRequest(BaseModel):
-    holder: str = Field(min_length=1, max_length=120, description="租约持有者标识（设备/实例）")
-
-
-async def _owned_character(character_id: str, owner_scope: str) -> Character:
-    async with AsyncSessionLocal() as session:
-        character = await session.get(Character, character_id)
-    if character is None or character.owner_scope != owner_scope:
-        raise AppError("not_found", "人物不存在。")
-    return character
-
-
-# ── 魂籍 ──────────────────────────────────────────────
-
-
-@router.get("/{character_id}/identity-records")
-async def list_identity_records(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> list[dict]:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        result = await session.execute(
-            select(IdentityRecord)
-            .where(IdentityRecord.character_id == character_id)
-            .order_by(IdentityRecord.version.desc())
-        )
-        records = result.scalars().all()
-    return [
-        {
-            "id": r.id,
-            "version": r.version,
-            "digest": r.digest,
-            "created_at": r.created_at.isoformat(),
-        }
-        for r in records
-    ]
-
-
-@router.get("/{character_id}/identity-records/{record_id}")
-async def get_identity_record(
-    character_id: str, record_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        record = await session.get(IdentityRecord, record_id)
-    if record is None or record.character_id != character_id:
-        raise AppError("not_found", "魂籍记录不存在。")
-    return {
-        "id": record.id,
-        "version": record.version,
-        "digest": record.digest,
-        "payload": json.loads(record.payload_json),
-        "created_at": record.created_at.isoformat(),
-    }
-
-
-@router.post("/{character_id}/identity-records")
-async def export_identity_record(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    """导出新版本魂籍：身份/数据/运行状态三段分离。"""
-    character = await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        latest = await session.scalar(
-            select(IdentityRecord.version)
-            .where(IdentityRecord.character_id == character_id)
-            .order_by(IdentityRecord.version.desc())
-            .limit(1)
-        )
-        next_version = (latest or 0) + 1
-        record = jingsheng.build_identity_record(
-            character_id=character_id,
-            version=next_version,
-            identity={
-                "name": character.name,
-                "source": character.source,
-                "identity_baseline": json.loads(character.identity_baseline_json or "{}"),
-                "activated_at": character.activated_at.isoformat() if character.activated_at else None,
-            },
-            runtime_state={"status": character.status},
-        )
-        session.add(record)
-        await session.commit()
-        await session.refresh(record)
-    return {
-        "id": record.id,
-        "version": record.version,
-        "digest": record.digest,
-        "created_at": record.created_at.isoformat(),
-    }
-
-
-@router.post("/{character_id}/identity-records/{record_id}/verify")
-async def verify_record(
-    character_id: str, record_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        record = await session.get(IdentityRecord, record_id)
-    if record is None or record.character_id != character_id:
-        raise AppError("not_found", "魂籍记录不存在。")
-    try:
-        verify_identity_record(record)
-    except IdentityVerificationError as exc:
-        raise AppError("HJ-9000", f"魂籍校验失败：{exc.reason}", status_code=422) from exc
-    return {"valid": True, "version": record.version, "digest": record.digest}
-
-
-# ── 死亡与冷静期 ──────────────────────────────────────────────
-
-
-@router.post("/{character_id}/death-request")
-async def request_death(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    character = await jingsheng.death_request(
-        character_id, user.owner_scope, calm_period_hours=settings.death_calm_period_hours
-    )
-    return {
-        "character_id": character.id,
-        "status": character.status,
-        "calm_period_until": character.calm_period_until.isoformat(),
-    }
-
-
-@router.post("/{character_id}/death-cancel")
-async def cancel_death(character_id: str, user: CurrentUser = Depends(get_current_user)) -> dict:
-    character = await jingsheng.death_cancel(character_id, user.owner_scope)
-    return {"character_id": character.id, "status": character.status}
-
-
-@router.post("/{character_id}/death-finalize")
-async def finalize_death(
-    character_id: str,
-    payload: DeathFinalizeRequest,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    character = await _owned_character(character_id, user.owner_scope)
-    if payload.confirm_phrase != character.name:
-        raise AppError("invalid_request", "确认短语与人物名不一致，拒绝落定。")
-    deceased = await jingsheng.death_finalize(character_id, user.owner_scope)
-    return {
-        "character_id": deceased.id,
-        "status": deceased.status,
-        "died_at": deceased.died_at.isoformat() if deceased.died_at else None,
-    }
-
-
-# ── 命台租约 ──────────────────────────────────────────────
-
-
-@router.post("/{character_id}/seat/acquire")
-async def acquire_seat(
-    character_id: str, payload: SeatLeaseRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        try:
-            seat = await acquire_lease(
-                session,
-                character_id,
-                payload.holder,
-                ttl_seconds=settings.seat_lease_ttl_seconds,
-            )
-        except SeatConflict as exc:
-            current_holder = exc.seat.holder
-            await session.rollback()
-            # 留痕在事务回滚后发射（避免 SQLite 跨连接写锁冲突）
-            await emit_seat_event(
-                "seat.contested",
-                character_id,
-                current_holder,
-                None,
-                requester=payload.holder,
-            )
-            raise AppError("HJ-1101", f"命台被占用：{exc}", status_code=429) from exc
-        epoch, holder = seat.epoch, seat.holder
-        await session.commit()
-    await emit_seat_event("seat.acquired", character_id, holder, epoch)
-    return {"epoch": epoch, "holder": holder}
-
-
-@router.post("/{character_id}/seat/release", status_code=204)
-async def release_seat(
-    character_id: str, payload: SeatLeaseRequest, user: CurrentUser = Depends(get_current_user)
-) -> None:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        released = await release_lease(session, character_id, payload.holder)
-        await session.commit()
-    if released:
-        await emit_seat_event("seat.released", character_id, payload.holder, None)

backend/app/api/v1/endpoints/kernel_runs.py

@@ -1,55 +0,0 @@
-"""Kernel Run API（rewrite/1.0 新契约首个端点）。
-
-POST /api/v1/runs：创建占位前台 Run（M0 骨架），事件流经既有
-GET /api/v1/runs/{run_id}/stream 订阅（SSE + Last-Event-ID 断线续传）。
-与旧 runs 路由共存：本模块只新增 POST，不改动旧读端点（M2 重建时收敛）。
-"""
-
-from __future__ import annotations
-
-from fastapi import APIRouter, Depends, Request
-from pydantic import BaseModel, Field
-from sqlalchemy.ext.asyncio import AsyncSession
-
-from app.api.v1.deps import get_current_user
-from app.db.session import get_session
-from app.kernel import Kernel
-from app.schemas.auth import CurrentUser
-from app.schemas.runtime import RunResponse
-from app.services.characters import resolve_active_character
-from app.services.runtime import get_run_response
-
-router = APIRouter(prefix="/runs", tags=["kernel"])
-
-
-class KernelRunCreate(BaseModel):
-    """占位 Run 创建请求：M0 无镜树挂载，prompt 直接作为用户输入。"""
-
-    prompt: str = Field(default="你好，请介绍一下你自己。", min_length=1, max_length=8000)
-    character_id: str | None = Field(default=None, description="缺省用当前激活人物")
-
-
-def _get_kernel(request: Request) -> Kernel:
-    kernel: Kernel | None = getattr(request.app.state, "kernel", None)
-    if kernel is None:
-        from app.core.errors import AppError
-
-        raise AppError("service_unavailable", "Kernel 运行时未就绪。", status_code=503)
-    return kernel
-
-
-@router.post("", response_model=RunResponse, status_code=200)
-async def create_kernel_run(
-    payload: KernelRunCreate,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-    db: AsyncSession = Depends(get_session),
-) -> RunResponse:
-    kernel = _get_kernel(request)
-    character = await resolve_active_character(
-        db, payload.character_id, owner_scope=user.owner_scope
-    )
-    run = await kernel.start_foreground_run(
-        character_id=character.id, prompt=payload.prompt, owner_id=user.owner_scope
-    )
-    return await get_run_response(run.id)

backend/app/api/v1/endpoints/kouxin.py

@@ -1,5 +0,0 @@
-"""叩心路由（域实现见 app/domains/kouxin/api.py）。"""
-
-from app.domains.kouxin.api import knock_router
-
-__all__ = ["knock_router"]

backend/app/api/v1/endpoints/mcp.py

@@ -7,12 +7,15 @@ stdio 模式通过 /start、/stop、/restart 控制子进程生命周期。
 from fastapi import APIRouter, Depends, Query
 from fastapi import status as http_status
 
+from app.api.v1.deps import get_optional_tool_runtime
+from app.application.tool_runtime.runtime import ToolRuntime
 from app.integrations.mcp.process_manager import get_process_manager
 from app.schemas.mcp import (
     CreateMcpServerRequest,
     McpServerResponse,
     McpServerStatusResponse,
-    UpdateMcpServerRequest)
+    UpdateMcpServerRequest,
+)
 from app.services import mcp as mcp_service
 
 router = APIRouter(prefix="/tools/mcp-servers", tags=["mcp"])
@@ -21,9 +24,12 @@ router = APIRouter(prefix="/tools/mcp-servers", tags=["mcp"])
 @router.post(
     "",
     response_model=McpServerResponse,
-    status_code=http_status.HTTP_201_CREATED)
+    status_code=http_status.HTTP_201_CREATED,
+)
 async def register_mcp_server(
-    payload: CreateMcpServerRequest) -> McpServerResponse:
+    payload: CreateMcpServerRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerResponse:
     """注册 MCP server。
 
     streamable-http：同步拉取工具清单并注册到运行时。
@@ -39,23 +45,28 @@ async def register_mcp_server(
         env_json=payload.env_json,
         cwd=payload.cwd,
         status=payload.status,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.get("", response_model=list[McpServerResponse])
 async def list_mcp_servers(
-    status: str | None = Query(default=None, description="按状态过滤：enabled/disabled")) -> list[McpServerResponse]:
+    status: str | None = Query(default=None, description="按状态过滤：enabled/disabled"),
+) -> list[McpServerResponse]:
     """列举 MCP server（含工具清单摘要）。"""
     return await mcp_service.list_mcp_servers(status=status)
 
 
 @router.patch(
     "/{server_id}",
-    response_model=McpServerResponse)
+    response_model=McpServerResponse,
+)
 async def update_mcp_server(
     server_id: str,
-    payload: UpdateMcpServerRequest) -> McpServerResponse:
+    payload: UpdateMcpServerRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerResponse:
     """更新 MCP server 字段（部分更新）。"""
     return await mcp_service.update_mcp_server(
         server_id,
@@ -66,61 +77,79 @@ async def update_mcp_server(
         args_json=payload.args_json,
         env_json=payload.env_json,
         cwd=payload.cwd,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.delete("/{server_id}", status_code=http_status.HTTP_204_NO_CONTENT)
 async def delete_mcp_server(
-    server_id: str) -> None:
+    server_id: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> None:
     """删除 MCP server（先 stop 子进程再删）。"""
     await mcp_service.delete_mcp_server(
         server_id,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.post(
     "/{server_id}/start",
-    response_model=McpServerStatusResponse)
+    response_model=McpServerStatusResponse,
+)
 async def start_mcp_server(
-    server_id: str) -> McpServerStatusResponse:
+    server_id: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerStatusResponse:
     """启动 stdio MCP server 子进程，拉取工具并注册。"""
     return await mcp_service.start_mcp_server(
         server_id,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.post(
     "/{server_id}/stop",
-    response_model=McpServerStatusResponse)
+    response_model=McpServerStatusResponse,
+)
 async def stop_mcp_server(
-    server_id: str) -> McpServerStatusResponse:
+    server_id: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerStatusResponse:
     """停止 stdio MCP server 子进程，注销工具。"""
     return await mcp_service.stop_mcp_server(
         server_id,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.post(
     "/{server_id}/restart",
-    response_model=McpServerStatusResponse)
+    response_model=McpServerStatusResponse,
+)
 async def restart_mcp_server(
-    server_id: str) -> McpServerStatusResponse:
+    server_id: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerStatusResponse:
     """重启 stdio MCP server。"""
     return await mcp_service.restart_mcp_server(
         server_id,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )
 
 
 @router.get(
     "/{server_id}/status",
-    response_model=McpServerStatusResponse)
+    response_model=McpServerStatusResponse,
+)
 async def get_mcp_server_status(
-    server_id: str) -> McpServerStatusResponse:
+    server_id: str,
+) -> McpServerStatusResponse:
     """查询 MCP server 进程状态。"""
     return await mcp_service.get_mcp_server_status(
         server_id,
@@ -130,11 +159,15 @@ async def get_mcp_server_status(
 
