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.env

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+APP_SECRET=123456

Dockerfile

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-# 使用指定的基础镜像
-FROM snailyc/blackbox2api
-
-# 设置环境变量
-ENV PORT=8001 \
-  APP_SECRET=Rfym21
-
-# 暴露端口 8001
-EXPOSE 8001
-
-# 启动命令
+# 使用官方Python基础镜像
+FROM python:3.9-slim
+
+# 设置工作目录
+WORKDIR /app
+
+# 复制依赖文件到工作目录
+COPY requirements.txt .
+
+# 安装依赖
+RUN pip install --no-cache-dir -r requirements.txt
+
+# 复制应用程序代码到容器中
+COPY . .
+
+# 暴露端口（根据你的应用程序监听的端口调整）
+EXPOSE 8001
+
+# 设置环境变量（例子）
+ENV APP_SECRET=Rfym21
+
+# 运行应用程序的命令
 CMD ["python", "main.py"]

api/app.py

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+from fastapi import FastAPI, Request
+from starlette.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from api.logger import setup_logger
+from api.routes import router  # 导入router而不是单独的函数
+
+logger = setup_logger(__name__)
+
+def create_app():
+    app = FastAPI()
+
+    # 配置CORS
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    # 添加路由
+    app.include_router(router)
+
+    @app.exception_handler(Exception)
+    async def global_exception_handler(request: Request, exc: Exception):
+        logger.error(f"An error occurred: {str(exc)}")
+        return JSONResponse(
+            status_code=500,
+            content={"message": "An internal server error occurred."},
+        )
+
+    return app
+
+app = create_app()

api/auth.py

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+from fastapi import Depends, HTTPException
+from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
+from api.config import APP_SECRET
+
+security = HTTPBearer()
+
+def verify_app_secret(credentials: HTTPAuthorizationCredentials = Depends(security)):
+    if credentials.credentials != APP_SECRET:
+        raise HTTPException(status_code=403, detail="Invalid APP_SECRET")
+    return credentials.credentials

api/config.py

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+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+BASE_URL = "https://www.blackbox.ai"
+headers = {
+    'accept': '*/*',
+    'accept-language': 'zh-CN,zh;q=0.9',
+    'origin': 'https://www.blackbox.ai',
+    'priority': 'u=1, i',
+    'sec-ch-ua': '"Google Chrome";v="129", "Not=A?Brand";v="8", "Chromium";v="129"',
+    'sec-ch-ua-mobile': '?0',
+    'sec-ch-ua-platform': '"Windows"',
+    'sec-fetch-dest': 'empty',
+    'sec-fetch-mode': 'cors',
+    'sec-fetch-site': 'same-origin',
+    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36',
+}
+APP_SECRET = os.getenv("APP_SECRET")
+ALLOWED_MODELS = [
+    {"id": "gpt-4o", "name": "gpt-4o"},
+    {"id": "gemini-1.5-pro-latest", "name": "gemini-pro"},
+    {"id": "gemini-1.5-pro", "name": "gemini-pro"},
+    {"id": "gemini-pro", "name": "gemini-pro"},
+    {"id": "claude-3-5-sonnet-20240620", "name": "claude-sonnet-3.5"},
+    {"id": "claude-3-5-sonnet", "name": "claude-sonnet-3.5"},
+]
+MODEL_MAPPING = {
+    "gpt-4o":"gpt-4o",
+    "gemini-1.5-pro-latest": "gemini-pro",
+    "gemini-1.5-pro":"gemini-1.5-pro",
+    "gemini-pro":"gemini-pro",
+    "claude-3-5-sonnet-20240620":"claude-sonnet-3.5",
+    "claude-3-5-sonnet":"claude-sonnet-3.5",
+}

api/logger.py

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+import logging
+
+def setup_logger(name):
+    logger = logging.getLogger(name)
+    if not logger.handlers:
+        logger.setLevel(logging.INFO)
+        formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+        
+        # 控制台处理器
+        console_handler = logging.StreamHandler()
+        console_handler.setFormatter(formatter)
+        logger.addHandler(console_handler)
+        
+        # 文件处理器 - 错误级别
+        # error_file_handler = logging.FileHandler('error.log')
+        # error_file_handler.setFormatter(formatter)
+        # error_file_handler.setLevel(logging.ERROR)
+        # logger.addHandler(error_file_handler)
+    
+    return logger

