first commit

main.py

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+from io import StringIO
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import StreamingResponse
+import os
+import json
+from openai import OpenAI
+from schemas import PresetCodeCreate, AIAnalysisRequest, DebugRequest
+from database import DatabaseService
+from pg_logger import exec_script_str_local
+from dotenv import load_dotenv
+
+
+# 加载环境变量
+load_dotenv()
+
+app = FastAPI(title="Code API", version="1.0.0")
+
+# CORS 配置
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=[
+        "https://code.xuyue.cc",
+        "http://10.13.114.114",
+        "http://localhost:3000",
+    ],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 数据库配置
+DATABASE_URL = "sqlite://database.db"
+
+# 初始化数据库
+DatabaseService.init_database(app, DATABASE_URL)
+
+
+@app.get("/")
+async def get_all_codes() -> dict:
+    """获取所有预设代码"""
+    codes = await DatabaseService.get_all_codes()
+    return {"data": codes}
+
+
+@app.get("/query/{query}")
+async def get_code_by_query(query: str) -> dict:
+    """根据查询字符串获取特定代码"""
+    code = await DatabaseService.get_code_by_query(query)
+    if not code:
+        raise HTTPException(status_code=404, detail="Record not found!")
+    return {"data": code}
+
+
+@app.post("/")
+async def create_code(code_data: PresetCodeCreate) -> dict:
+    """创建新的预设代码"""
+    try:
+        code = await DatabaseService.create_code(code_data)
+        return {"data": code}
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.delete("/{code_id}")
+async def delete_code(code_id: int) -> dict:
+    """删除指定 ID 的代码"""
+    success = await DatabaseService.delete_code(code_id)
+    if not success:
+        raise HTTPException(status_code=400, detail="Record not found!")
+
+    return {"data": True}
+
+
+@app.post("/ai")
+async def ai_analysis(request: AIAnalysisRequest):
+    """AI 代码分析端点"""
+    code = request.code
+    error_info = request.error_info
+    language = request.language
+
+    api_key = os.getenv("API_KEY")
+    if not api_key:
+        raise HTTPException(status_code=400, detail="API_KEY is not set")
+
+    system_prompt = "你是编程老师，擅长分析代码和错误信息，一般出错在语法和格式，请指出错误在第几行，并给出中文的、简要的解决方法。用 markdown 格式返回。"
+    user_prompt = f"编程语言：{language}\n代码：\n```{language}\n{code}\n```\n错误信息：\n```\n{error_info}\n```"
+
+    def generate_response():
+        try:
+            # 初始化 OpenAI 客户端
+            client = OpenAI(api_key=api_key, base_url="https://api.deepseek.com")
+
+            # 创建流式响应
+            stream = client.chat.completions.create(
+                model="deepseek-chat",
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": user_prompt},
+                ],
+                stream=True,
+                seed=0,
+            )
+
+            for chunk in stream:
+                if chunk.choices and len(chunk.choices) > 0:
+                    delta = chunk.choices[0].delta
+                    if hasattr(delta, "content") and delta.content:
+                        yield f"data: {json.dumps({'event': 'chunk', 'data': delta.content})}\n\n"
+
+            # 发送完成信号
+            yield f"data: {json.dumps({'event': 'done', 'data': ''})}\n\n"
+
+        except Exception as e:
+            yield f"data: {json.dumps({'event': 'error', 'data': str(e)})}\n\n"
+
+    return StreamingResponse(
+        generate_response(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+        },
+    )
+
+
+@app.post("/debug")
+async def debug(request: DebugRequest):
+    """调试端点"""
+    code = request.code
+    inputs = request.inputs
+
+    data = {}
+
+    def dump(input_code, output_trace):
+        data.update(dict(code=input_code, trace=output_trace))
+
+    exec_script_str_local(code, inputs, False, False, dump)
+    return {"data": data}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, port=8080)