 @router.post(
     "/{server_id}/refresh",
-    response_model=McpServerResponse)
+    response_model=McpServerResponse,
+)
 async def refresh_mcp_server_tools(
-    server_id: str) -> McpServerResponse:
+    server_id: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> McpServerResponse:
     """重新拉取 MCP server 工具清单并注册到运行时。"""
     return await mcp_service.refresh_mcp_server_tools(
         server_id,
+        runtime=runtime,
         process_manager=get_process_manager(),
     )

backend/app/api/v1/endpoints/me.py

@@ -1,71 +0,0 @@
-"""用户面 API（神识阁数据源）：BYOK 密钥管理与用量查询。
-
-灵台是神识唯一调用方：本端点鉴权后以 ``X-Hunjing-User-Id`` 代理转发；
-密钥明文只进不出（登记请求体 → 神识加密落库，响应永远脱敏）。
-"""
-
-from fastapi import APIRouter, Depends, Request, status
-
-from app.api.v1.deps import get_current_user
-from app.core.errors import AppError
-from app.kernel import Kernel
-from app.schemas.auth import CurrentUser
-from app.schemas.me import (
-    ByokKeyListResponse,
-    MyUsageResponse,
-    RegisterByokKeyRequest,
-)
-from app.shenshi_client.client import ShenshiClient
-from app.shenshi_client.types import ShenshiError
-
-router = APIRouter(prefix="/me", tags=["me"])
-
-
-def _shenshi(request: Request) -> ShenshiClient:
-    kernel: Kernel | None = getattr(request.app.state, "kernel", None)
-    if kernel is None:
-        raise AppError("service_unavailable", "Kernel 未就绪。", status_code=503)
-    return kernel.shenshi
-
-
-@router.get("/byok-keys", response_model=ByokKeyListResponse)
-async def list_byok_keys(
-    request: Request, user: CurrentUser = Depends(get_current_user)
-) -> ByokKeyListResponse:
-    keys = await _shenshi(request).list_byok_keys(user.owner_scope)
-    return ByokKeyListResponse(keys=keys)
-
-
-@router.post("/byok-keys", status_code=status.HTTP_201_CREATED)
-async def register_byok_key(
-    payload: RegisterByokKeyRequest,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    key = await _shenshi(request).register_byok_key(
-        user.owner_scope,
-        name=payload.name,
-        type=payload.type,
-        base_url=payload.base_url,
-        api_key=payload.api_key,
-        model=payload.model,
-    )
-    return key
-
-
-@router.delete("/byok-keys/{key_id}", status_code=status.HTTP_204_NO_CONTENT)
-async def revoke_byok_key(
-    key_id: str, request: Request, user: CurrentUser = Depends(get_current_user)
-) -> None:
-    try:
-        await _shenshi(request).revoke_byok_key(user.owner_scope, key_id)
-    except ShenshiError as exc:
-        raise AppError(exc.code, exc.message, status_code=404) from None
-
-
-@router.get("/usage", response_model=MyUsageResponse)
-async def my_usage(
-    request: Request, user: CurrentUser = Depends(get_current_user)
-) -> MyUsageResponse:
-    data = await _shenshi(request).get_my_usage(user.owner_scope)
-    return MyUsageResponse(rows=data.get("rows", []), quota=data.get("quota"))

backend/app/api/v1/endpoints/memory.py

@@ -0,0 +1,73 @@
+"""记忆 API。"""
+
+from fastapi import APIRouter, Depends, Header, Query, Request
+
+from app.api.v1.deps import get_current_user
+from app.schemas.auth import CurrentUser
+from app.schemas.common import Page
+from app.schemas.memory import MemoryCreateRequest, MemoryResponse, MemoryUpdateRequest
+from app.services.idempotency import run_idempotent
+from app.services.memory import create_memory, delete_memory, list_memory_page, update_memory
+
+router = APIRouter(prefix="/memory", tags=["memory"])
+
+
+@router.get("", response_model=Page[MemoryResponse])
+async def list_memory(
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+    memory_type: str | None = Query(
+        default=None,
+        alias="type",
+        description="按类型过滤（如 user/assistant/system，契约字典 memory.type）。",
+    ),
+    source: str | None = Query(
+        default=None,
+        description="按来源过滤（如 user_explicit/big_cycle/import，契约字典 memory.source）。",
+    ),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> Page[MemoryResponse]:
+    return await list_memory_page(
+        page=page,
+        page_size=page_size,
+        memory_type=memory_type,
+        source=source,
+        owner_scope=current_user.owner_scope,
+    )
+
+
+@router.post("", response_model=MemoryResponse)
+async def create_memory_api(
+    payload: MemoryCreateRequest,
+    request: Request,
+    idempotency_key: str | None = Header(default=None, alias="Idempotency-Key"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> MemoryResponse:
+    return await run_idempotent(
+        key=idempotency_key,
+        method="POST",
+        path=str(request.url.path),
+        payload=payload,
+        response_type=MemoryResponse,
+        resource_type="memory",
+        handler=lambda session: create_memory(
+            session, payload, owner_scope=current_user.owner_scope
+        ),
+    )
+
+
+@router.patch("/{memory_id}", response_model=MemoryResponse)
+async def update_memory_api(
+    memory_id: str,
+    payload: MemoryUpdateRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> MemoryResponse:
+    return await update_memory(memory_id, payload, owner_scope=current_user.owner_scope)
+
+
+@router.delete("/{memory_id}", response_model=MemoryResponse)
+async def delete_memory_api(
+    memory_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> MemoryResponse:
+    return await delete_memory(memory_id, owner_scope=current_user.owner_scope)

backend/app/api/v1/endpoints/mirror_trees.py

@@ -1,240 +0,0 @@
-"""镜树 API（api-contracts.md §3.3）。树级操作挂 /trees，节点级挂 /nodes 与 /citations。"""
-
-from __future__ import annotations
-
-from fastapi import APIRouter, Depends, Query, Request
-from pydantic import BaseModel, Field
-
-from app.api.v1.deps import get_current_user
-from app.core.errors import AppError
-from app.domains import mirror_tree
-from app.kernel import Kernel
-from app.schemas.auth import CurrentUser
-
-router = APIRouter(prefix="/trees", tags=["mirror-tree"])
-node_router = APIRouter(prefix="/nodes", tags=["mirror-tree"])
-
-
-class TreeCreate(BaseModel):
-    character_id: str
-    title: str = Field(min_length=1, max_length=300)
-    default_realm: str = "reality"
-
-
-class TreePatch(BaseModel):
-    title: str | None = Field(default=None, min_length=1, max_length=300)
-    status: str | None = Field(default=None, description="active / archived")
-
-
-class QuestionCreate(BaseModel):
-    content: str = Field(min_length=1, max_length=20_000)
-    realm: str | None = None
-    parent_answer_id: str | None = None
-    citations: list[dict] = Field(default_factory=list)
-
-
-class AnswerRequest(BaseModel):
-    instructions: str | None = Field(default=None, max_length=8000)
-
-
-class AdoptRequest(BaseModel):
-    node_id: str
-
-
-class CanonizeRequest(BaseModel):
-    endpoint_node_id: str
-    canonical_scope: str
-    world_id: str | None = None
-
-
-class EditForkRequest(BaseModel):
-    new_content: str = Field(min_length=1, max_length=20_000)
-
-
-class TransplantRequest(BaseModel):
-    node_id: str
-    new_title: str = Field(min_length=1, max_length=300)
-
-
-class CitationCreate(BaseModel):
-    target_type: str = "text_range"
-    locator: dict = Field(default_factory=dict)
-    snapshot: str = ""
-    source_id: str = Field(min_length=1, max_length=200)
-    source_version: int = 1
-
-
-def _get_kernel(request: Request) -> Kernel:
-    kernel: Kernel | None = getattr(request.app.state, "kernel", None)
-    if kernel is None:
-        raise AppError("service_unavailable", "Kernel 运行时未就绪。", status_code=503)
-    return kernel
-
-
-@router.get("")
-async def list_trees_api(
-    character_id: str | None = Query(default=None),
-    user: CurrentUser = Depends(get_current_user),
-) -> list[dict]:
-    return [mirror_tree.tree_view(t) for t in await mirror_tree.list_trees(user.owner_scope, character_id)]
-
-
-@router.post("", status_code=201)
-async def create_tree_api(
-    payload: TreeCreate, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    tree = await mirror_tree.create_tree(
-        character_id=payload.character_id, owner_scope=user.owner_scope, title=payload.title,
-        default_realm=payload.default_realm,
-    )
-    return mirror_tree.tree_view(tree)
-
-
-@router.get("/{tree_id}")
-async def get_tree_api(tree_id: str, user: CurrentUser = Depends(get_current_user)) -> dict:
-    return await mirror_tree.get_tree_view(tree_id, user.owner_scope)
-
-
-@router.patch("/{tree_id}")
-async def patch_tree_api(
-    tree_id: str, payload: TreePatch, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    if payload.status == "archived":
-        return await mirror_tree.archive_tree(tree_id, user.owner_scope)
-    if payload.title is not None:
-        return await mirror_tree.rename_tree(tree_id, user.owner_scope, payload.title)
-    return await mirror_tree.get_tree_view(tree_id, user.owner_scope)
-
-
-@router.get("/{tree_id}/path")
-async def tree_path_api(
-    tree_id: str,
-    entry: str | None = Query(default=None),
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    return await mirror_tree.path_view(tree_id, user.owner_scope, entry)
-
-
-@router.get("/{tree_id}/local-graph")
-async def local_graph_api(
-    tree_id: str,
-    node: str | None = Query(default=None),
-    depth: int = Query(default=2, ge=0, le=6),
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    return await mirror_tree.local_graph(tree_id, user.owner_scope, node, depth)
-
-
-@router.post("/{tree_id}/nodes", status_code=201)
-async def create_question_api(
-    tree_id: str, payload: QuestionCreate, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    node = await mirror_tree.create_question(
-        tree_id=tree_id,
-        owner_scope=user.owner_scope,
-        content=payload.content,
-        realm=payload.realm,
-        parent_answer_id=payload.parent_answer_id,
-        citations=payload.citations,
-    )
-    return mirror_tree.node_view(node)
-
-
-@router.post("/{tree_id}/adopt")
-async def adopt_api(
-    tree_id: str, payload: AdoptRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await mirror_tree.adopt(tree_id=tree_id, owner_scope=user.owner_scope, node_id=payload.node_id)
-
-
-@router.post("/{tree_id}/canonize")
-async def canonize_api(
-    tree_id: str, payload: CanonizeRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await mirror_tree.canonize(
-        tree_id=tree_id,
-        owner_scope=user.owner_scope,
-        endpoint_node_id=payload.endpoint_node_id,
-        scope=payload.canonical_scope,
-        world_id=payload.world_id,
-    )
-
-
-@router.post("/{tree_id}/transplant", status_code=201)
-async def transplant_api(
-    tree_id: str, payload: TransplantRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await mirror_tree.transplant(
-        tree_id=tree_id, owner_scope=user.owner_scope, node_id=payload.node_id,
-        new_title=payload.new_title,
-    )
-
-
-# ── 节点级 ──────────────────────────────────────────────
-
-
-@node_router.post("/{node_id}/answers", status_code=202)
-async def spawn_answer_api(
-    node_id: str,
-    payload: AnswerRequest,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    result = await mirror_tree.spawn_answer(
-        question_id=node_id,
-        owner_scope=user.owner_scope,
-        kernel=_get_kernel(request),
-        instructions=payload.instructions,
-    )
-    return result
-
-
-@node_router.post("/{node_id}/continue", status_code=202)
-async def continue_api(
-    node_id: str,
-    payload: AnswerRequest,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    return await mirror_tree.continue_node(
-        node_id=node_id, owner_scope=user.owner_scope, kernel=_get_kernel(request),
-        instructions=payload.instructions,
-    )
-
-
-@node_router.post("/{node_id}/resume", status_code=202)
-async def resume_api(
-    node_id: str,
-    payload: AnswerRequest,
-    request: Request,
-    user: CurrentUser = Depends(get_current_user),
-) -> dict:
-    return await mirror_tree.resume_node(
-        node_id=node_id, owner_scope=user.owner_scope, kernel=_get_kernel(request),
-        instructions=payload.instructions,
-    )
-
-
-@node_router.post("/{node_id}/edit-fork", status_code=201)
-async def edit_fork_api(
-    node_id: str, payload: EditForkRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await mirror_tree.edit_fork(
-        node_id=node_id, owner_scope=user.owner_scope, new_content=payload.new_content
-    )
-
-
-@node_router.post("/{node_id}/citations", status_code=201)
-async def create_citation_api(
-    node_id: str, payload: CitationCreate, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await mirror_tree.create_citation(
-        node_id=node_id, owner_scope=user.owner_scope, data=payload.model_dump()
-    )
-
-
-@node_router.get("/{node_id}/citations")
-async def list_citations_api(
-    node_id: str, user: CurrentUser = Depends(get_current_user)
-) -> list[dict]:
-    return await mirror_tree.list_citations(node_id, user.owner_scope)

