commit 67b4558ef013e8ebc13e07bb0ec5db6db0d2a882 Author: LzSkyline Date: Tue Jan 7 15:16:09 2025 +0800 init. diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..45dcd86 --- /dev/null +++ b/.env.example @@ -0,0 +1,10 @@ +# Dify Model Configurations +# Format: JSON string in one line +MODEL_CONFIG={"claude-3-5-sonnet-v2":"app-xxxxxxxxxxxxxxxx","gemini-2.0-flash-thinking-exp-1219":"app-xxxxxxxxxxxxxxxx","o1-preview":"app-xxxxxxxxxxxxxxxx"} + +# Dify API Base URL +DIFY_API_BASE="https://api.dify.example.com/v1" + +# Server Configuration +SERVER_HOST="127.0.0.1" +SERVER_PORT=5000 \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..24119b5 --- /dev/null +++ b/.gitignore @@ -0,0 +1,64 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# Virtual Environment +venv/ +env/ +ENV/ +.env + +# IDE +.idea/ +.vscode/ +*.swp +*.swo +.DS_Store + +# Logs +*.log +logs/ + +# Local development +.env +.env.local +.env.*.local + +# Testing +.coverage +htmlcov/ +.pytest_cache/ +.tox/ +.nox/ +coverage.xml +*.cover +.hypothesis/ + +# Distribution +*.pyc +*.pyo +*.pyd +.Python +*.so + +# Project specific +*.pid +*.sock \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..0e805c1 --- /dev/null +++ b/README.md @@ -0,0 +1,168 @@ +# OpenDify + +OpenDify 是一个将 Dify API 转换为 OpenAI API 格式的代理服务器。它允许使用 OpenAI API 客户端直接与 Dify 服务进行交互。 + +> 🌟 本项目完全由 Cursor + Claude-3.5 自动生成，未手动编写任何代码（包括此Readme），向 AI 辅助编程的未来致敬！ + +## 功能特点 + +- 完整支持 OpenAI API 格式转换为 Dify API +- 支持流式输出（Streaming） +- 智能动态延迟控制，提供流畅的输出体验 +- 支持多个模型配置 +- 完整的错误处理和日志记录 +- 兼容标准的 OpenAI API 客户端 +- 灵活的模型配置支持 + +## 支持的模型 + +支持任意 Dify 模型，只需在配置文件中添加对应的 API Key 即可。 + +## 快速开始 + +### 环境要求 + +- Python 3.9+ +- pip + +### 安装依赖 + +```bash +pip install -r requirements.txt +``` + +### 配置 + +1. 复制 `.env.example` 文件并重命名为 `.env`： +```bash +cp .env.example .env +``` + +2. 在 Dify 平台配置应用： + - 登录 Dify 平台，进入工作室 + - 点击"创建应用"，配置好需要的模型（如 Claude、Gemini 等） + - 配置应用的提示语和其他参数 + - 发布应用 + - 进入"访问 API"页面，生成 API 密钥 + + > **重要说明**：Dify 不支持在请求时动态传入提示词、切换模型及其他参数。所有这些配置都需要在创建应用时设置好。Dify 会根据 API 密钥来确定使用哪个应用及其对应的配置。 + +3. 在 `.env` 文件中配置你的 Dify 模型和 API Keys： +```env +# Dify Model Configurations +# 注意：必须是单行的 JSON 字符串格式 +MODEL_CONFIG={"claude-3-5-sonnet-v2":"your-claude-api-key","custom-model":"your-custom-api-key"} + +# Dify API Base URL +DIFY_API_BASE="https://your-dify-api-base-url/v1" + +# Server Configuration +SERVER_HOST="127.0.0.1" +SERVER_PORT=5000 +``` + +你可以根据需要添加或删除模型配置，但必须保持 JSON 格式在单行内。这是因为 python-dotenv 的限制。 + +每个模型配置的格式为：`"模型名称": "Dify应用的API密钥"`。其中： +- 模型名称：可以自定义，用于在 API 调用时识别不同的应用 +- API 密钥：从 Dify 平台获取的应用 API 密钥 + +例如，如果你在 Dify 上创建了一个使用 Claude 的翻译应用和一个使用 Gemini 的代码助手应用，可以这样配置： +```env +MODEL_CONFIG={"translator":"app-xxxxxx","code-assistant":"app-yyyyyy"} +``` + +### 运行服务 + +```bash +python openai_to_dify.py +``` + +服务将在 `http://127.0.0.1:5000` 启动 + +## API 使用 + +### List Models + +获取所有可用模型列表： + +```python +import openai + +openai.api_base = "http://127.0.0.1:5000/v1" +openai.api_key = "any" # 可以使用任意值 + +# 获取可用模型列表 +models = openai.Model.list() +print(models) + +# 输出示例： +{ + "object": "list", + "data": [ + { + "id": "claude-3-5-sonnet-v2", + "object": "model", + "created": 1704603847, + "owned_by": "dify" + }, + { + "id": "gemini-2.0-flash-thinking-exp-1219", + "object": "model", + "created": 1704603847, + "owned_by": "dify" + }, + // ... 