79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
"""开发档 Mock 模型服务：OpenAI 兼容 /chat/completions SSE 流式回声。
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仅供本地联调 Run 流水线（事件序列、芽体渲染、对账），不模拟任何真实模型能力。
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生产部署不启动本服务（与 /v1/webhooks/v1/payments/mock 同一开发档惯例）。
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启动：uv run python scripts/mock_model.py （127.0.0.1:8001）
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鉴权：任意 Bearer 均接受（联调端点，只监听回环地址）。
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"""
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import asyncio
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import json
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from fastapi import FastAPI, Request
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from fastapi.responses import StreamingResponse
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app = FastAPI(title="Hunjing Dev Mock Model", docs_url=None)
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REPLY = (
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"收到了。按当前镜域的状态，我先把这件事拆成两步：先核对读书会的偏好记忆，"
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"再给出一份可归真的结果。这个回复由开发档 Mock 模型逐字流出，"
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"用于验证 content.block.delta 事件序列、临时芽体渲染与 message.completed 对账。"
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)
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@app.get("/healthz")
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async def healthz() -> dict[str, str]:
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return {"status": "ok", "env": "development", "mock": "true"}
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@app.post("/v1/chat/completions")
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async def chat_completions(request: Request) -> StreamingResponse:
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body = await request.json()
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user_text = ""
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for m in reversed(body.get("messages", [])):
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if m.get("role") == "user" and m.get("content"):
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user_text = str(m["content"])[-60:]
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break
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text = f"（mock 回应 · 你说：「{user_text}」）\n{REPLY}"
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async def gen():
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# 逐字流出，模拟真实 TTFT 与节奏
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for ch in text:
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await asyncio.sleep(0.02)
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yield (
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"data: "
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+ json.dumps(
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{"choices": [{"index": 0, "delta": {"content": ch}, "finish_reason": None}]},
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ensure_ascii=False,
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)
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+ "\n\n"
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)
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yield (
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"data: "
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+ json.dumps(
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{"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
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ensure_ascii=False,
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)
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+ "\n\n"
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)
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yield (
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"data: "
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+ json.dumps(
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{
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"choices": [],
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"usage": {
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"prompt_tokens": 32,
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"completion_tokens": len(text),
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"total_tokens": 32 + len(text),
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},
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},
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ensure_ascii=False,
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)
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+ "\n\n"
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)
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yield "data: [DONE]\n\n"
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return StreamingResponse(gen(), media_type="text/event-stream")
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