backend/app/api/v1/endpoints/personality.py

@@ -0,0 +1,122 @@
+"""人格 API。"""
+
+from fastapi import APIRouter, Depends, Query, status
+
+from app.api.v1.deps import get_current_user
+from app.schemas.auth import CurrentUser
+from app.schemas.common import Page
+from app.schemas.personality import (
+    PersonalityProposalResponse,
+    PersonalityResponse,
+    ProposePersonalityUpdateRequest,
+)
+from app.services.personality import (
+    approve_personality_proposal,
+    get_current_personality,
+    list_personality_proposals,
+    list_personality_versions,
+    propose_personality_update,
+    reject_personality_proposal,
+    rollback_personality,
+)
+
+router = APIRouter(prefix="/personality", tags=["personality"])
+
+
+@router.get("/current", response_model=PersonalityResponse)
+async def current_personality(
+    current_user: CurrentUser = Depends(get_current_user),
+) -> PersonalityResponse:
+    return await get_current_personality(owner_scope=current_user.owner_scope)
+
+
+@router.get("/versions", response_model=Page[PersonalityResponse])
+async def personality_versions(
+    character_id: str | None = Query(default=None, description="人物 ID，省略取当前激活人物。"),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> Page[PersonalityResponse]:
+    return await list_personality_versions(
+        character_id=character_id,
+        page=page,
+        page_size=page_size,
+        owner_scope=current_user.owner_scope,
+    )
+
+
+@router.get("/proposals", response_model=Page[PersonalityProposalResponse])
+async def personality_proposals(
+    character_id: str | None = Query(default=None, description="人物 ID，省略取当前激活人物。"),
+    status: str | None = Query(
+        default=None, description="按状态过滤：pending / approved / rejected / applied"
+    ),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> Page[PersonalityProposalResponse]:
+    """人格修改建议列表（待审审批墙数据源）。"""
+    return await list_personality_proposals(
+        character_id=character_id,
+        status=status,
+        page=page,
+        page_size=page_size,
+        owner_scope=current_user.owner_scope,
+    )
+
+
+# —— 人格修改建议与版本回滚（api-spec §11） ——
+
+
+@router.post(
+    "/propose-update",
+    response_model=PersonalityProposalResponse,
+    status_code=status.HTTP_201_CREATED,
+)
+async def propose_personality_update_endpoint(
+    payload: ProposePersonalityUpdateRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> PersonalityProposalResponse:
+    """提交人格修改建议；进入 pending 待审核，不直接写入人格版本。"""
+    return await propose_personality_update(
+        character_id=payload.character_id,
+        fields=payload.fields,
+        reason=payload.reason,
+        owner_scope=current_user.owner_scope,
+    )
+
+
+@router.post(
+    "/proposals/{proposal_id}/approve",
+    response_model=PersonalityProposalResponse,
+)
+async def approve_proposal(
+    proposal_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> PersonalityProposalResponse:
+    """审核通过人格建议：派生新人格版本并切换人物当前指针。"""
+    return await approve_personality_proposal(proposal_id, owner_scope=current_user.owner_scope)
+
+
+@router.post(
+    "/proposals/{proposal_id}/reject",
+    response_model=PersonalityProposalResponse,
+)
+async def reject_proposal(
+    proposal_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> PersonalityProposalResponse:
+    """驳回人格建议：标记 rejected，不生成新版本。"""
+    return await reject_personality_proposal(proposal_id, owner_scope=current_user.owner_scope)
+
+
+@router.post("/versions/{version_id}/rollback", response_model=PersonalityResponse)
+async def rollback_personality_version(
+    version_id: str,
+    character_id: str | None = Query(default=None, description="人物 ID，省略取当前激活人物。"),
+    current_user: CurrentUser = Depends(get_current_user),
+) -> PersonalityResponse:
+    """回滚到指定人格版本；被取代的旧版本标记 rolled_back_at。"""
+    return await rollback_personality(
+        character_id=character_id, version_id=version_id, owner_scope=current_user.owner_scope
+    )

backend/app/api/v1/endpoints/runs.py

@@ -1,23 +1,32 @@
-"""Run 与 SSE API（Run 的启动契约见 kernel_runs.py）。"""
+"""Run 与 SSE API。"""
 
 import asyncio
 import json
 from collections.abc import AsyncGenerator
 from typing import Any
 
-from fastapi import APIRouter, Header, Query
+from fastapi import APIRouter, Header, Query, Request
 from sse_starlette.sse import EventSourceResponse
 
+from app.application.agent.confirmation import ConfirmationRegistry
+from app.application.agent.run_registry import AgentRunRegistry
 from app.core.config import settings
 from app.core.errors import AppError
 from app.core.time import to_iso, utc_now
 from app.db.session import AsyncSessionLocal
 from app.repositories import runtime as runtime_repo
 from app.schemas.common import Page
-from app.schemas.runtime import EventResponse, RunResponse
+from app.schemas.runtime import (
+    AgentControlRequest,
+    AgentControlResponse,
+    ConfirmationResolutionResponse,
+    EventResponse,
+    RunResponse,
+)
 from app.services.event_bus import bus
 from app.services.runtime import (
     cancel_run,
+    confirmation_exists_in_run,
     get_run_response,
     list_run_event_responses,
     list_runs_response,
@@ -29,6 +38,7 @@ router = APIRouter(prefix="/runs", tags=["runs"])
 @router.get("", response_model=Page[RunResponse])
 async def list_runs(
     character_id: str | None = Query(default=None, description="按人物过滤。"),
+    session_id: str | None = Query(default=None, description="按会话过滤。"),
     status: str | None = Query(default=None, description="按状态过滤。"),
     page: int = Query(default=1, ge=1),
     page_size: int = Query(default=20, ge=1, le=100),
@@ -36,6 +46,7 @@ async def list_runs(
     """Run 列表（按创建时间倒序）；归档页运行时间河数据源。"""
     return await list_runs_response(
         character_id=character_id,
+        session_id=session_id,
         status=status,
         page=page,
         page_size=page_size,
@@ -57,11 +68,107 @@ async def list_run_events(
     return await list_run_event_responses(run_id, limit=limit, offset=offset)
 
 
+def _get_agent_run_registry(request: Request) -> AgentRunRegistry:
+    registry: AgentRunRegistry | None = getattr(request.app.state, "agent_run_registry", None)
+    if registry is None:
+        raise AppError("service_unavailable", "Agent 运行控制未启用。", status_code=503)
+    return registry
+
+
 @router.post("/{run_id}/cancel", response_model=RunResponse)
-async def cancel_run_api(run_id: str) -> RunResponse:
+async def cancel_run_api(run_id: str, request: Request) -> RunResponse:
+    registry = getattr(request.app.state, "agent_run_registry", None)
+    if registry is not None:
+        await registry.abort(run_id)
     return await cancel_run(run_id)
 
 
+@router.post("/{run_id}/steer", response_model=AgentControlResponse)
+async def steer_run(
+    run_id: str,
+    payload: AgentControlRequest,
+    request: Request,
+) -> AgentControlResponse:
+    if not _get_agent_run_registry(request).steer(run_id, payload.content):
+        raise AppError("conflict", "Run 当前不在本进程执行，无法 steer。", status_code=409)
+    return AgentControlResponse()
+
+
+@router.post("/{run_id}/follow-up", response_model=AgentControlResponse)
+async def follow_up_run(
+    run_id: str,
+    payload: AgentControlRequest,
+    request: Request,
+) -> AgentControlResponse:
+    if not _get_agent_run_registry(request).follow_up(run_id, payload.content):
+        raise AppError("conflict", "Run 当前不在本进程执行，无法追加 follow-up。", status_code=409)
+    return AgentControlResponse()
+
+
+def _get_confirmation_registry(request: Request) -> ConfirmationRegistry:
+    """从 app.state 取 ConfirmationRegistry；未挂载时 503。"""
+    registry: ConfirmationRegistry | None = getattr(
+        request.app.state, "confirmation_registry", None
+    )
+    if registry is None:
+        raise AppError(
+            "service_unavailable",
+            "确认机制未启用（进程内 Future 注册表未挂载）",
+            status_code=503,
+        )
+    return registry
+
+
+async def _resolve_confirmation(
+    request: Request,
+    run_id: str,
+    confirmation_id: str,
+    approved: bool,
+) -> ConfirmationResolutionResponse:
+    """approve/deny 共用逻辑：通过 ConfirmationRegistry 更新确认状态。"""
+    registry = _get_confirmation_registry(request)
+    if await registry.resolve(run_id, approved, confirmation_id=confirmation_id):
+        return ConfirmationResolutionResponse(approved=approved)
+
+    # 记录已处理/不存在——查 events 表区分 410 与 404
+    event_store = getattr(request.app.state, "event_store", None)
+    if event_store is not None and await confirmation_exists_in_run(
+        event_store, run_id, confirmation_id
+    ):
+        raise AppError(
+            "confirmation_expired",
+            "确认已失效（服务可能已重启或已处理），请重新发起对话",
+            status_code=410,
+        )
+    raise AppError("confirmation_not_found", "确认项不存在", status_code=404)
+
+
+@router.post(
+    "/{run_id}/confirmations/{confirmation_id}/approve",
+    response_model=ConfirmationResolutionResponse,
+)
+async def approve_confirmation(
+    run_id: str,
+    confirmation_id: str,
+    request: Request,
+) -> ConfirmationResolutionResponse:
+    """批准高风险工具执行：触发 Agent 循环恢复（confirmed=True 重试）。"""
+    return await _resolve_confirmation(request, run_id, confirmation_id, approved=True)
+
+
+@router.post(
+    "/{run_id}/confirmations/{confirmation_id}/deny",
+    response_model=ConfirmationResolutionResponse,
+)
+async def deny_confirmation(
+    run_id: str,
+    confirmation_id: str,
+    request: Request,
+) -> ConfirmationResolutionResponse:
+    """拒绝高风险工具执行：Agent 循环回填拒绝 ToolMessage。"""
+    return await _resolve_confirmation(request, run_id, confirmation_id, approved=False)
+
+
 @router.get("/{run_id}/stream")
 async def stream_run(
     run_id: str,

backend/app/api/v1/endpoints/safety.py

@@ -1,30 +1,162 @@
-"""安全 API（§16）：审计时间线查询。
+"""安全 API（api-spec §16）。
 
-工具策略治理与确认流已由百工域承接（/capabilities /mandates /petitions）；
+audit-events 按人物/枢过滤查询审计时间线；confirmations 的 approve/deny 负责
-本路由保留 audit-events（行动账时间线）。
+高风险工具确认：通过 ConfirmationRegistry 更新工具确认状态唤醒 Agent 循环。
 """
 
 from __future__ import annotations
 
-from fastapi import APIRouter, Depends, Query
+from fastapi import APIRouter, Depends, HTTPException, Query, Response, status
 
-from app.api.v1.deps import get_current_user
+from app.api.v1.deps import get_confirmation_registry, get_optional_tool_runtime
+from app.application.agent.confirmation import ConfirmationRegistry
+from app.application.tool_runtime.runtime import ToolRuntime
 from app.schemas.admin import AuditEntry
-from app.schemas.auth import CurrentUser
 from app.schemas.common import Page
+from app.schemas.safety import (
+    CreateToolPolicyRequest,
+    SafetyPolicyItem,
+    ToolPolicyResponse,
+    UpdateToolPolicyRequest,
+)
 from app.services import audit as audit_service
+from app.services import governance as governance_service
 
 router = APIRouter(prefix="/safety", tags=["safety"])
 