其他在 MODEL_CONFIG 中配置的模型 + ] +} +``` + +只有在 `.env` 文件的 `MODEL_CONFIG` 中配置了 API Key 的模型才会出现在列表中。 + +### Chat Completions + +```python +import openai + +openai.api_base = "http://127.0.0.1:5000/v1" +openai.api_key = "any" # 可以使用任意值 + +response = openai.ChatCompletion.create( + model="claude-3-5-sonnet-v2", # 使用在 MODEL_CONFIG 中配置的模型名称 + messages=[ + {"role": "user", "content": "你好"} + ], + stream=True +) + +for chunk in response: + print(chunk.choices[0].delta.content or "", end="") +``` + +## 特性说明 + +### 流式输出优化 + +- 智能缓冲区管理 +- 动态延迟计算 +- 平滑的输出体验 + +### 错误处理 + +- 完整的错误捕获和处理 +- 详细的日志记录 +- 友好的错误提示 + +### 配置灵活性 + +- 支持动态添加新模型 +- 支持 JSON 格式配置 +- 支持自定义模型名称 + +## 贡献指南 + +欢迎提交 Issue 和 Pull Request 来帮助改进项目。 + +## 许可证 + +[MIT License](LICENSE) \ No newline at end of file diff --git a/main.py b/main.py new file mode 100644 index 0000000..bdebf6d --- /dev/null +++ b/main.py @@ -0,0 +1,395 @@ +import json +import logging +import asyncio +from flask import Flask, request, Response, stream_with_context +import httpx +import time +from dotenv import load_dotenv +import os +import ast + +# 配置日志 +logging.basicConfig( + level=logging.DEBUG, + format='%(asctime)s - %(levelname)s - %(message)s' +) +logger = logging.getLogger(__name__) + +# 设置 httpx 的日志级别 +logging.getLogger("httpx").setLevel(logging.DEBUG) + +# 加载环境变量 +load_dotenv() + +def parse_model_config(): + """ + 从环境变量解析模型配置 + 返回一个字典 {model_name: api_key} + """ + try: + config_str = os.getenv('MODEL_CONFIG', '{}') + # 尝试作为Python字典解析 + try: + return ast.literal_eval(config_str) + except (SyntaxError, ValueError) as e: + logger.error(f"Failed to parse MODEL_CONFIG as Python dict: {e}") + try: + # 尝试作为JSON解析 + return json.loads(config_str) + except json.JSONDecodeError as e: + logger.error(f"Failed to parse MODEL_CONFIG as JSON: {e}") + return {} + except Exception as e: + logger.error(f"Error parsing MODEL_CONFIG: {e}") + return {} + +# 从环境变量获取配置 +MODEL_TO_API_KEY = parse_model_config() + +# 根据MODEL_TO_API_KEY自动生成模型信息 +AVAILABLE_MODELS = [ + { + "id": model_id, + "object": "model", + "created": int(time.time()), + "owned_by": "dify" + } + for model_id, api_key in MODEL_TO_API_KEY.items() + if api_key is not None # 只包含配置了API Key的模型 +] + +app = Flask(__name__) + +# 从环境变量获取API基础URL +DIFY_API_BASE = os.getenv("DIFY_API_BASE", "https://mify-be.pt.xiaomi.com/api/v1") + +def get_api_key(model_name): + """根据模型名称获取对应的API密钥""" + api_key = MODEL_TO_API_KEY.get(model_name) + if not api_key: + logger.warning(f"No API key found for model: {model_name}") + return api_key + +def transform_openai_to_dify(openai_request, endpoint): + """将OpenAI格式的请求转换为Dify格式""" + + if endpoint == "/chat/completions": + messages = openai_request.get("messages", []) + stream = openai_request.get("stream", False) + + dify_request = { + "inputs": {}, + "query": messages[-1]["content"] if messages else "", + "response_mode": "streaming" if stream else "blocking", + "conversation_id": openai_request.get("conversation_id", None), + "user": openai_request.get("user", "default_user") + } + + # 添加历史消息 + if