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.env.example

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+# 客户端请求时允许通过请求的 API KEY，无需在当前环境变量当中手动添加 Bearer，目前只支持一个，未来可以升级为数组/toml/yaml 或专门的管理工具
+ALLOW_API_KEY=your_api_key 
+
+# 服务端跨域配置
+# 允许访问的域名，多个域名使用逗号分隔(中间不能有空格)，例如：http://localhost:3000,https://chat.example.com
+# 如果允许所有域名访问，则填写 *
+ALLOW_ORIGINS=your_allow_origins
+
+# DeepSeek API KEY，默认为 DeepSeek 官方 API，只支持 r1 系列模型（包括基于 llama 和 qwen 的密集模型，1.5b、7b、8b、14b、32b、70b、671b）
+# 除了采用官网的 DeepSeek r1 外，还推荐以下：
+# 1.SiliconFlow 的 deepseek-ai/DeepSeek-R1 获取 API KEY 的链接：https://cloud.siliconflow.cn/i/RXikvHE2 (点击此链接可以获得到 2000 万免费 tokens)
+# 2.Groq 托管的 deepseek-r1-distill-llama-70b 获取 API KEY 的链接：https://console.groq.com/docs/models
+# 3.本地 Ollama 运行的 DeepSeek r1 , 可以根据自己电脑的内存和显存大小而定，推荐 7b、8b、14b 最佳，获取链接：https://ollama.com
+DEEPSEEK_API_KEY=your_deepseek_api_key
+DEEPSEEK_API_URL=https://api.deepseek.com/v1/chat/completions #如果是siliconflow，则使用 https://api.siliconflow.cn/v1/chat/completions
+DEEPSEEK_MODEL=deepseek-reasoner #如果是siliconflow，则使用 deepseek-ai/DeepSeek-R1
+
+
+# Claude API KEY，默认为 Claude 官方 API，只推荐 Claude 3.5 Sonnet 模型，不推荐其他模型
+CLAUDE_API_KEY=your_claude_api_key
+CLAUDE_MODEL=claude-3-5-sonnet-20241022
+
+# Claude Provider
+# 若使用官方则填 anthropic
+# 若使用中转平台如 OpenRouter 或国内基于 OneAPI 的中转平台则填oneapi
+CLAUDE_PROVIDER=anthropic
+
+# 如果使用 OpenRouter，这里填写 OpenRouter 的 API URL https://openrouter.ai/api/v1/chat/completions, 
+# 如果使用中转平台则填写相应的 API URL: 例如 https://api.oneapi.com/v1/chat/completions
+# 默认为 Anthropic 的 API URL https://api.anthropic.com/v1/messages
+CLAUDE_API_URL=https://api.anthropic.com/v1/messages
+
+# 日志配置
+# 可选值：DEBUG, INFO, WARNING, ERROR, CRITICAL
+LOG_LEVEL=INFO

Dockerfile

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+# 使用 Python 3.11 slim 版本作为基础镜像
+FROM python:3.11-slim
+
+# 设置工作目录
+WORKDIR /app
+
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1
+
+# 安装依赖
+RUN pip install --no-cache-dir \
+    aiohttp==3.11.11 \
+    colorlog==6.9.0 \
+    fastapi==0.115.8 \
+    python-dotenv==1.0.1 \
+    "uvicorn[standard]"
+
+# 复制项目文件
+COPY ./app ./app
+
+# 暴露端口
+EXPOSE 8000
+
+# 启动命令
+CMD ["python", "-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

app/clients/__init__.py

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+from .base_client import BaseClient
+from .deepseek_client import DeepSeekClient
+from .claude_client import ClaudeClient
+
+__all__ = ['BaseClient', 'DeepSeekClient', 'ClaudeClient']