 
+# —— §16 审计事件查询 ——
+
+
 @router.get("/audit-events", response_model=Page[AuditEntry])
 async def list_audit_events(
     character_id: str | None = Query(default=None, description="按人物过滤。"),
     pivot: str | None = Query(default=None, description="按枢过滤（契约字典 §5.9）。"),
     page: int = Query(default=1, ge=1),
     page_size: int = Query(default=50, ge=1, le=200),
-    _user: CurrentUser = Depends(get_current_user),
 ) -> Page[AuditEntry]:
     return await audit_service.query_audit_events(
         character_id=character_id, pivot=pivot, page=page, page_size=page_size
     )
+
+
+# —— §16 工具策略治理 ——
+
+
+async def _refresh_governor(runtime: ToolRuntime | None) -> None:
+    """策略写操作后刷新 ToolRuntime 的司命决策器；tool_runtime 未就绪则跳过（重启后从 db 加载）。"""
+    if runtime is not None:
+        await runtime.reload_governor()
+
+
+@router.get("/policies", response_model=list[SafetyPolicyItem])
+async def list_safety_policies() -> list[SafetyPolicyItem]:
+    return await governance_service.list_safety_policies()
+
+
+@router.post("/policies", response_model=ToolPolicyResponse, status_code=status.HTTP_201_CREATED)
+async def create_safety_policy(
+    payload: CreateToolPolicyRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> ToolPolicyResponse:
+    response = await governance_service.create_tool_policy(payload)
+    await _refresh_governor(runtime)
+    return response
+
+
+@router.patch("/policies/{tool}", response_model=ToolPolicyResponse)
+async def update_safety_policy(
+    tool: str,
+    payload: UpdateToolPolicyRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> ToolPolicyResponse:
+    response = await governance_service.update_tool_policy(tool, payload)
+    await _refresh_governor(runtime)
+    return response
+
+
+@router.delete("/policies/{tool}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_safety_policy(
+    tool: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> Response:
+    await governance_service.delete_tool_policy(tool)
+    await _refresh_governor(runtime)
+    return Response(status_code=status.HTTP_204_NO_CONTENT)
+
+
+# —— §16 高风险工具确认 ——
+
+
+def _not_found(confirmation_id: str) -> HTTPException:
+    return HTTPException(
+        status_code=404,
+        detail={
+            "error": {"code": "not_found", "message": f"确认不存在或已被消费: {confirmation_id}"}
+        },
+    )
+
+
+def _cancelled(confirmation_id: str) -> dict[str, str]:
+    return {"status": "cancelled", "confirmation_id": confirmation_id}
+
+
+@router.post("/confirmations/{confirmation_id}/approve")
+async def approve(
+    confirmation_id: str,
+    registry: ConfirmationRegistry = Depends(get_confirmation_registry),
+) -> dict[str, bool | str]:
+    """批准工具执行。通过 ConfirmationRegistry 唤醒等待的 Agent 循环。"""
+    from sqlalchemy import select
+
+    from app.db.session import AsyncSessionLocal
+    from app.models.safety import PendingConfirmationRecord
+
+    async with AsyncSessionLocal() as session:
+        result = await session.execute(
+            select(PendingConfirmationRecord).where(PendingConfirmationRecord.id == confirmation_id)
+        )
+        record = result.scalar_one_or_none()
+        if record is None or record.run_id is None:
+            raise _not_found(confirmation_id)
+
+    # 更新 resolution 并唤醒进程内 Event
+    ok = await registry.resolve(
+        record.run_id,
+        approved=True,
+        confirmation_id=confirmation_id,
+    )
+    if not ok:
+        raise _not_found(confirmation_id)
+
+    return {"status": "resolved", "approved": True, "run_id": record.run_id}
+
+
+@router.post("/confirmations/{confirmation_id}/deny")
+async def deny(
+    confirmation_id: str,
+    registry: ConfirmationRegistry = Depends(get_confirmation_registry),
+) -> dict[str, str]:
+    """拒绝工具执行。通过 ConfirmationRegistry 通知 Agent 循环。"""
+    from sqlalchemy import select
+
+    from app.db.session import AsyncSessionLocal
+    from app.models.safety import PendingConfirmationRecord
+
+    async with AsyncSessionLocal() as session:
+        result = await session.execute(
+            select(PendingConfirmationRecord).where(PendingConfirmationRecord.id == confirmation_id)
+        )
+        record = result.scalar_one_or_none()
+        if record is None or record.run_id is None:
+            raise _not_found(confirmation_id)
+
+    ok = await registry.resolve(
+        record.run_id,
+        approved=False,
+        confirmation_id=confirmation_id,
+    )
+    if not ok:
+        raise _not_found(confirmation_id)
+
+    return {"status": "cancelled", "confirmation_id": confirmation_id}

backend/app/api/v1/endpoints/sandbox_files.py

@@ -22,9 +22,8 @@ import mimetypes
 from fastapi import APIRouter, Depends, HTTPException, Query
 from starlette.responses import Response
 
-from app.api.v1.deps import get_current_user, get_sandbox_client
+from app.api.v1.deps import get_current_user, get_tool_runtime
-from app.domains.baigong import files as baigong_files
+from app.application.tool_runtime.runtime import ToolRuntime
-from app.integrations.sandbox.client import SandboxClient
 from app.integrations.sandbox.exceptions import SandboxError, SandboxNotFound
 from app.schemas.auth import CurrentUser
 
@@ -55,7 +54,7 @@ async def read_sandbox_file(
         "write_file 写入的文件在 workspace/<character_id>/ 下，"
         "传递 write_file 的 path 时保持 True 即可。",
     ),
-    sandbox: SandboxClient = Depends(get_sandbox_client),
+    runtime: ToolRuntime = Depends(get_tool_runtime),
     _current_user: CurrentUser = Depends(get_current_user),
 ) -> Response:
     """读取沙箱内文件，以原始字节返回（MIME 类型由路径扩展名推导）。
@@ -77,9 +76,8 @@ async def read_sandbox_file(
 
     # 2) 从沙箱读取
     try:
-        result = await baigong_files.read_sandbox_file(
+        result = await runtime.read_sandbox_file(
-            sandbox,
+            path=path,
-            path,
             run_id=run_id,
             character_id=character_id,
             isolated=isolated,
@@ -119,7 +117,7 @@ async def list_sandbox_files(
         description="人物 ID。提供时自动应用 isolated_workspace 隔离前缀。",
     ),
     isolated: bool = Query(True, description="是否自动补全隔离前缀"),
-    sandbox: SandboxClient = Depends(get_sandbox_client),
+    runtime: ToolRuntime = Depends(get_tool_runtime),
     _current_user: CurrentUser = Depends(get_current_user),
 ) -> list[dict[str, object]]:
     """列出沙箱工作区目录内容。
@@ -128,9 +126,8 @@ async def list_sandbox_files(
     适用于前端文件浏览器导航。
     """
     try:
-        entries = await baigong_files.list_sandbox_dir(
+        entries = await runtime.list_sandbox_dir(
-            sandbox,
+            path=path,
-            path,
             run_id=run_id,
             character_id=character_id,
             isolated=isolated,

backend/app/api/v1/endpoints/settings.py

@@ -1,25 +1,60 @@
-"""设置 API（生成偏好）。
+"""设置 API（模型网关状态 + 生成偏好）。
 
-生成偏好可读可写；模型网关状态由神识承接（用户面见神识阁）。
+对应前端 settingsApi。模型网关为只读总览，生成偏好可读可写；
-业务逻辑在 services/preferences（与系统配置 core/config/settings 区分）。
+真实密钥不进入响应。业务逻辑在 services/preferences（与系统配置 core/config/settings 区分）。
 """
 
 from fastapi import APIRouter, Depends
 
 from app.api.v1.deps import get_current_user
+from app.core.errors import AppError
 from app.schemas.auth import CurrentUser
 from app.schemas.preferences import (
     GenerationPreferencesResponse,
+    ModelEndpointStatus,
+    ModelGatewayStatus,
+    UpdateEndpointOverrideRequest,
     UpdateGenerationPreferencesRequest,
 )
+from app.services.ai_provider_admin import update_endpoint_override
 from app.services.preferences import (
     get_generation_preferences,
+    get_provider_gateway,
     update_generation_preferences,
 )
 
 router = APIRouter(prefix="/settings", tags=["settings"])
 
 
+@router.get("/models", response_model=ModelGatewayStatus)
+async def read_provider_gateway() -> ModelGatewayStatus:
+    return get_provider_gateway()
+
+
+@router.patch(
+    "/models/{model}/endpoints/{endpoint}",
+    response_model=ModelEndpointStatus,
+)
+async def update_model_endpoint(
+    model: str,
+    endpoint: str,
+    payload: UpdateEndpointOverrideRequest,
+) -> ModelEndpointStatus:
+    """更新 endpoint 覆盖（base_url / api_key / status / weight / priority，DB 优先 env）。
+
+    写后热重载 registry（reset_model_router）。响应脱敏，不回 base_url / api_key 原值。
+    """
+    await update_endpoint_override(model, endpoint, payload)
+    gateway = get_provider_gateway()
+    for m in gateway.models:
+        if m.name != model:
+            continue
+        for ep in m.endpoints or []:
+            if ep.name == endpoint:
+                return ep
+    raise AppError("not_found", "endpoint 不存在。")
+
+
 @router.get("/preferences", response_model=GenerationPreferencesResponse)
 async def read_generation_preferences(
     current_user: CurrentUser = Depends(get_current_user),

backend/app/api/v1/endpoints/skills.py

@@ -0,0 +1,54 @@
+"""Skill 能力包 API（/tools/skills，skills-design §6）。"""
+
+from fastapi import APIRouter, Query, status
+
+from app.schemas.skills import (
+    CreateSkillRequest,
+    SkillResponse,
+    UpdateSkillRequest,
+)
+from app.services import skills as skills_service
+
+router = APIRouter(prefix="/tools/skills", tags=["skills"])
+
+
+@router.post("", response_model=SkillResponse, status_code=status.HTTP_201_CREATED)
+async def create_skill(payload: CreateSkillRequest) -> SkillResponse:
+    """注册 Skill 能力包（name 唯一）。"""
+    return await skills_service.create_skill(
+        name=payload.name,
+        description=payload.description,
+        trigger=payload.trigger,
+        prompt_fragment=payload.prompt_fragment,
+        tool_bindings=payload.tool_bindings,
+        risk_level=payload.risk_level,
+        status=payload.status,
+    )
+
+
+@router.get("", response_model=list[SkillResponse])
+async def list_skills(
+    status: str | None = Query(default=None, description="按状态过滤：enabled/disabled"),
+) -> list[SkillResponse]:
+    """列举 Skill（可按 status 过滤）。"""
+    return await skills_service.list_skills(status=status)
+
+
+@router.patch("/{skill_id}", response_model=SkillResponse)
+async def update_skill(skill_id: str, payload: UpdateSkillRequest) -> SkillResponse:
+    """更新 / 启用 / 禁用 Skill。"""
+    return await skills_service.update_skill(
+        skill_id,
+        description=payload.description,
+        trigger=payload.trigger,
+        prompt_fragment=payload.prompt_fragment,
+        tool_bindings=payload.tool_bindings,
+        risk_level=payload.risk_level,
+        status=payload.status,
+    )
+
+
+@router.delete("/{skill_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_skill(skill_id: str) -> None:
+    """删除 Skill。"""
+    await skills_service.delete_skill(skill_id)

backend/app/api/v1/endpoints/soul.py

@@ -1,72 +0,0 @@
-"""道体铸魂与分灵 API（/characters/{id}/soul）。"""
-
-from fastapi import APIRouter, Depends
-from pydantic import BaseModel, Field
-
-from app.api.v1.deps import get_current_user
-from app.domains.jingsheng import soul
-from app.schemas.auth import CurrentUser
-
-soul_router = APIRouter(prefix="/characters/{character_id}/soul", tags=["jingsheng"])
-
-
-class ForgingRequest(BaseModel):
-    anchor_changes: dict = Field(description="道体锚点变更（键：identity_baseline_json）")
-    reason: str = Field(min_length=1, max_length=2000)
-
-
-class SplitRequest(BaseModel):
-    reason: str = Field(min_length=1, max_length=2000)
-    initial_anchor: dict = Field(default_factory=dict)
-
-
-@soul_router.get("/forgings")
-async def list_forgings(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> list[dict]:
-    return await soul.list_forgings(character_id, user.owner_scope)
-
-
-@soul_router.post("/forgings", status_code=201)
-async def propose_forging(
-    character_id: str, payload: ForgingRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await soul.propose_forging(
-        character_id=character_id,
-        owner_scope=user.owner_scope,
-        anchor_changes=payload.anchor_changes,
-        reason=payload.reason,
-    )
-
-
-@soul_router.post("/forgings/{forging_id}/confirm")
-async def confirm_forging(
-    character_id: str, forging_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await soul.confirm_forging(forging_id, user.owner_scope)
-
-
-@soul_router.post("/forgings/{forging_id}/reject")
-async def reject_forging(
-    character_id: str, forging_id: str, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await soul.reject_forging(forging_id, user.owner_scope)
-
-
-@soul_router.post("/split", status_code=201)
-async def split_soul(
-    character_id: str, payload: SplitRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    return await soul.split_soul(
-        character_id=character_id,
-        owner_scope=user.owner_scope,
-        reason=payload.reason,
-        initial_anchor=payload.initial_anchor,
-    )
-
-
-@soul_router.get("/lineage")
-async def get_lineage(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> list[dict]:
-    return await soul.get_lineage(character_id, user.owner_scope)

backend/app/api/v1/endpoints/tiangong.py

@@ -1,5 +0,0 @@
-"""天工阁路由（域实现见 app/domains/tiangong/api.py）。"""
-
-from app.domains.tiangong.api import task_router
-
-__all__ = ["task_router"]

backend/app/api/v1/endpoints/tianzai.py

@@ -1,5 +0,0 @@
-"""器谱路由（域实现见 app/domains/tianzai/api.py）。"""
-
-from app.domains.tianzai.api import device_router
-
-__all__ = ["device_router"]

