chenxin
462d570751
- ① 后端删除 app/ai_provider/（38 文件，含 anthropic/openai 格式、billing、audio、embedding）、services/ai_provider_admin.py、core/config/model_config.py、tests/ai_provider/（21 文件） - ② 连带退役 application/agent/（旧 Agent 循环/steer/follow-up/确认注册表）、application/skill_executor.py、app/skills/（python skills 孤儿）、endpoints/audio.py、application/imports.py（ProviderManager 消费方）；settings 端点收敛为生成偏好 - ③ runs.py 修剪：AgentRunRegistry/steer/follow-up/confirmations 端点退役，保留 list/get/events/cancel/stream；safety 确认改为直接落库裁决（pending→approved/denied） - ④ 前端删除：models 页、ModelGatewayView、gateway.ts、GatewayPanel（玄关）、ModelGatewayPanel/ModelStrategyForm、audio.ts/useVoiceInput、网关类型与 mock；设置页收敛为外观/语言/通知 - ⑤ 配置收敛：config/models|providers|pricing.example.yaml 归档 shenshi/config/；.env.example 删 provider keys/MODEL_ENDPOINT_POOL/MODEL_CONFIG_PATH，收敛 SHENSHI_* - ⑥ 验收：rg 审计灵台 Provider SDK import 与 ai_provider 引用归零；后端 528 passed（2 个预存失败经 HEAD 复跑验证与本手术无关）、前端 type-check+201 passed、神识 go vet+test、BFF 4 passed
88 lines
3.9 KiB
Python
88 lines
3.9 KiB
Python
"""运行时 API schema。"""
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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class EventResponse(BaseModel):
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model_config = ConfigDict(
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json_schema_extra={
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"examples": [
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{
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"event_id": "event_70d5ef8a4c5b44a893b4f83f933b78e9",
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"run_id": "run_a2c8ecc73c0e4cc7bc2fafbaeada74e0",
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"character_id": "character_ec83d55746c54e47ab6f98d683032626",
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"type": "message.delta",
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"sequence": 2,
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"visibility": "public",
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"payload": {
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"message_id": "message_2f9b7bf7d3b84231b67b28bb39fbfa7a",
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"delta": "你好，我是魂镜中的默认人物，",
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"index": 0,
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},
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"created_at": "2026-06-19T09:10:52.676462Z",
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}
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]
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}
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)
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event_id: str = Field(description="事件 ID，前缀为 event_。")
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run_id: str = Field(description="所属运行 ID。")
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character_id: str = Field(description="所属人物 ID。")
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type: str = Field(description="事件类型，例如 run.started、message.delta、run.completed。")
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sequence: int = Field(description="Run 内递增序号，用于 SSE 断点续传。")
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visibility: str = Field(description="事件可见性：public / internal / audit。")
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payload: dict[str, Any] = Field(
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description="事件负载。message.delta 中包含 delta、index、message_id。"
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)
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created_at: str = Field(description="创建时间，UTC ISO 8601 字符串。")
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trace_id: str | None = Field(
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default=None, description="链路追踪 ID，可在司命台链路追踪页据此追溯。"
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)
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class RunResponse(BaseModel):
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model_config = ConfigDict(
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json_schema_extra={
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"examples": [
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{
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"id": "run_a2c8ecc73c0e4cc7bc2fafbaeada74e0",
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"character_id": "character_ec83d55746c54e47ab6f98d683032626",
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"session_id": "session_2e7c3cbd4ef8472bab59718b7d012f80",
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"status": "completed",
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"goal": "回复用户消息",
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"origin": "chat",
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"model_hint": "deepseek-v4-flash",
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"started_at": "2026-06-19T09:10:52.660153Z",
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"completed_at": "2026-06-19T09:10:52.690000Z",
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"error_code": None,
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"error_message": None,
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"created_at": "2026-06-19T09:10:52.660153Z",
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"updated_at": "2026-06-19T09:10:52.690000Z",
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}
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]
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}
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)
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id: str = Field(description="运行 ID，前缀为 run_。")
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character_id: str | None = Field(
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default=None, description="所属人物 ID；照心试演（kind=rehearsal）无正式人物。"
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)
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status: str = Field(
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description="运行状态：queued / running / completed / failed / cancelled / interrupted。"
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)
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kind: str = Field(
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default="foreground",
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description="运行种类：foreground / background_task / awakening / rehearsal（契约词典 §8.2）。",
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)
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goal: str | None = Field(description="运行目标。")
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origin: str = Field(description="运行来源，例如 chat。")
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model_hint: str | None = Field(description="本次运行使用的逻辑模型名或能力槽位。")
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started_at: str | None = Field(description="开始时间。")
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completed_at: str | None = Field(description="完成时间。")
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error_code: str | None = Field(description="失败错误码；成功时为空。")
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error_message: str | None = Field(description="失败错误信息；成功时为空。")
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created_at: str = Field(description="创建时间，UTC ISO 8601 字符串。")
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updated_at: str = Field(description="更新时间，UTC ISO 8601 字符串。")
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