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Update app.py
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app.py
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@@ -1,12 +1,16 @@
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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import subprocess
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app = FastAPI()
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# 健康检查端点
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@app.get("/health")
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def health_check():
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return {"status": "ok"}
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class PromptRequest(BaseModel):
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@@ -15,12 +19,14 @@ class PromptRequest(BaseModel):
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@app.post("/generate")
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async def generate_response(request: PromptRequest):
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try:
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# 调用 Ollama 模型生成响应
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result = subprocess.check_output(["ollama", "run", request.prompt], text=True)
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return {"response": result.strip()}
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except subprocess.CalledProcessError as e:
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raise HTTPException(status_code=500, detail=f"Error: {e}")
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@app.get("/")
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def read_root():
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return {"message": "Ollama API is running"}
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import logging
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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import subprocess
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# 配置日志
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logging.basicConfig(level=logging.INFO)
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app = FastAPI()
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@app.get("/health")
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def health_check():
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logging.info("Health check endpoint was called")
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return {"status": "ok"}
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class PromptRequest(BaseModel):
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@app.post("/generate")
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async def generate_response(request: PromptRequest):
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try:
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result = subprocess.check_output(["ollama", "run", request.prompt], text=True)
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logging.info(f"Model response: {result.strip()}")
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return {"response": result.strip()}
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except subprocess.CalledProcessError as e:
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logging.error(f"Error during model generation: {e}")
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raise HTTPException(status_code=500, detail=f"Error: {e}")
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@app.get("/")
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def read_root():
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logging.info("Root endpoint was called")
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return {"message": "Ollama API is running"}
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