backend/app/api/v1/endpoints/time.py

@@ -0,0 +1,113 @@
+"""辰正时态 API（设计 §10）。
+
+挂载于 /api/v1/time。事件不走 REST（走 EventStore 订阅）。路由薄层：参数校验 → 调
+service → 转响应；session 由 service 自管（deps.py 惯例）。
+"""
+
+from fastapi import APIRouter, Depends, Request
+
+from app.api.v1.deps import get_current_user, get_event_store
+from app.core.config import settings
+from app.schemas.auth import CurrentUser
+from app.schemas.time import (
+    AcquaintanceResponse,
+    AnniversaryCreateRequest,
+    AnniversaryResponse,
+    AnniversaryUpdateRequest,
+    SnapshotResponse,
+    TimeConfigResponse,
+)
+from app.services.time_sense import (
+    create_anniversary_for_active,
+    delete_anniversary_or_404,
+    get_acquaintance_for_active,
+    get_anniversary_or_404,
+    get_live_snapshot,
+    list_anniversaries_for_active,
+    update_anniversary_or_404,
+)
+
+router = APIRouter(prefix="/time", tags=["time"])
+
+
+@router.get("/snapshot", response_model=SnapshotResponse)
+async def get_snapshot(
+    request: Request, current_user: CurrentUser = Depends(get_current_user)
+) -> SnapshotResponse:
+    """当前 TemporalSnapshot + ModulationFactors + context_text。"""
+    result = await get_live_snapshot(get_event_store(request), owner_scope=current_user.owner_scope)
+    return SnapshotResponse(
+        snapshot=result.snapshot,
+        factors=result.factors,
+        context_text=result.context_text,
+    )
+
+
+@router.get("/anniversaries", response_model=list[AnniversaryResponse])
+async def list_anniversaries_api(
+    current_user: CurrentUser = Depends(get_current_user),
+) -> list[AnniversaryResponse]:
+    items = await list_anniversaries_for_active(owner_scope=current_user.owner_scope)
+    return [AnniversaryResponse.model_validate(a) for a in items]
+
+
+@router.post("/anniversaries", response_model=AnniversaryResponse, status_code=201)
+async def create_anniversary_api(
+    payload: AnniversaryCreateRequest, current_user: CurrentUser = Depends(get_current_user)
+) -> AnniversaryResponse:
+    created = await create_anniversary_for_active(payload, owner_scope=current_user.owner_scope)
+    return AnniversaryResponse.model_validate(created)
+
+
+@router.get("/anniversaries/{anniv_id}", response_model=AnniversaryResponse)
+async def get_anniversary_api(
+    anniv_id: str, current_user: CurrentUser = Depends(get_current_user)
+) -> AnniversaryResponse:
+    return AnniversaryResponse.model_validate(
+        await get_anniversary_or_404(anniv_id, owner_scope=current_user.owner_scope)
+    )
+
+
+@router.patch("/anniversaries/{anniv_id}", response_model=AnniversaryResponse)
+async def update_anniversary_api(
+    anniv_id: str,
+    payload: AnniversaryUpdateRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> AnniversaryResponse:
+    return AnniversaryResponse.model_validate(
+        await update_anniversary_or_404(anniv_id, payload, owner_scope=current_user.owner_scope)
+    )
+
+
+@router.delete("/anniversaries/{anniv_id}", status_code=204)
+async def delete_anniversary_api(
+    anniv_id: str, current_user: CurrentUser = Depends(get_current_user)
+) -> None:
+    await delete_anniversary_or_404(anniv_id, owner_scope=current_user.owner_scope)
+
+
+@router.get("/acquaintance", response_model=AcquaintanceResponse)
+async def get_acquaintance_api(
+    request: Request, current_user: CurrentUser = Depends(get_current_user)
+) -> AcquaintanceResponse:
+    acq = await get_acquaintance_for_active(
+        get_event_store(request), owner_scope=current_user.owner_scope
+    )
+    return AcquaintanceResponse(total_days=acq.total_days, natural_language=acq.natural_language)
+
+
+@router.get("/config", response_model=TimeConfigResponse)
+async def get_time_config_api(
+    current_user: CurrentUser = Depends(get_current_user),  # noqa: ARG001
+) -> TimeConfigResponse:
+    return TimeConfigResponse(
+        user_timezone=settings.user_timezone,
+        home_timezone=settings.home_timezone,
+        default_city=settings.default_city,
+        offline_active_minutes=settings.offline_active_minutes,
+        offline_short_absence_minutes=settings.offline_short_absence_minutes,
+        offline_long_absence_minutes=settings.offline_long_absence_minutes,
+        offline_reunion_impact_minutes=settings.offline_reunion_impact_minutes,
+        care_enabled=settings.care_enabled,
+        jetlag_threshold_minutes=settings.jetlag_threshold_minutes,
+    )

backend/app/api/v1/endpoints/tools.py

@@ -1,37 +1,252 @@
-"""工具 API（§15 兼容面）：清单走百工能力目录，调用走 /capabilities/{id}/invoke。
+"""工具调用 API（api-spec §15）。
 
-旧 ToolRuntime/策略治理端点已随 M5 百工重写退役；本路由只保留
+- GET /tools：列出已注册工具策略元数据（从 tool_policies 表，含 executable 派生）。
-`/tools`（能力目录投影）与 `/tools/calls/{id}`（一炁事件详情）。
+- POST /tools：注册自定义工具策略（百工枢器用治理声明，记审计）。
+- GET /tools/calls/{tool_call_id}：单次工具调用事件详情。
+- PATCH /tools/{tool_name}：编辑工具策略元数据（spec §15: risk_level 等）。
+- DELETE /tools/{tool_name}：注销自定义工具（builtin 不可删）。
+- POST /tools/{tool_name}/invoke：调用工具；高风险返回 requires_confirmation + confirmation_id，
+  交由 /safety/confirmations/{id}/approve 消费。
+- POST /tools/{tool_name}/invoke/stream：流式调用（SSE），实时推送 tool.stdout/tool.stderr
+  增量与 tool.completed；司命 deny/ask-未确认/沙箱错误分别以 tool.failed / tool.requires_confirmation 结束流。
+
+策略写操作（POST/PATCH/DELETE）后刷新 ToolRuntime 的司命决策器，使变更即时生效；
+tool_runtime 未就绪时仅写库（重启后从 db 加载）。
 """
 
-from fastapi import APIRouter, Depends
+from __future__ import annotations
 
-from app.api.v1.deps import get_current_user
+import json
-from app.domains.baigong import service as baigong
+from typing import Any
-from app.schemas.auth import CurrentUser
+
-from app.schemas.safety import ToolCallDetail
+from fastapi import APIRouter, Depends, Response, status
-from app.services.runtime import get_tool_call_detail
+from pydantic import BaseModel
+from sse_starlette.sse import EventSourceResponse
+
+from app.api.v1.deps import get_confirmation_store, get_optional_tool_runtime, get_tool_runtime
+from app.application.tool_runtime.runtime import ToolRuntime
+from app.db.session import AsyncSessionLocal
+from app.integrations.sandbox.exceptions import SandboxError
+from app.models.safety import PendingConfirmationRecord
+from app.modules.safety.confirmation import (
+    ConfirmationStore,
+    PendingConfirmation,
+    new_confirmation_id,
+)
+from app.modules.safety.exceptions import PermissionDenied, RequiresConfirmation
+from app.schemas.safety import (
+    CreateToolPolicyRequest,
+    ToolCallDetail,
+    ToolPolicyResponse,
+    UpdateToolPolicyRequest,
+)
+from app.schemas.skills import ToolCapability
+from app.services import governance as governance_service
+from app.services import skills as skills_service
 
 router = APIRouter(prefix="/tools", tags=["tools"])
 
 
-@router.get("")
+class InvokeRequest(BaseModel):
-async def list_tools(user: CurrentUser = Depends(get_current_user)) -> list[dict]:
+    input: dict[str, Any]
-    """能力目录投影（新链路以 /capabilities 为准；此处给旧消费方过渡读取）。"""
+    run_id: str | None = None
-    caps = await baigong.list_capabilities(user.owner_scope)
+    character_id: str | None = None
-    return [
+    trace_id: str | None = None
-        {
+    confirmed: bool = False
-            "name": c["name"],
+
-            "description": c["description"],
+
-            "risk_level": max(c["risk_dims"].values(), default="L1"),
+class ToolResultPayload(BaseModel):
-            "permission_policy": "ask" if c["consent_mode"] == "ask" else "allow",
+    ok: bool
-            "enabled": c["enabled"],
+    exit_code: int | None = None
-            "source": c["source"],
+    stdout: str = ""
-        }
+    stderr: str = ""
-        for c in caps
+    duration_ms: int = 0
-    ]
+    timeout: bool = False
+    truncated: bool = False
+    trace_id: str = ""
+
+
+class CompletedResponse(BaseModel):
+    status: str = "completed"
+    result: ToolResultPayload
+
+
+class RequiresConfirmationResponse(BaseModel):
+    status: str = "requires_confirmation"
+    confirmation_id: str
+    risk_level: str
+    reason: str
+
+
+async def _sync_confirmation_record(pending: PendingConfirmation) -> None:
+    """把 InMemoryConfirmationStore 的待确认记录同步持久化到 DB。"""
+    async with AsyncSessionLocal() as session:
+        record = PendingConfirmationRecord(
+            id=pending.confirmation_id,
+            tool=pending.tool,
+            input_json=json.dumps(pending.input) if pending.input else "{}",
+            risk_level=pending.risk_level,
+            reason=pending.reason or "",
+            run_id=pending.run_id,
+            character_id=pending.character_id,
+            trace_id=pending.trace_id,
+            status="pending",
+        )
+        session.add(record)
+        await session.commit()
+
+
+# —— §15 工具策略治理 ——
+
+
+@router.get("", response_model=list[ToolPolicyResponse])
+async def list_tools() -> list[ToolPolicyResponse]:
+    return await governance_service.list_tool_policies()
+
+
+@router.get("/capabilities", response_model=list[ToolCapability])
+async def list_capabilities(
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> list[ToolCapability]:
+    """统一列举所有能力（builtin / mcp / skill，含来源标记，skills-design §6）。"""
+    return await skills_service.list_all_capabilities(runtime)
+
+
+@router.post("", response_model=ToolPolicyResponse, status_code=status.HTTP_201_CREATED)
+async def register_tool(
+    payload: CreateToolPolicyRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> ToolPolicyResponse:
+    response = await governance_service.create_tool_policy(payload)
+    if runtime is not None:
+        await runtime.reload_governor()
+    return response
 
 
 @router.get("/calls/{tool_call_id}", response_model=ToolCallDetail)
-async def get_tool_call_detail(tool_call_id: str) -> ToolCallDetail:
+async def get_tool_call(tool_call_id: str) -> ToolCallDetail:
-    return await get_tool_call_detail(tool_call_id)
+    return await governance_service.get_tool_call(tool_call_id)
+
+
+@router.patch("/{tool_name}", response_model=ToolPolicyResponse)
+async def update_tool(
+    tool_name: str,
+    payload: UpdateToolPolicyRequest,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> ToolPolicyResponse:
+    response = await governance_service.update_tool_policy(tool_name, payload)
+    if runtime is not None:
+        await runtime.reload_governor()
+    return response
+
+
+@router.delete("/{tool_name}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_tool(
+    tool_name: str,
+    runtime: ToolRuntime | None = Depends(get_optional_tool_runtime),
+) -> Response:
+    await governance_service.delete_tool_policy(tool_name)
+    if runtime is not None:
+        await runtime.reload_governor()
+    return Response(status_code=status.HTTP_204_NO_CONTENT)
+
+
+# —— §15 工具调用 ——
+
+
+@router.post("/{tool_name}/invoke", response_model=None)
+async def invoke_tool(
+    tool_name: str,
+    body: InvokeRequest,
+    runtime: ToolRuntime = Depends(get_tool_runtime),
+    confirmations: ConfirmationStore = Depends(get_confirmation_store),
+) -> CompletedResponse | RequiresConfirmationResponse:
+    try:
+        result = await runtime.execute(
+            tool_name,
+            body.input,
+            run_id=body.run_id,
+            character_id=body.character_id,
+            trace_id=body.trace_id,
+            confirmed=body.confirmed,
+        )
+    except RequiresConfirmation as exc:
+        pending = await confirmations.create(
+            PendingConfirmation(
+                confirmation_id=new_confirmation_id(),
+                tool=tool_name,
+                input=body.input,
+                risk_level=exc.risk_level or "L2",
+                reason=exc.message,
+                run_id=body.run_id,
+                character_id=body.character_id,
+                trace_id=body.trace_id,
+            )
+        )
+        # 同步持久化 PendingConfirmationRecord（供 safety/confirmations 新端点查找）
+        await _sync_confirmation_record(pending)
+        return RequiresConfirmationResponse(
+            confirmation_id=pending.confirmation_id,
+            risk_level=pending.risk_level,
+            reason=pending.reason,
+        )
+
+    return CompletedResponse(
+        result=ToolResultPayload(
+            ok=result.ok,
+            exit_code=result.exit_code,
+            stdout=result.stdout,
+            stderr=result.stderr,
+            duration_ms=result.duration_ms,
+            timeout=result.timeout,
+            truncated=result.truncated,
+            trace_id=result.trace_id,
+        )
+    )
+
+
+@router.post("/{tool_name}/invoke/stream")
+async def invoke_tool_stream(
+    tool_name: str,
+    body: InvokeRequest,
+    runtime: ToolRuntime = Depends(get_tool_runtime),
+) -> EventSourceResponse:
+    """流式调用工具（SSE）。
+
+    事件：``tool.stdout`` / ``tool.stderr``（data 为 ``{"data":"<base64>"}``，前端解码）、
+    ``tool.completed``（data 为结束汇总 JSON）。司命 deny → ``tool.failed``；
+    ask 且未确认 → ``tool.requires_confirmation``（前端应先走非流式 invoke 完成 confirmation，
+    再以 confirmed=True 调用本端点）；沙箱错误 → ``tool.failed``。
+    """
+
+    async def event_gen():
+        try:
+            async for ev in runtime.execute_stream(
+                tool_name,
+                body.input,
+                run_id=body.run_id,
+                character_id=body.character_id,
+                trace_id=body.trace_id,
+                confirmed=body.confirmed,
+            ):
+                if ev.kind in ("stdout", "stderr"):
+                    yield {"event": f"tool.{ev.kind}", "data": json.dumps({"data": ev.payload})}
+                elif ev.kind == "done":
+                    yield {"event": "tool.completed", "data": json.dumps(ev.payload)}
+        except RequiresConfirmation as exc:
+            yield {
+                "event": "tool.requires_confirmation",
+                "data": json.dumps({"risk_level": exc.risk_level, "reason": exc.message}),
+            }
+        except PermissionDenied as exc:
+            yield {
+                "event": "tool.failed",
+                "data": json.dumps({"error_code": "permission_denied", "error_message": str(exc)}),
+            }
+        except SandboxError as exc:
+            yield {
+                "event": "tool.failed",
+                "data": json.dumps({"error_code": exc.code, "error_message": str(exc)}),
+            }
+
+    return EventSourceResponse(event_gen())