api/models.py

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+from typing import List, Optional
+from pydantic import BaseModel
+
+
+class Message(BaseModel):
+    role: str
+    content: str | list
+
+
+class ChatRequest(BaseModel):
+    model: str
+    messages: List[Message]
+    stream: Optional[bool] = False
+    temperature: Optional[float] = 0.7
+    top_p: Optional[float] = 0.9
+    max_tokens: Optional[int] = 8192

api/routes.py

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+import json
+from fastapi import APIRouter, Depends, HTTPException, Request, Response
+from fastapi.responses import StreamingResponse
+from api.auth import verify_app_secret
+from api.config import ALLOWED_MODELS
+from api.models import ChatRequest
+from api.utils import process_non_streaming_response, process_streaming_response
+from api.logger import setup_logger
+
+logger = setup_logger(__name__)
+
+router = APIRouter()
+
+@router.options("/v1/chat/completions")
+@router.options("/api/v1/chat/completions")
+async def chat_completions_options():
+    return Response(
+        status_code=200,
+        headers={
+            "Access-Control-Allow-Origin": "*",
+            "Access-Control-Allow-Methods": "POST, OPTIONS",
+            "Access-Control-Allow-Headers": "Content-Type, Authorization",
+        },
+    )
+
+@router.get("/v1/models")
+@router.get("/api/v1/models")
+async def list_models():
+    return {"object": "list", "data": ALLOWED_MODELS}
+
+@router.post("/v1/chat/completions")
+@router.post("/api/v1/chat/completions")
+async def chat_completions(
+    request: ChatRequest, app_secret: str = Depends(verify_app_secret)
+):
+    logger.info("Entering chat_completions route")
+    logger.info(f"Received request: {request}")
+    logger.info(f"App secret: {app_secret}")
+    logger.info(f"Received chat completion request for model: {request.model}")
+
+    if request.model not in [model["id"] for model in ALLOWED_MODELS]:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Model {request.model} is not allowed. Allowed models are: {', '.join(model['id'] for model in ALLOWED_MODELS)}",
+        )
+
+    if request.stream:
+        logger.info("Streaming response")
+        return StreamingResponse(process_streaming_response(request), media_type="text/event-stream")
+    else:
+        logger.info("Non-streaming response")
+        return await process_non_streaming_response(request)
+
+
+@router.route('/')  
+@router.route('/healthz')  
+@router.route('/ready')  
+@router.route('/alive')  
+@router.route('/status') 
+@router.get("/health")
+def health_check(request: Request):  
+    return Response(content=json.dumps({"status": "ok"}), media_type="application/json")  