app/clients/base_client.py

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+"""基础客户端类，定义通用接口"""
+from typing import AsyncGenerator, Any
+import aiohttp
+from app.utils.logger import logger
+from abc import ABC, abstractmethod
+
+
+class BaseClient(ABC):
+    def __init__(self, api_key: str, api_url: str):
+        """初始化基础客户端
+        
+        Args:
+            api_key: API密钥
+            api_url: API地址
+        """
+        self.api_key = api_key
+        self.api_url = api_url
+        
+    async def _make_request(self, headers: dict, data: dict) -> AsyncGenerator[bytes, None]:
+        """发送请求并处理响应
+        
+        Args:
+            headers: 请求头
+            data: 请求数据
+            
+        Yields:
+            bytes: 原始响应数据
+        """
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(self.api_url, headers=headers, json=data) as response:
+                    if response.status != 200:
+                        error_text = await response.text()
+                        logger.error(f"API 请求失败: {error_text}")
+                        return
+                        
+                    async for chunk in response.content.iter_any():
+                        yield chunk
+                        
+        except Exception as e:
+            logger.error(f"请求 API 时发生错误: {e}")
+            
+    @abstractmethod
+    async def stream_chat(self, messages: list, model: str) -> AsyncGenerator[tuple[str, str], None]:
+        """流式对话，由子类实现
+        
+        Args:
+            messages: 消息列表
+            model: 模型名称
+            
+        Yields:
+            tuple[str, str]: (内容类型, 内容)
+        """
+        pass

app/clients/claude_client.py

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+"""Claude API 客户端"""
+import json
+from typing import AsyncGenerator
+from app.utils.logger import logger
+from .base_client import BaseClient
+
+
+class ClaudeClient(BaseClient):
+    def __init__(self, api_key: str, api_url: str = "https://api.anthropic.com/v1/messages", provider: str = "anthropic"):
+        """初始化 Claude 客户端
+        
+        Args:
+            api_key: Claude API密钥
+            api_url: Claude API地址
+            is_openrouter: 是否使用 OpenRouter API
+        """
+        super().__init__(api_key, api_url)
+        self.provider = provider
+        
+    async def stream_chat(self, messages: list, model: str = "claude-3-5-sonnet-20241022") -> AsyncGenerator[tuple[str, str], None]:
+        """流式对话
+        
+        Args:
+            messages: 消息列表
+            model: 模型名称。如果是 OpenRouter，会自动转换为 'anthropic/claude-3.5-sonnet' 格式
+            
+        Yields:
+            tuple[str, str]: (内容类型, 内容)
+                内容类型: "answer"
+                内容: 实际的文本内容
+        """
+
+        if self.provider == "openrouter":
+            logger.info("使用 OpenRouter API 作为 Claude 3.5 Sonnet 供应商 ")
+            # 转换模型名称为 OpenRouter 格式
+            model = "anthropic/claude-3.5-sonnet"
+                
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json",
+                "HTTP-Referer": "https://github.com/ErlichLiu/DeepClaude",  # OpenRouter 需要
+                "X-Title": "DeepClaude"  # OpenRouter 需要
+            }
+            
+            data = {
+                "model": model,  # OpenRouter 使用 anthropic/claude-3.5-sonnet 格式
+                "messages": messages,
+                "stream": True
+            }
+        elif self.provider == "oneapi":
+            logger.info("使用 OneAPI API 作为 Claude 3.5 Sonnet 供应商 ")
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json"
+            }
+
+            data = {
+                "model": model,
+                "messages": messages,
+                "stream": True
+            }
+        elif self.provider == "anthropic":
+            logger.info("使用 Anthropic API 作为 Claude 3.5 Sonnet 供应商 ")
+            headers = {
+                "x-api-key": self.api_key,
+                "anthropic-version": "2023-06-01",
+                "content-type": "application/json",
+                "accept": "text/event-stream",
+            }
+            
+            data = {
+                "model": model,
+                "messages": messages,
+                "max_tokens": 8192,
+                "stream": True
+            }
+        else:
+            raise ValueError(f"不支持的Claude Provider: {self.provider}")
+        
+        async for chunk in self._make_request(headers, data):
+            chunk_str = chunk.decode('utf-8')
+            if not chunk_str.strip():
+                continue
+                
+            for line in chunk_str.split('\n'):
+                if line.startswith('data: '):
+                    json_str = line[6:]  # 去掉 'data: ' 前缀
+                    if json_str.strip() == '[DONE]':
+                        return
+                        
+                    try:
+                        data = json.loads(json_str)
+                        if self.provider in ("openrouter", "oneapi"):
+                            # OpenRouter/OneApi 格式
+                            content = data.get('choices', [{}])[0].get('delta', {}).get('content', '')
+                            if content:
+                                yield "answer", content
+                        elif self.provider == "anthropic":
+                            # Anthropic 格式
+                            if data.get('type') == 'content_block_delta':
+                                content = data.get('delta', {}).get('text', '')
+                                if content:
+                                    yield "answer", content
+                        else:
+                            raise ValueError(f"不支持的Claude Provider: {self.provider}")
+                    except json.JSONDecodeError:
+                        continue