backend/app/api/v1/endpoints/world.py

@@ -0,0 +1,95 @@
+"""世界模型 API（河图枢运行时，api-spec §12）。"""
+
+from fastapi import APIRouter, Depends, Query
+
+from app.api.v1.deps import get_current_user
+from app.schemas.auth import CurrentUser
+from app.schemas.common import Page
+from app.schemas.world import (
+    WorldEntityCreateRequest,
+    WorldEntityResponse,
+    WorldGraphResponse,
+    WorldRelationCreateRequest,
+    WorldRelationResponse,
+)
+from app.services.world import (
+    create_entity,
+    create_relation,
+    delete_relation,
+    get_entity_by_id,
+    get_graph,
+    list_entities_page,
+    list_relations_page,
+)
+
+router = APIRouter(prefix="/world", tags=["world"])
+
+
+@router.get("/entities", response_model=Page[WorldEntityResponse])
+async def list_entities(
+    current_user: CurrentUser = Depends(get_current_user),
+    character_id: str | None = Query(default=None, description="所属人物；省略取当前激活。"),
+    type: str | None = Query(default=None, description="按实体类型过滤（契约字典 §11.1）。"),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[WorldEntityResponse]:
+    return await list_entities_page(
+        character_id,
+        entity_type=type,
+        page=page,
+        page_size=page_size,
+        owner_scope=current_user.owner_scope,
+    )
+
+
+@router.post("/entities", response_model=WorldEntityResponse)
+async def create_entity_api(
+    payload: WorldEntityCreateRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> WorldEntityResponse:
+    return await create_entity(payload, owner_scope=current_user.owner_scope)
+
+
+@router.get("/entities/{entity_id}", response_model=WorldEntityResponse)
+async def get_entity(
+    entity_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> WorldEntityResponse:
+    return await get_entity_by_id(entity_id, owner_scope=current_user.owner_scope)
+
+
+@router.get("/relations", response_model=Page[WorldRelationResponse])
+async def list_relations(
+    current_user: CurrentUser = Depends(get_current_user),
+    character_id: str | None = Query(default=None, description="所属人物；省略取当前激活。"),
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=20, ge=1, le=100),
+) -> Page[WorldRelationResponse]:
+    return await list_relations_page(
+        character_id, page=page, page_size=page_size, owner_scope=current_user.owner_scope
+    )
+
+
+@router.post("/relations", response_model=WorldRelationResponse)
+async def create_relation_api(
+    payload: WorldRelationCreateRequest,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> WorldRelationResponse:
+    return await create_relation(payload, owner_scope=current_user.owner_scope)
+
+
+@router.delete("/relations/{relation_id}", status_code=204)
+async def delete_relation_api(
+    relation_id: str,
+    current_user: CurrentUser = Depends(get_current_user),
+) -> None:
+    await delete_relation(relation_id, owner_scope=current_user.owner_scope)
+
+
+@router.get("/graph", response_model=WorldGraphResponse)
+async def world_graph(
+    current_user: CurrentUser = Depends(get_current_user),
+    character_id: str | None = Query(default=None, description="所属人物；省略取当前激活。"),
+) -> WorldGraphResponse:
+    """返回人物的完整世界图谱（无分页），供前端 D3/Force 图谱渲染。"""
+    return await get_graph(character_id, owner_scope=current_user.owner_scope)

backend/app/api/v1/endpoints/xingyi.py

@@ -1,5 +0,0 @@
-"""形仪路由（域实现见 app/domains/xingyi/api.py）。"""
-
-from app.domains.xingyi.api import form_router
-
-__all__ = ["form_router"]

backend/app/api/v1/endpoints/xirang.py

@@ -1,157 +0,0 @@
-"""息壤（记忆域）API（api-contracts §3.5）。"""
-
-from __future__ import annotations
-
-import json
-
-from fastapi import APIRouter, Depends, Query
-from pydantic import BaseModel, Field
-from sqlalchemy import select
-
-from app.api.v1.deps import get_current_user
-from app.core.errors import AppError
-from app.db.session import AsyncSessionLocal
-from app.domains import xirang
-from app.models.character import Character
-from app.models.xirang import FactualRecord, Memory
-from app.schemas.auth import CurrentUser
-
-router = APIRouter(tags=["xirang"])
-
-
-class MemorizeRequest(BaseModel):
-    label: str = Field(description="fact / insight / opinion / hypothesis")
-
-
-class CorrectRequest(BaseModel):
-    new_content: str = Field(min_length=1, max_length=8000)
-
-
-def _memory_view(m: Memory, with_content: bool = True) -> dict:
-    return {
-        "id": m.id,
-        "character_id": m.character_id,
-        "tier": m.tier,
-        "type": m.type,
-        "status": m.status,
-        "source": m.source,
-        "content": m.content if with_content else "",
-        "source_refs": json.loads(m.source_refs_json or "[]"),
-        "sensitivity": m.sensitivity,
-        "priority": m.priority,
-        "confidence": m.confidence,
-        "vitality": round(m.vitality, 3),
-        "realm": m.realm,
-        "prev_version_id": m.prev_version_id,
-        "recall_count": m.recall_count,
-        "last_recalled_at": m.last_recalled_at.isoformat() if m.last_recalled_at else None,
-        "created_at": m.created_at.isoformat(),
-    }
-
-
-async def _owned_character(character_id: str, owner_scope: str) -> Character:
-    async with AsyncSessionLocal() as session:
-        character = await session.get(Character, character_id)
-    if character is None or character.owner_scope != owner_scope:
-        raise AppError("not_found", "人物不存在。")
-    return character
-
-
-@router.get("/characters/{character_id}/memories")
-async def list_memories(
-    character_id: str,
-    tier: str | None = Query(default=None),
-    status: str | None = Query(default=None),
-    type_: str | None = Query(default=None, alias="type"),
-    user: CurrentUser = Depends(get_current_user),
-) -> list[dict]:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        stmt = select(Memory).where(Memory.character_id == character_id)
-        if tier:
-            stmt = stmt.where(Memory.tier == tier)
-        if status:
-            stmt = stmt.where(Memory.status == status)
-        if type_:
-            stmt = stmt.where(Memory.type == type_)
-        stmt = stmt.order_by(Memory.created_at.desc()).limit(200)
-        rows = (await session.execute(stmt)).scalars().all()
-    # 高敏不展示原文（sensitivity=high 摘要化）；墓碑不承载原文
-    return [
-        _memory_view(
-            m,
-            with_content=not (m.sensitivity == "high" or m.status == "tombstoned"),
-        )
-        for m in rows
-    ]
-
-
-@router.get("/memories/{memory_id}")
-async def get_memory(memory_id: str, user: CurrentUser = Depends(get_current_user)) -> dict:
-    async with AsyncSessionLocal() as session:
-        memory = await session.get(Memory, memory_id)
-        if memory is not None:
-            character = await session.get(Character, memory.character_id)
-    if memory is None or character is None or character.owner_scope != user.owner_scope:
-        raise AppError("not_found", "记忆不存在。")
-    return _memory_view(memory)
-
-
-@router.post("/memories/{memory_id}/confirm")
-async def confirm_memory_api(memory_id: str, user: CurrentUser = Depends(get_current_user)) -> dict:
-    memory = await xirang.confirm_memory(memory_id, user.owner_scope)
-    return _memory_view(memory)
-
-
-@router.post("/memories/{memory_id}/deny")
-async def deny_memory_api(memory_id: str, user: CurrentUser = Depends(get_current_user)) -> dict:
-    return await xirang.deny_memory(memory_id, user.owner_scope)
-
-
-@router.post("/memories/{memory_id}/correct")
-async def correct_memory_api(
-    memory_id: str, payload: CorrectRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    memory = await xirang.correct_memory(memory_id, user.owner_scope, payload.new_content)
-    return _memory_view(memory)
-
-
-@router.delete("/memories/{memory_id}", status_code=204)
-async def delete_memory_api(memory_id: str, user: CurrentUser = Depends(get_current_user)) -> None:
-    await xirang.delete_memory(memory_id, user.owner_scope)
-
-
-@router.post("/nodes/{node_id}/memorize", status_code=201)
-async def memorize_node_api(
-    node_id: str, payload: MemorizeRequest, user: CurrentUser = Depends(get_current_user)
-) -> dict:
-    memory = await xirang.memorize_node(
-        node_id=node_id, owner_scope=user.owner_scope, label=payload.label
-    )
-    return _memory_view(memory)
-
-
-@router.get("/characters/{character_id}/factual-records")
-async def list_factual_records(
-    character_id: str, user: CurrentUser = Depends(get_current_user)
-) -> list[dict]:
-    await _owned_character(character_id, user.owner_scope)
-    async with AsyncSessionLocal() as session:
-        rows = (
-            await session.execute(
-                select(FactualRecord)
-                .where(FactualRecord.character_id == character_id)
-                .order_by(FactualRecord.occurred_at.desc())
-                .limit(100)
-            )
-        ).scalars().all()
-    return [
-        {
-            "id": r.id,
-            "canonization_id": r.canonization_id,
-            "summary": r.summary,
-            "evidence": json.loads(r.evidence_json or "{}"),
-            "occurred_at": r.occurred_at.isoformat(),
-        }
-        for r in rows
-    ]

backend/app/api/v1/endpoints/yuanqi.py

@@ -1,5 +0,0 @@
-"""缘契路由（域实现见 app/domains/yuanqi/api.py）。"""
-
-from app.domains.yuanqi.api import cov_router
-
-__all__ = ["cov_router"]

