Hua
68ab86e6b9
- POST /solve accepts JSON with base64 encoded image - POST /solve/upload keeps multipart file upload compatibility - Server only depends on inference code (onnxruntime), no torch - Catch invalid image errors with proper 400 response - Update CLAUDE.md with new API documentation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
121 lines
3.5 KiB
Python
121 lines
3.5 KiB
Python
"""
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FastAPI HTTP 推理服务 (纯推理，不依赖 torch/训练代码)
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仅依赖: fastapi, uvicorn, python-multipart, onnxruntime, pillow, numpy
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API:
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POST /solve JSON base64 图片识别
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POST /solve/upload multipart 文件上传识别
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GET /health 健康检查
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启动:
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uv sync --extra server
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python cli.py serve --port 8080
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请求示例 (base64):
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curl -X POST http://localhost:8080/solve \
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-H "Content-Type: application/json" \
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-d '{"image": "<base64>", "type": "normal"}'
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请求示例 (文件上传):
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curl -X POST http://localhost:8080/solve/upload -F "image=@captcha.png"
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响应:
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{"type": "normal", "result": "A3B8", "raw": "A3B8", "time_ms": 12.3}
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"""
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import base64
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def create_app():
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"""
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创建 FastAPI 应用实例（工厂函数）。
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cli.py 的 cmd_serve 依赖此签名。
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"""
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from typing import Optional
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from fastapi import FastAPI, File, Query, UploadFile
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from fastapi.responses import JSONResponse
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from pydantic import BaseModel
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from inference.pipeline import CaptchaPipeline
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app = FastAPI(
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title="CaptchaBreaker",
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description="验证码识别多模型系统 - HTTP 推理服务",
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version="0.1.0",
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)
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pipeline: Optional[CaptchaPipeline] = None
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# ---- 启动时加载模型 ----
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@app.on_event("startup")
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def _load_models():
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nonlocal pipeline
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try:
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pipeline = CaptchaPipeline()
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except FileNotFoundError:
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pipeline = None
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# ---- 请求体定义 ----
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class SolveRequest(BaseModel):
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image: str # base64 编码的图片
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type: Optional[str] = None # 指定类型可跳过分类
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# ---- 通用推理逻辑 ----
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def _solve(image_bytes: bytes, captcha_type: Optional[str]) -> dict:
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if pipeline is None:
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return JSONResponse(
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status_code=503,
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content={"error": "模型未加载，请先训练并导出 ONNX 模型"},
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)
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if not image_bytes:
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return JSONResponse(status_code=400, content={"error": "空图片"})
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try:
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result = pipeline.solve(image_bytes, captcha_type=captcha_type)
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except (RuntimeError, TypeError) as e:
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return JSONResponse(status_code=400, content={"error": str(e)})
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except Exception as e:
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return JSONResponse(status_code=400, content={"error": f"图片解析失败: {e}"})
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return {
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"type": result["type"],
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"result": result["result"],
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"raw": result["raw"],
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"time_ms": result["time_ms"],
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}
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# ---- 路由 ----
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@app.get("/health")
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def health():
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models_loaded = pipeline is not None
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return {
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"status": "ok" if models_loaded else "no_models",
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"models_loaded": models_loaded,
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}
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@app.post("/solve")
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async def solve_base64(req: SolveRequest):
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"""JSON 请求，图片通过 base64 传输。"""
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try:
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image_bytes = base64.b64decode(req.image)
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except Exception:
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return JSONResponse(
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status_code=400,
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content={"error": "base64 解码失败"},
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)
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return _solve(image_bytes, req.type)
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@app.post("/solve/upload")
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async def solve_upload(
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image: UploadFile = File(...),
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type: Optional[str] = Query(None, description="指定类型跳过分类"),
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):
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"""multipart 文件上传。"""
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data = await image.read()
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return _solve(data, type)
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return app
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