app/clients/deepseek_client.py

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+"""DeepSeek API 客户端"""
+import json
+from typing import AsyncGenerator
+from app.utils.logger import logger
+from .base_client import BaseClient
+
+
+class DeepSeekClient(BaseClient):
+    def __init__(self, api_key: str, api_url: str = "https://api.siliconflow.cn/v1/chat/completions"):
+        """初始化 DeepSeek 客户端
+        
+        Args:
+            api_key: DeepSeek API密钥
+            api_url: DeepSeek API地址
+        """
+        super().__init__(api_key, api_url)
+        
+    def _process_think_tag_content(self, content: str) -> tuple[bool, str]:
+        """处理包含 think 标签的内容
+        
+        Args:
+            content: 需要处理的内容字符串
+            
+        Returns:
+            tuple[bool, str]: 
+                bool: 是否检测到完整的 think 标签对
+                str: 处理后的内容
+        """
+        has_start = "<think>" in content
+        has_end = "</think>" in content
+        
+        if has_start and has_end:
+            return True, content
+        elif has_start:
+            return False, content
+        elif not has_start and not has_end:
+            return False, content
+        else:
+            return True, content
+            
+    async def stream_chat(self, messages: list, model: str = "deepseek-ai/DeepSeek-R1", is_origin_reasoning: bool = True) -> AsyncGenerator[tuple[str, str], None]:
+        """流式对话
+        
+        Args:
+            messages: 消息列表
+            model: 模型名称
+            
+        Yields:
+            tuple[str, str]: (内容类型, 内容)
+                内容类型: "reasoning" 或 "content"
+                内容: 实际的文本内容
+        """
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+            "Accept": "text/event-stream",
+        }
+        data = {
+            "model": model,
+            "messages": messages,
+            "stream": True,
+        }
+        
+        logger.debug(f"开始流式对话：{data}")
+
+        accumulated_content = ""
+        is_collecting_think = False
+        
+        async for chunk in self._make_request(headers, data):
+            chunk_str = chunk.decode('utf-8')
+            
+            try:
+                lines = chunk_str.splitlines()
+                for line in lines:
+                    if line.startswith("data: "):
+                        json_str = line[len("data: "):]
+                        if json_str == "[DONE]":
+                            return
+                        
+                        data = json.loads(json_str)
+                        if data and data.get("choices") and data["choices"][0].get("delta"):
+                            delta = data["choices"][0]["delta"]
+                            
+                            if is_origin_reasoning:
+                                # 处理 reasoning_content
+                                if delta.get("reasoning_content"):
+                                    content = delta["reasoning_content"]
+                                    logger.debug(f"提取推理内容：{content}")
+                                    yield "reasoning", content
+                                
+                                if delta.get("reasoning_content") is None and delta.get("content"):
+                                    content = delta["content"]
+                                    logger.info(f"提取内容信息，推理阶段结束: {content}")
+                                    yield "content", content
+                            else:
+                                # 处理其他模型的输出
+                                if delta.get("content"):
+                                    content = delta["content"]
+                                    accumulated_content += content
+                                    
+                                    # 检查累积的内容是否包含完整的 think 标签对
+                                    is_complete, processed_content = self._process_think_tag_content(accumulated_content)
+                                    
+                                    if "<think>" in content and not is_collecting_think:
+                                        # 开始收集推理内容
+                                        logger.debug(f"开始收集推理内容：{content}")
+                                        is_collecting_think = True
+                                        yield "reasoning", content
+                                    elif is_collecting_think:
+                                        if "</think>" in content:
+                                            # 推理内容结束
+                                            logger.debug(f"推理内容结束：{content}")
+                                            is_collecting_think = False
+                                            yield "reasoning", content
+                                            # 输出空的 content 来触发 Claude 处理
+                                            yield "content", ""
+                                            # 重置累积内容
+                                            accumulated_content = ""
+                                        else:
+                                            # 继续收集推理内容
+                                            yield "reasoning", content
+                                    else:
+                                        # 普通内容
+                                        yield "content", content
+                                        
+            except json.JSONDecodeError as e:
+                logger.error(f"JSON 解析错误: {e}")
+            except Exception as e:
+                logger.error(f"处理 chunk 时发生错误: {e}")