backend/app/application/agent/__init__.py

@@ -0,0 +1,82 @@
+"""非流式 Agent 应用层：工具调用闭环编排。
+
+入口：
+    - ``run_agent_turn`` 执行一轮带工具调用的对话循环
+    - ``AgentTurnResult`` 循环产出
+    - ``to_ai_provider_tools`` 把 ToolSpec 转成 OpenAI function schema dict
+    - ``default_tools`` 返回全部内置工具（依赖司命 + 确认流控风险）
+"""
+
+from app.application.agent.agent import (
+    Agent,
+    AgentConfig,
+    AgentState,
+    AgentStatus,
+    PendingMessageQueue,
+    QueueMode,
+)
+from app.application.agent.confirmation import ConfirmationRegistry
+from app.application.agent.extensions import (
+    AfterToolCallDecision,
+    AgentContext,
+    AgentEvent,
+    AgentRunContext,
+    BeforeToolCallDecision,
+    CancellationToken,
+    ExtensionRegistry,
+    ToolCallContext,
+    TurnSnapshot,
+)
+from app.application.agent.prompt_composer import compose_system_messages
+from app.application.agent.python_skills import (
+    PythonSkillActivation,
+    PythonSkillCatalog,
+    PythonSkillDefinition,
+    activate_python_skills,
+    discover_python_skills,
+)
+from app.application.agent.run_registry import AgentRunRegistry
+from app.application.agent.runtime import AgentTurnResult, run_agent_turn
+from app.application.agent.skill_loader import load_skill_manifests
+from app.application.agent.tasks import (
+    next_step_for_tool,
+    step_event_payload,
+    task_from_deliberative_plan,
+    task_plan_payload,
+)
+from app.application.agent.tools import default_tools, to_ai_provider_tools
+
+__all__ = [
+    "AfterToolCallDecision",
+    "Agent",
+    "AgentConfig",
+    "AgentContext",
+    "AgentEvent",
+    "AgentRunContext",
+    "AgentRunRegistry",
+    "AgentState",
+    "AgentStatus",
+    "AgentTurnResult",
+    "BeforeToolCallDecision",
+    "CancellationToken",
+    "ConfirmationRegistry",
+    "ExtensionRegistry",
+    "PendingMessageQueue",
+    "PythonSkillActivation",
+    "PythonSkillCatalog",
+    "PythonSkillDefinition",
+    "QueueMode",
+    "ToolCallContext",
+    "TurnSnapshot",
+    "activate_python_skills",
+    "compose_system_messages",
+    "default_tools",
+    "discover_python_skills",
+    "load_skill_manifests",
+    "next_step_for_tool",
+    "run_agent_turn",
+    "step_event_payload",
+    "task_from_deliberative_plan",
+    "task_plan_payload",
+    "to_ai_provider_tools",
+]

backend/app/application/agent/agent.py

@@ -0,0 +1,303 @@
+"""Pi agent-core 风格的有状态 Agent 门面。"""
+
+from __future__ import annotations
+
+import asyncio
+from collections.abc import Awaitable, Callable
+from contextlib import suppress
+from dataclasses import dataclass, field, replace
+from enum import StrEnum
+from typing import Any
+
+from app.ai_provider.types.chat import ChatChunk, TokenUsage
+from app.ai_provider.types.messages import BaseMessage, HumanMessage
+from app.application.agent.confirmation import ConfirmationRegistry
+from app.application.agent.extensions import (
+    AgentEvent,
+    AgentRunContext,
+    CancellationToken,
+    ExtensionRegistry,
+)
+from app.application.agent.runtime import AgentTurnResult, run_agent_turn
+from app.modules.tool_runtime.definition import ToolRuntimeLike
+
+
+class AgentStatus(StrEnum):
+    idle = "idle"
+    running = "running"
+    completed = "completed"
+    failed = "failed"
+    cancelled = "cancelled"
+
+
+class QueueMode(StrEnum):
+    all = "all"
+    one_at_a_time = "one-at-a-time"
+
+
+@dataclass
+class AgentState:
+    """有状态 Agent 的进程内快照。"""
+
+    messages: list[BaseMessage] = field(default_factory=list)
+    status: AgentStatus = AgentStatus.idle
+    streaming_message: str = ""
+    pending_tool_calls: set[str] = field(default_factory=set)
+    error_message: str | None = None
+    usage: TokenUsage = field(default_factory=TokenUsage)
+
+
+class PendingMessageQueue:
+    """steering/follow-up 共用的小型 FIFO。"""
+
+    def __init__(self, mode: QueueMode = QueueMode.one_at_a_time) -> None:
+        self.mode = mode
+        self._messages: list[BaseMessage] = []
+
+    def put(self, message: BaseMessage) -> None:
+        self._messages.append(message)
+
+    def drain(self) -> list[BaseMessage]:
+        if not self._messages:
+            return []
+        if self.mode is QueueMode.all:
+            messages, self._messages = self._messages, []
+            return messages
+        return [self._messages.pop(0)]
+
+    def clear(self) -> None:
+        self._messages.clear()
+
+    def __bool__(self) -> bool:
+        return bool(self._messages)
+
+
+@dataclass(frozen=True)
+class AgentConfig:
+    """Stateful Agent 的稳定运行配置。"""
+
+    tools: tuple[dict[str, Any], ...]
+    tool_runtime: ToolRuntimeLike | None
+    model_hint: str | None = None
+    thinking_enabled: bool | None = None
+    reasoning_effort: str | None = None
+    max_iterations: int = 8
+    confirmation_registry: ConfirmationRegistry | None = None
+    confirmation_timeout: float = 300.0
+    on_turn: Callable[[], Awaitable[None]] | None = None
+    on_chunk: Callable[[ChatChunk], Awaitable[None]] | None = None
+    on_tool_event: Callable[[str, dict[str, Any]], Awaitable[None]] | None = None
+    on_confirm_timeout: Callable[[str], Awaitable[None]] | None = None
+
+
+class Agent:
+    """管理状态、消息队列、取消与扩展 Hook；低层循环仍由 run_agent_turn 负责。"""
+
+    def __init__(
+        self,
+        config: AgentConfig,
+        *,
+        messages: list[BaseMessage] | None = None,
+        run_context: AgentRunContext | None = None,
+        extensions: ExtensionRegistry | None = None,
+        runner: Callable[..., Awaitable[AgentTurnResult]] = run_agent_turn,
+    ) -> None:
+        self.config = config
+        self.state = AgentState(messages=list(messages or []))
+        self.run_context = run_context or AgentRunContext()
+        self.extensions = extensions or ExtensionRegistry()
+        self._runner = runner
+        self.steering = PendingMessageQueue()
+        self.follow_ups = PendingMessageQueue()
+        self._active_task: asyncio.Task[AgentTurnResult] | None = None
+        self._accepting_messages = False
+        self._idle = asyncio.Event()
+        self._idle.set()
+
+    def steer(self, message: str | BaseMessage) -> bool:
+        if not self._accepting_messages:
+            return False
+        self.steering.put(self._as_message(message))
+        return True
+
+    def follow_up(self, message: str | BaseMessage) -> bool:
+        if not self._accepting_messages:
+            return False
+        self.follow_ups.put(self._as_message(message))
+        return True
+
+    async def prompt(self, message: str | BaseMessage) -> AgentTurnResult:
+        if self.state.status is AgentStatus.running:
+            raise RuntimeError("Agent 正在运行，请使用 steer 或 follow_up")
+        self.state.messages.append(self._as_message(message))
+        return await self._run()
+
+    async def continue_run(self) -> AgentTurnResult:
+        if self.state.status is AgentStatus.running:
+            raise RuntimeError("Agent 正在运行")
+        return await self._run()
+
+    async def abort(self) -> bool:
+        task = self._active_task
+        if task is None or task.done():
+            return False
+        self.run_context.cancellation.cancel()
+        task.cancel()
+        return True
+
+    async def wait_for_idle(self) -> None:
+        await self._idle.wait()
+
+    async def reset(self) -> None:
+        await self.abort()
+        await self.wait_for_idle()
+        self.state = AgentState()
+        self.steering.clear()
+        self.follow_ups.clear()
+
+    async def _run(self) -> AgentTurnResult:
+        if self.run_context.cancellation.cancelled:
+            self.run_context = replace(self.run_context, cancellation=CancellationToken())
+        self.state.status = AgentStatus.running
+        self.state.streaming_message = ""
+        self.state.pending_tool_calls.clear()
+        self.state.error_message = None
+        self._accepting_messages = True
+        self._idle.clear()
+        try:
+            await self.extensions.publish(AgentEvent("agent.started"), self.run_context)
+            task = asyncio.create_task(self._run_loop())
+            self._active_task = task
+            result = await task
+            self._accepting_messages = False
+            self.state.status = AgentStatus.completed
+            self.state.streaming_message = result.content
+            self.state.usage = result.usage
+            await self.extensions.publish(
+                AgentEvent("agent.ended", {"iterations": result.iterations}), self.run_context
+            )
+            return result
+        except asyncio.CancelledError:
+            self._accepting_messages = False
+            self.state.status = AgentStatus.cancelled
+            await self.extensions.publish(AgentEvent("agent.cancelled"), self.run_context)
+            raise
+        except Exception as exc:
+            self._accepting_messages = False
+            self.state.status = AgentStatus.failed
+            self.state.error_message = str(exc)
+            with suppress(Exception):
+                await self.extensions.publish(
+                    AgentEvent("agent.failed", {"error": str(exc)}), self.run_context
+                )
+            raise
+        finally:
+            self._accepting_messages = False
+            with suppress(Exception):
+                await self.extensions.publish(
+                    AgentEvent("agent.settled", {"status": self.state.status.value}),
+                    self.run_context,
+                )
+            self._active_task = None
+            self._idle.set()
+
+    async def _run_loop(self) -> AgentTurnResult:
+        remaining = self.config.max_iterations
+        total_iterations = 0
+        total_usage = TokenUsage()
+        total_tool_history: list[dict[str, Any]] = []
+        final = AgentTurnResult(content="", reasoning="")
+        while remaining > 0:
+            working_messages = list(self.state.messages)
+            final = await self._runner(
+                messages=working_messages,
+                tools=list(self.config.tools),
+                tool_runtime=self.config.tool_runtime,
+                model_hint=self.config.model_hint,
+                thinking_enabled=self.config.thinking_enabled,
+                reasoning_effort=self.config.reasoning_effort,
+                max_iterations=remaining,
+                run_id=self.run_context.run_id,
+                character_id=self.run_context.character_id,
+                trace_id=self.run_context.trace_id,
+                on_turn=self.config.on_turn,
+                on_chunk=self._on_chunk,
+                on_tool_event=self._on_tool_event,
+                confirmation_registry=self.config.confirmation_registry,
+                confirmation_timeout=self.config.confirmation_timeout,
+                on_confirm_timeout=self.config.on_confirm_timeout,
+                extensions=self.extensions,
+                run_context=self.run_context,
+                get_steering_messages=self.steering.drain,
+            )
+            self.state.messages = working_messages
+            total_iterations += final.iterations
+            total_usage += final.usage
+            total_tool_history.extend(final.tool_history)
+            remaining -= final.iterations
+            if final.truncated:
+                return AgentTurnResult(
+                    content=final.content,
+                    reasoning=final.reasoning,
+                    tool_history=total_tool_history,
+                    iterations=total_iterations,
+                    truncated=True,
+                    usage=total_usage,
+                )
+            if remaining <= 0:
+                return AgentTurnResult(
+                    content=final.content,
+                    reasoning=final.reasoning,
+                    tool_history=total_tool_history,
+                    iterations=total_iterations,
+                    truncated=bool(self.follow_ups),
+                    usage=total_usage,
+                )
+            follow_ups = self.follow_ups.drain()
+            if not follow_ups:
+                return AgentTurnResult(
+                    content=final.content,
+                    reasoning=final.reasoning,
+                    tool_history=total_tool_history,
+                    iterations=total_iterations,
+                    truncated=final.truncated,
+                    usage=total_usage,
+                )
+            self.state.messages.extend(follow_ups)
+        return final
+
+    async def _on_chunk(self, chunk: ChatChunk) -> None:
+        if chunk.delta_content:
+            self.state.streaming_message += chunk.delta_content
+        if self.config.on_chunk is not None:
+            await self.config.on_chunk(chunk)
+
+    async def _on_tool_event(self, event_type: str, payload: dict[str, Any]) -> None:
+        call_id = str(payload.get("tool_call_id", ""))
+        if event_type == "tool.started" and call_id:
+            self.state.pending_tool_calls.add(call_id)
+        elif event_type in ("tool.completed", "tool.failed") and call_id:
+            self.state.pending_tool_calls.discard(call_id)
+        # 先转发 SSE（用户可见流优先），再把同一事件发布进扩展事件流，
+        # 让 AgentEventListener 也能观测工具级生命周期。
+        # 扩展 listener 异常被吞掉，避免观测副菜阻断工具事件主流程。
+        if self.config.on_tool_event is not None:
+            await self.config.on_tool_event(event_type, payload)
+        with suppress(Exception):
+            await self.extensions.publish(
+                AgentEvent(event_type, payload), self.run_context
+            )
+
+    @staticmethod
+    def _as_message(message: str | BaseMessage) -> BaseMessage:
+        return HumanMessage(content=message) if isinstance(message, str) else message
+
+
+__all__ = [
+    "Agent",
+    "AgentConfig",
+    "AgentState",
+    "AgentStatus",
+    "PendingMessageQueue",
+    "QueueMode",
+]