api/utils.py

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+from datetime import datetime
+from http.client import HTTPException
+import json
+from typing import Any, Dict, Optional
+import uuid
+
+import httpx
+from api.config import MODEL_MAPPING, headers
+from fastapi import Depends, security
+from fastapi.security import HTTPAuthorizationCredentials
+
+from api.config import APP_SECRET, BASE_URL
+from api.models import ChatRequest
+
+from api.logger import setup_logger
+
+logger = setup_logger(__name__)
+
+
+def create_chat_completion_data(
+    content: str, model: str, timestamp: int, finish_reason: Optional[str] = None
+) -> Dict[str, Any]:
+    return {
+        "id": f"chatcmpl-{uuid.uuid4()}",
+        "object": "chat.completion.chunk",
+        "created": timestamp,
+        "model": model,
+        "choices": [
+            {
+                "index": 0,
+                "delta": {"content": content, "role": "assistant"},
+                "finish_reason": finish_reason,
+            }
+        ],
+        "usage": None,
+    }
+
+
+def verify_app_secret(credentials: HTTPAuthorizationCredentials = Depends(security)):
+    if credentials.credentials != APP_SECRET:
+        raise HTTPException(status_code=403, detail="Invalid APP_SECRET")
+    return credentials.credentials
+
+
+def message_to_dict(message):
+    if isinstance(message.content, str):
+        return {"role": message.role, "content": message.content}
+    elif isinstance(message.content, list) and len(message.content) == 2:
+        return {
+            "role": message.role,
+            "content": message.content[0]["text"],
+            "data": {
+                "imageBase64": message.content[1]["image_url"]["url"],
+                "fileText": "",
+                "title": "snapshoot",
+            },
+        }
+    else:
+        return {"role": message.role, "content": message.content}
+
+
+async def process_streaming_response(request: ChatRequest):
+    json_data = {
+        "messages": [message_to_dict(msg) for msg in request.messages],
+        "previewToken": None,
+        "userId": None,
+        "codeModelMode": True,
+        "agentMode": {},
+        "trendingAgentMode": {},
+        "isMicMode": False,
+        "userSystemPrompt": None,
+        "maxTokens": request.max_tokens,
+        "playgroundTopP": request.top_p,
+        "playgroundTemperature": request.temperature,
+        "isChromeExt": False,
+        "githubToken": None,
+        "clickedAnswer2": False,
+        "clickedAnswer3": False,
+        "clickedForceWebSearch": False,
+        "visitFromDelta": False,
+        "mobileClient": False,
+        "userSelectedModel": MODEL_MAPPING.get(request.model),
+    }
+
+    async with httpx.AsyncClient() as client:
+        try:
+            async with client.stream(
+                "POST",
+                f"{BASE_URL}/api/chat",
+                headers=headers,
+                json=json_data,
+                timeout=100,
+            ) as response:
+                response.raise_for_status()
+                async for line in response.aiter_lines():
+                    timestamp = int(datetime.now().timestamp())
+                    if line:
+                        content = line + "\n"
+                        if content.startswith("$@$v=undefined-rv1$@$"):
+                            yield f"data: {json.dumps(create_chat_completion_data(content[21:], request.model, timestamp))}\n\n"
+                        else:
+                            yield f"data: {json.dumps(create_chat_completion_data(content, request.model, timestamp))}\n\n"
+
+                yield f"data: {json.dumps(create_chat_completion_data('', request.model, timestamp, 'stop'))}\n\n"
+                yield "data: [DONE]\n\n"
+        except httpx.HTTPStatusError as e:
+            logger.error(f"HTTP error occurred: {e}")
+            raise HTTPException(status_code=e.response.status_code, detail=str(e))
+        except httpx.RequestError as e:
+            logger.error(f"Error occurred during request: {e}")
+            raise HTTPException(status_code=500, detail=str(e))
+
+
+async def process_non_streaming_response(request: ChatRequest):
+    json_data = {
+        "messages": [message_to_dict(msg) for msg in request.messages],
+        "previewToken": None,
+        "userId": None,
+        "codeModelMode": True,
+        "agentMode": {},
+        "trendingAgentMode": {},
+        "isMicMode": False,
+        "userSystemPrompt": None,
+        "maxTokens": request.max_tokens,
+        "playgroundTopP": request.top_p,
+        "playgroundTemperature": request.temperature,
+        "isChromeExt": False,
+        "githubToken": None,
+        "clickedAnswer2": False,
+        "clickedAnswer3": False,
+        "clickedForceWebSearch": False,
+        "visitFromDelta": False,
+        "mobileClient": False,
+        "userSelectedModel": MODEL_MAPPING.get(request.model),
+    }
+    full_response = ""
+    async with httpx.AsyncClient() as client:
+        async with client.stream(
+            method="POST", url=f"{BASE_URL}/api/chat", headers=headers, json=json_data
+        ) as response:
+            async for chunk in response.aiter_text():
+                full_response += chunk
+    if full_response.startswith("$@$v=undefined-rv1$@$"):
+        full_response = full_response[21:]
+    return {
+        "id": f"chatcmpl-{uuid.uuid4()}",
+        "object": "chat.completion",
+        "created": int(datetime.now().timestamp()),
+        "model": request.model,
+        "choices": [
+            {
+                "index": 0,
+                "message": {"role": "assistant", "content": full_response},
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": None,
+    }

main.py

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+import uvicorn
+from api.app import app
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8001)

requirements.txt

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+fastapi
+httpx
+pydantic
+pyinstaller
+python-dotenv
+starlette
+uvicorn