app/deepclaude/deepclaude.py

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+"""DeepClaude 服务，用于协调 DeepSeek 和 Claude API 的调用"""
+import json
+import time
+import asyncio
+from typing import AsyncGenerator
+from app.utils.logger import logger
+from app.clients import DeepSeekClient, ClaudeClient
+
+
+class DeepClaude:
+    """处理 DeepSeek 和 Claude API 的流式输出衔接"""
+    
+    def __init__(self, deepseek_api_key: str, claude_api_key: str, 
+                 deepseek_api_url: str = "https://api.deepseek.com/v1/chat/completions", 
+                 claude_api_url: str = "https://api.anthropic.com/v1/messages",
+                 claude_provider: str = "anthropic",
+                 is_origin_reasoning: bool = True):
+        """初始化 API 客户端
+        
+        Args:
+            deepseek_api_key: DeepSeek API密钥
+            claude_api_key: Claude API密钥
+        """
+        self.deepseek_client = DeepSeekClient(deepseek_api_key, deepseek_api_url)
+        self.claude_client = ClaudeClient(claude_api_key, claude_api_url, claude_provider)
+        self.is_origin_reasoning = is_origin_reasoning
+    
+    async def chat_completions_with_stream(self, messages: list, 
+                                         deepseek_model: str = "deepseek-reasoner",
+                                         claude_model: str = "claude-3-5-sonnet-20241022") -> AsyncGenerator[bytes, None]:
+        """处理完整的流式输出过程
+        
+        Args:
+            messages: 初始消息列表
+            deepseek_model: DeepSeek 模型名称
+            claude_model: Claude 模型名称
+            
+        Yields:
+            字节流数据，格式如下：
+            {
+                "id": "chatcmpl-xxx",
+                "object": "chat.completion.chunk",
+                "created": timestamp,
+                "model": model_name,
+                "choices": [{
+                    "index": 0,
+                    "delta": {
+                        "role": "assistant",
+                        "reasoning_content": reasoning_content,
+                        "content": content
+                    }
+                }]
+            }
+        """
+        # 生成唯一的会话ID和时间戳
+        chat_id = f"chatcmpl-{hex(int(time.time() * 1000))[2:]}"
+        created_time = int(time.time())
+
+        # 创建队列，用于收集输出数据
+        output_queue = asyncio.Queue()
+        # 队列，用于传递 DeepSeek 推理内容给 Claude
+        claude_queue = asyncio.Queue()
+        
+        # 用于存储 DeepSeek 的推理累积内容
+        reasoning_content = []
+        
+        async def process_deepseek():
+            logger.info(f"开始处理 DeepSeek 流，使用模型：{deepseek_model}")
+            try:
+                async for content_type, content in self.deepseek_client.stream_chat(messages, deepseek_model, self.is_origin_reasoning):
+                    if content_type == "reasoning":
+                        reasoning_content.append(content)
+                        response = {
+                            "id": chat_id,
+                            "object": "chat.completion.chunk",
+                            "created": created_time,
+                            "model": deepseek_model,
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "role": "assistant",
+                                    "reasoning_content": content,
+                                    "content": ""
+                                }
+                            }]
+                        }
+                        await output_queue.put(f"data: {json.dumps(response)}\n\n".encode('utf-8'))
+                    elif content_type == "content":
+                        # 当收到 content 类型时，将完整的推理内容发送到 claude_queue，并结束 DeepSeek 流处理
+                        logger.info(f"DeepSeek 推理完成，收集到的推理内容长度：{len(''.join(reasoning_content))}")
+                        await claude_queue.put("".join(reasoning_content))
+                        break
+            except Exception as e:
+                logger.error(f"处理 DeepSeek 流时发生错误: {e}")
+                await claude_queue.put("")
+            # 用 None 标记 DeepSeek 任务结束
+            logger.info("DeepSeek 任务处理完成，标记结束")
+            await output_queue.put(None)
+        
+        async def process_claude():
+            try:
+                logger.info("等待获取 DeepSeek 的推理内容...")
+                reasoning = await claude_queue.get()
+                logger.debug(f"获取到推理内容，内容长度：{len(reasoning) if reasoning else 0}")
+                if not reasoning:
+                    logger.warning("未能获取到有效的推理内容，将使用默认提示继续")
+                    reasoning = "获取推理内容失败"
+                # 构造 Claude 的输入消息
+                claude_messages = messages.copy()
+                claude_messages.append({
+                    "role": "assistant",
+                    "content": f"Here's my reasoning process:\n{reasoning}\n\nBased on this reasoning, I will now provide my response:"
+                })
+                # 处理可能 messages 内存在 role = system 的情况，如果有，则去掉当前这一条的消息对象
+                claude_messages = [message for message in claude_messages if message.get("role", "") != "system"]
+
+                async for content_type, content in self.claude_client.stream_chat(claude_messages, claude_model):
+                    if content_type == "answer":
+                        response = {
+                            "id": chat_id,
+                            "object": "chat.completion.chunk",
+                            "created": created_time,
+                            "model": claude_model,
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "role": "assistant",
+                                    "content": content
+                                }
+                            }]
+                        }
+                        await output_queue.put(f"data: {json.dumps(response)}\n\n".encode('utf-8'))
+            except Exception as e:
+                logger.error(f"处理 Claude 流时发生错误: {e}")
+            # 用 None 标记 Claude 任务结束
+            await output_queue.put(None)
+        
+        # 创建并发任务
+        deepseek_task = asyncio.create_task(process_deepseek())
+        claude_task = asyncio.create_task(process_claude())
+        
+        # 等待两个任务完成，通过计数判断
+        finished_tasks = 0
+        while finished_tasks < 2:
+            item = await output_queue.get()
+            if item is None:
+                finished_tasks += 1
+            else:
+                yield item
+        
+        # 发送结束标记
+        yield b'data: [DONE]\n\n'