backend/app/application/agent/confirmation.py

@@ -0,0 +1,148 @@
+"""混合确认注册表 — 同进程 Event 唤醒 + 重启后 DB polling 兜底。
+
+Agent 循环在工具需要确认时：
+1. 写 PendingConfirmationRecord 到 DB（持久化挂起状态）
+2. 调 ``ConfirmationRegistry.wait(run_id)`` — 同进程用 Event 0 延迟唤醒，
+   重启后 polling DB 兜底
+
+approve/deny 端点统一调 ``registry.resolve(run_id, approved)``：
+- 更新 PendingConfirmationRecord.status + resolved_at
+- 同一进程直接 set Event
+"""
+
+from __future__ import annotations
+
+import asyncio
+import time
+from datetime import UTC, datetime
+
+from sqlalchemy import or_, select, update
+
+from app.models.safety import PendingConfirmationRecord
+
+
+class ConfirmationRegistry:
+    """混合确认注册表。
+
+    - 同进程：``asyncio.Event`` 直接唤醒，0 延迟
+    - 重启后：Event 不存在 → polling ``PendingConfirmationRecord.status`` 兜底
+    - approve/deny 端点统一调用 ``resolve(run_id, approved)``
+    """
+
+    def __init__(self) -> None:
+        self._events: dict[str, asyncio.Event] = {}
+
+    async def wait(
+        self,
+        run_id: str,
+        *,
+        poll_interval: float = 0.5,
+        timeout: float = 60,
+        confirmation_id: str | None = None,
+    ) -> bool:
+        """等待确认。
+
+        同一进程的事件直接唤醒；跨进程或重启后 polling 兜底。
+
+        ``confirmation_id`` 可选，传入时会同时注册为该 Event 的别名，
+        使得外部以 ``confirmation_id`` 调 ``resolve`` 时也能立即唤醒同进程的 Event
+        （无需等 DB polling 兜底）。
+
+        返回：
+            True=批准, False=拒绝 ; 超时抛出 TimeoutError
+        """
+        event = asyncio.Event()
+        self._events[run_id] = event
+        if confirmation_id:
+            self._events[confirmation_id] = event
+
+        try:
+            deadline = time.monotonic() + timeout
+            while time.monotonic() < deadline:
+                # 1) polling DB 获取真实状态（Event 只用于唤醒，不携带批准/拒绝值）
+                from app.db.session import AsyncSessionLocal
+
+                async with AsyncSessionLocal() as session:
+                    if confirmation_id is None:
+                        stmt = select(PendingConfirmationRecord).where(
+                            or_(
+                                PendingConfirmationRecord.id == run_id,
+                                PendingConfirmationRecord.run_id == run_id,
+                            )
+                        )
+                    else:
+                        stmt = select(PendingConfirmationRecord).where(
+                            PendingConfirmationRecord.id == confirmation_id,
+                            PendingConfirmationRecord.run_id == run_id,
+                        )
+                    result = await session.execute(stmt)
+                    record = result.scalar_one_or_none()
+                    if record is not None and record.status != "pending":
+                        return record.status == "approved"
+
+                # 2) 等一个间隔，同时监听 Event（Event set 只表示「有变化」，实际值靠 DB）
+                try:
+                    await asyncio.wait_for(
+                        asyncio.shield(event.wait()),
+                        timeout=poll_interval,
+                    )
+                    # Event 被唤醒 → 回到循环顶部重新查 DB
+                    continue
+                except TimeoutError:
+                    continue
+
+            # 超时
+            raise TimeoutError(f"确认超时（等待 {timeout:.0f}s 未裁决）")
+        finally:
+            self._events.pop(run_id, None)
+            if confirmation_id:
+                self._events.pop(confirmation_id, None)
+
+    async def resolve(
+        self,
+        run_id: str,
+        approved: bool,
+        *,
+        confirmation_id: str | None = None,
+    ) -> bool:
+        """精确裁决一个待确认工具调用，并唤醒对应等待者。"""
+        from app.db.session import AsyncSessionLocal
+
+        target_id = confirmation_id or run_id
+        async with AsyncSessionLocal() as session:
+            status = "approved" if approved else "denied"
+            stmt = update(PendingConfirmationRecord).where(
+                PendingConfirmationRecord.status == "pending"
+            )
+            if confirmation_id is None:
+                stmt = stmt.where(
+                    or_(
+                        PendingConfirmationRecord.id == run_id,
+                        PendingConfirmationRecord.run_id == run_id,
+                    )
+                )
+            else:
+                stmt = stmt.where(
+                    PendingConfirmationRecord.id == confirmation_id,
+                    PendingConfirmationRecord.run_id == run_id,
+                )
+            result = await session.execute(
+                stmt.values(status=status, resolved_at=datetime.now(UTC))
+            )
+            await session.commit()
+
+        if result.rowcount == 0:
+            return False
+
+        event = self._events.get(target_id) or self._events.get(run_id)
+        if event is not None:
+            event.set()
+        return True
+
+    def has(self, run_id: str) -> bool:
+        """是否仍在等待（同进程检查）。"""
+        event = self._events.get(run_id)
+        return event is not None and not event.is_set()
+
+
+__all__ = ["ConfirmationRegistry"]

backend/app/application/agent/extensions.py

@@ -0,0 +1,229 @@
+"""Agent 扩展契约与注册表。
+
+扩展只接触本次运行的快照与 ToolResult，不持有数据库会话、密钥或安全治理对象。
+"""
+
+from __future__ import annotations
+
+import asyncio
+from collections.abc import Awaitable, Callable
+from dataclasses import dataclass, field, replace
+from typing import Any
+
+from app.ai_provider.types.chat import TokenUsage
+from app.ai_provider.types.messages import BaseMessage
+from app.modules.tool_runtime.definition import ToolResult
+
+
+class CancellationToken:
+    """协作式取消信号；阻塞 await 仍由活动 asyncio.Task.cancel() 负责中断。"""
+
+    def __init__(self) -> None:
+        self._cancelled = False
+
+    @property
+    def cancelled(self) -> bool:
+        return self._cancelled
+
+    def cancel(self) -> None:
+        self._cancelled = True
+
+    def raise_if_cancelled(self) -> None:
+        if self._cancelled:
+            raise asyncio.CancelledError
+
+
+@dataclass(frozen=True)
+class AgentRunContext:
+    """扩展可见的最小运行上下文。"""
+
+    run_id: str | None = None
+    session_id: str | None = None
+    character_id: str | None = None
+    trace_id: str | None = None
+    metadata: dict[str, Any] = field(default_factory=dict)
+    cancellation: CancellationToken = field(default_factory=CancellationToken)
+
+
+@dataclass(frozen=True)
+class AgentContext:
+    """每轮发送给模型前可转换的上下文快照。"""
+
+    messages: tuple[BaseMessage, ...]
+    tools: tuple[dict[str, Any], ...]
+    model_hint: str | None = None
+
+
+@dataclass(frozen=True)
+class AgentEvent:
+    """Agent Core 内部生命周期事件。"""
+
+    type: str
+    payload: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass(frozen=True)
+class ToolCallContext:
+    """工具调用 Hook 的稳定输入。"""
+
+    tool_call_id: str
+    name: str
+    input: dict[str, Any]
+    messages: tuple[BaseMessage, ...]
+
+
+@dataclass(frozen=True)
+class BeforeToolCallDecision:
+    """执行前决策；扩展只能收紧或改参，不能绕过 ToolRuntime。"""
+
+    allowed: bool = True
+    reason: str | None = None
+    input: dict[str, Any] | None = None
+
+
+@dataclass(frozen=True)
+class AfterToolCallDecision:
+    """执行后结果覆盖与提前终止提示。"""
+
+    result: ToolResult | None = None
+    terminate: bool = False
+
+
+@dataclass(frozen=True)
+class TurnSnapshot:
+    """一轮模型调用及其工具执行结果摘要。"""
+
+    iteration: int
+    content: str
+    reasoning: str
+    tool_calls: tuple[dict[str, Any], ...]
+    tool_results: tuple[dict[str, Any], ...]
+    usage: TokenUsage = field(default_factory=TokenUsage)
+
+
+ContextTransformer = Callable[[AgentContext, AgentRunContext], Awaitable[AgentContext]]
+BeforeToolCallHook = Callable[
+    [ToolCallContext, AgentRunContext], Awaitable[BeforeToolCallDecision | None]
+]
+AfterToolCallHook = Callable[
+    [ToolCallContext, ToolResult, AgentRunContext], Awaitable[AfterToolCallDecision | None]
+]
+TurnPolicy = Callable[[TurnSnapshot, AgentRunContext], Awaitable[bool]]
+AgentEventListener = Callable[[AgentEvent, AgentRunContext], Awaitable[None]]
+
+
+class ExtensionRegistry:
+    """受约束的 Agent 扩展注册表；按注册顺序执行 Hook。"""
+
+    def __init__(self) -> None:
+        self._context_transformers: list[ContextTransformer] = []
+        self._before_tool_hooks: list[BeforeToolCallHook] = []
+        self._after_tool_hooks: list[AfterToolCallHook] = []
+        self._turn_policies: list[TurnPolicy] = []
+        self._event_listeners: list[AgentEventListener] = []
+
+    def add_context_transformer(self, transformer: ContextTransformer) -> None:
+        self._context_transformers.append(transformer)
+
+    def add_before_tool_hook(self, hook: BeforeToolCallHook) -> None:
+        self._before_tool_hooks.append(hook)
+
+    def add_after_tool_hook(self, hook: AfterToolCallHook) -> None:
+        self._after_tool_hooks.append(hook)
+
+    def add_turn_policy(self, policy: TurnPolicy) -> None:
+        self._turn_policies.append(policy)
+
+    def add_event_listener(self, listener: AgentEventListener) -> Callable[[], None]:
+        self._event_listeners.append(listener)
+
+        def unsubscribe() -> None:
+            if listener in self._event_listeners:
+                self._event_listeners.remove(listener)
+
+        return unsubscribe
+
+    def extend(self, registry: ExtensionRegistry) -> None:
+        """按原注册顺序合并另一组扩展。"""
+        self._context_transformers.extend(registry._context_transformers)
+        self._before_tool_hooks.extend(registry._before_tool_hooks)
+        self._after_tool_hooks.extend(registry._after_tool_hooks)
+        self._turn_policies.extend(registry._turn_policies)
+        self._event_listeners.extend(registry._event_listeners)
+
+    async def transform_context(
+        self, context: AgentContext, run: AgentRunContext
+    ) -> AgentContext:
+        for transformer in self._context_transformers:
+            run.cancellation.raise_if_cancelled()
+            context = await transformer(context, run)
+        return context
+
+    async def before_tool_call(
+        self, call: ToolCallContext, run: AgentRunContext
+    ) -> BeforeToolCallDecision:
+        current = call
+        for hook in self._before_tool_hooks:
+            run.cancellation.raise_if_cancelled()
+            decision = await hook(current, run)
+            if decision is None:
+                continue
+            if not decision.allowed:
+                return decision
+            if decision.input is not None:
+                current = replace(current, input=decision.input)
+        return BeforeToolCallDecision(input=current.input)
+
+    async def after_tool_call(
+        self,
+        call: ToolCallContext,
+        result: ToolResult,
+        run: AgentRunContext,
+    ) -> AfterToolCallDecision:
+        current = result
+        terminate = False
+        for hook in self._after_tool_hooks:
+            run.cancellation.raise_if_cancelled()
+            decision = await hook(call, current, run)
+            if decision is None:
+                continue
+            if decision.result is not None:
+                current = decision.result
+            terminate = terminate or decision.terminate
+        return AfterToolCallDecision(result=current, terminate=terminate)
+
+    async def should_stop(self, turn: TurnSnapshot, run: AgentRunContext) -> bool:
+        for policy in self._turn_policies:
+            run.cancellation.raise_if_cancelled()
+            if await policy(turn, run):
+                return True
+        return False
+
+    async def publish(self, event: AgentEvent, run: AgentRunContext) -> None:
+        for listener in tuple(self._event_listeners):
+            await listener(event, run)
+
+    @property
+    def enabled(self) -> bool:
+        return any(
+            (
+                self._context_transformers,
+                self._before_tool_hooks,
+                self._after_tool_hooks,
+                self._turn_policies,
+                self._event_listeners,
+            )
+        )
+
+
+__all__ = [
+    "AfterToolCallDecision",
+    "AgentContext",
+    "AgentEvent",
+    "AgentRunContext",
+    "BeforeToolCallDecision",
+    "CancellationToken",
+    "ExtensionRegistry",
+    "ToolCallContext",
+    "TurnSnapshot",
+]

backend/app/application/agent/prompt_composer.py

@@ -0,0 +1,21 @@
+"""通用 Agent 提示组合。"""
+
+from __future__ import annotations
+
+from app.modules.agent import AgentDefinition
+from app.modules.skills import SkillManifest
+
+
+def compose_system_messages(
+    base_messages: list[str],
+    agent: AgentDefinition | None,
+    skills: list[SkillManifest],
+) -> list[str]:
+    """按稳定基础提示、Agent 身份、技能说明的顺序组合提示。"""
+    messages = list(base_messages)
+    if agent is not None and agent.system_prompt:
+        messages.append(f"【Agent：{agent.name}】\n{agent.system_prompt}")
+    for skill in skills:
+        if skill.prompt:
+            messages.append(f"【{skill.name}·能力注入】\n{skill.prompt}")
+    return messages