app/main.py

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+import os
+from dotenv import load_dotenv
+
+# 加载环境变量
+load_dotenv()
+
+from fastapi import FastAPI, Depends, Request
+from fastapi.responses import StreamingResponse
+from fastapi.middleware.cors import CORSMiddleware
+from app.utils.logger import logger
+from app.utils.auth import verify_api_key
+from app.deepclaude.deepclaude import DeepClaude
+import os
+
+app = FastAPI(title="DeepClaude API")
+
+# 从环境变量获取 CORS配置, API 密钥、地址以及模型名称
+ALLOW_ORIGINS = os.getenv("ALLOW_ORIGINS", "*")
+
+CLAUDE_API_KEY = os.getenv("CLAUDE_API_KEY")
+CLAUDE_MODEL = os.getenv("CLAUDE_MODEL")
+CLAUDE_PROVIDER = os.getenv("CLAUDE_PROVIDER", "anthropic") # Claude模型提供商, 默认为anthropic
+CLAUDE_API_URL = os.getenv("CLAUDE_API_URL", "https://api.anthropic.com/v1/messages")
+
+DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
+DEEPSEEK_API_URL = os.getenv("DEEPSEEK_API_URL")
+DEEPSEEK_MODEL = os.getenv("DEEPSEEK_MODEL")
+
+IS_ORIGIN_REASONING = os.getenv("IS_ORIGIN_REASONING", "True")
+
+# CORS设置
+allow_origins_list = ALLOW_ORIGINS.split(",") if ALLOW_ORIGINS else [] # 将逗号分隔的字符串转换为列表
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=allow_origins_list,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 验证日志级别
+logger.debug("当前日志级别为 DEBUG")
+logger.info("开始请求")
+
+@app.get("/", dependencies=[Depends(verify_api_key)])
+async def root():
+    logger.info("访问了根路径")
+    return {"message": "Welcome to DeepClaude API"}
+
+@app.post("/v1/chat/completions", dependencies=[Depends(verify_api_key)])
+async def chat_completions(request: Request):
+    """处理聊天完成请求，返回流式响应
+    
+    请求体格式应与 OpenAI API 保持一致，包含：
+    - messages: 消息列表
+    - model: 模型名称（可选）
+    - stream: 是否使用流式输出（必须为 True）
+    """
+
+    try:
+        # 1. 获取并验证请求数据
+        body = await request.json()
+        messages = body.get("messages")
+        if not messages:
+            return {"error": "messages 不能为空"}
+        
+        if not body.get("stream", False):
+            return {"error": "目前仅支持流式输出，stream 必须为 True"}
+        
+        # 3. 创建 DeepClaude 实例
+        if not DEEPSEEK_API_KEY or not CLAUDE_API_KEY:
+            return {"error": "未设置 API 密钥"}
+            
+        deep_claude = DeepClaude(
+            DEEPSEEK_API_KEY, 
+            CLAUDE_API_KEY, 
+            DEEPSEEK_API_URL,
+            CLAUDE_API_URL,
+            CLAUDE_PROVIDER,
+            IS_ORIGIN_REASONING
+        )
+        
+        # 4. 返回流式响应
+        return StreamingResponse(
+            deep_claude.chat_completions_with_stream(
+                messages=messages,
+                deepseek_model=DEEPSEEK_MODEL,
+                claude_model=CLAUDE_MODEL
+            ),
+            media_type="text/event-stream"
+        )
+        
+    except Exception as e:
+        logger.error(f"处理请求时发生错误: {e}")
+        return {"error": str(e)}

app/utils/auth.py

@@ -0,0 +1,47 @@
+from fastapi import HTTPException, Header
+from typing import Optional
+import os
+from dotenv import load_dotenv
+from app.utils.logger import logger
+
+# 加载 .env 文件
+logger.info(f"当前工作目录: {os.getcwd()}")
+logger.info("尝试加载.env文件...")
+load_dotenv(override=True)  # 添加override=True强制覆盖已存在的环境变量
+
+# 获取环境变量
+ALLOW_API_KEY = os.getenv("ALLOW_API_KEY")
+logger.info(f"ALLOW_API_KEY环境变量状态: {'已设置' if ALLOW_API_KEY else '未设置'}")
+
+if not ALLOW_API_KEY:
+    raise ValueError("ALLOW_API_KEY environment variable is not set")
+
+# 打印API密钥的前4位用于调试
+logger.info(f"Loaded API key starting with: {ALLOW_API_KEY[:4] if len(ALLOW_API_KEY) >= 4 else ALLOW_API_KEY}")
+
+
+async def verify_api_key(authorization: Optional[str] = Header(None)) -> None:
+    """验证API密钥
+
+    Args:
+        authorization (Optional[str], optional): Authorization header中的API密钥. Defaults to Header(None).
+
+    Raises:
+        HTTPException: 当Authorization header缺失或API密钥无效时抛出401错误
+    """
+    if authorization is None:
+        logger.warning("请求缺少Authorization header")
+        raise HTTPException(
+            status_code=401,
+            detail="Missing Authorization header"
+        )
+    
+    api_key = authorization.replace("Bearer ", "").strip()
+    if api_key != ALLOW_API_KEY:
+        logger.warning(f"无效的API密钥: {api_key}")
+        raise HTTPException(
+            status_code=401,
+            detail="Invalid API key"
+        )
+    
+    logger.info("API密钥验证通过")

app/utils/logger.py

@@ -0,0 +1,70 @@
+import logging
+import colorlog
+import sys
+import os
+from dotenv import load_dotenv
+
+# 确保环境变量被加载
+load_dotenv()
+
+def get_log_level() -> int:
+    """从环境变量获取日志级别
+    
+    Returns:
+        int: logging 模块定义的日志级别
+    """
+    level_map = {
+        'DEBUG': logging.DEBUG,
+        'INFO': logging.INFO,
+        'WARNING': logging.WARNING,
+        'ERROR': logging.ERROR,
+        'CRITICAL': logging.CRITICAL
+    }
+    
+    level = os.getenv('LOG_LEVEL', 'INFO').upper()
+    return level_map.get(level, logging.INFO)
+
+def setup_logger(name: str = "DeepClaude") -> logging.Logger:
+    """设置一个彩色的logger
+
+    Args:
+        name (str, optional): logger的名称. Defaults to "DeepClaude".
+
+    Returns:
+        logging.Logger: 配置好的logger实例
+    """
+    logger = colorlog.getLogger(name)
+    
+    if logger.handlers:
+        return logger
+    
+    # 从环境变量获取日志级别
+    log_level = get_log_level()
+    
+    # 设置日志级别
+    logger.setLevel(log_level)
+    
+    # 创建控制台处理器
+    console_handler = logging.StreamHandler(sys.stdout)
+    console_handler.setLevel(log_level)
+    
+    # 设置彩色日志格式
+    formatter = colorlog.ColoredFormatter(
+        "%(log_color)s%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+        datefmt="%Y-%m-%d %H:%M:%S",
+        log_colors={
+            'DEBUG':    'cyan',
+            'INFO':     'green',
+            'WARNING':  'yellow',
+            'ERROR':    'red',
+            'CRITICAL': 'red,bg_white',
+        }
+    )
+    
+    console_handler.setFormatter(formatter)
+    logger.addHandler(console_handler)
+    
+    return logger
+
+# 创建一个默认的logger实例
+logger = setup_logger()

pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "deepclaude"
+version = "0.1.0"
+description = "This is a project for combining DeepSeek and Claude into one api call. Full unleash the power of AI."
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "aiohttp>=3.11.11",
+    "colorlog>=6.9.0",
+    "fastapi>=0.115.8",
+    "python-dotenv>=1.0.1",
+    "uvicorn>=0.34.0",
+]

uv.lock

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