len(messages) > 1: + history = [] + for msg in messages[:-1]: # 除了最后一条消息 + history.append({ + "role": msg["role"], + "content": msg["content"] + }) + dify_request["conversation_history"] = history + + return dify_request + + return None + +def transform_dify_to_openai(dify_response, model="claude-3-5-sonnet-v2", stream=False): + """将Dify格式的响应转换为OpenAI格式""" + + if not stream: + return { + "id": dify_response.get("message_id", ""), + "object": "chat.completion", + "created": dify_response.get("created", int(time.time())), + "model": model, # 使用实际使用的模型 + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": dify_response.get("answer", "") + }, + "finish_reason": "stop" + }] + } + else: + # 流式响应的转换在stream_response函数中处理 + return dify_response + +def create_openai_stream_response(content, message_id, model="claude-3-5-sonnet-v2"): + """创建OpenAI格式的流式响应""" + return { + "id": message_id, + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "delta": { + "content": content + }, + "finish_reason": None + }] + } + +@app.route('/v1/chat/completions', methods=['POST']) +def chat_completions(): + try: + openai_request = request.get_json() + logger.info(f"Received request: {json.dumps(openai_request, ensure_ascii=False)}") + + model = openai_request.get("model", "claude-3-5-sonnet-v2") + logger.info(f"Using model: {model}") + + # 验证模型是否支持 + api_key = get_api_key(model) + if not api_key: + error_msg = f"Model {model} is not supported. Available models: {', '.join(MODEL_TO_API_KEY.keys())}" + logger.error(error_msg) + return { + "error": { + "message": error_msg, + "type": "invalid_request_error", + "code": "model_not_found" + } + }, 404 + + dify_request = transform_openai_to_dify(openai_request, "/chat/completions") + logger.info(f"Transformed request: {json.dumps(dify_request, ensure_ascii=False)}") + + if not dify_request: + logger.error("Failed to transform request") + return { + "error": { + "message": "Invalid request format", + "type": "invalid_request_error", + } + }, 400 + + headers = { + "Authorization": f"Bearer {api_key}", + "Content-Type": "application/json" + } + + stream = openai_request.get("stream", False) + dify_endpoint = f"{DIFY_API_BASE}/chat-messages" + logger.info(f"Sending request to Dify endpoint: {dify_endpoint}, stream={stream}") + + if stream: + def generate(): + client = httpx.Client(timeout=None) + + def flush_chunk(chunk_data): + """Helper function to flush chunks immediately""" + return chunk_data.encode('utf-8') + + def calculate_delay(buffer_size): + """ + 根据缓冲区大小动态计算延迟 + buffer_size: 缓冲区中剩余的字符数量 + """ + if buffer_size > 30: # 缓冲区内容较多，快速输出 + return 0.001 # 5ms延迟 + elif buffer_size > 20: # 中等数量，适中速度 + return 0.002 # 10ms延迟 + elif buffer_size > 10: # 较少内容，稍慢速度 + return 0.01 # 20ms延迟 + else: # 内容很少，使用较慢的速度 + return 0.02 # 30ms延迟 + + def send_char(char, message_id): + """Helper function to send single character""" + openai_chunk = { + "id": message_id, + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "delta": { + "content": char + }, + "finish_reason": None + }] + } + chunk_data = f"data: {json.dumps(openai_chunk)}\n\n" + return flush_chunk(chunk_data) + + # 初始化缓冲区 + output_buffer = [] + + try: + with client.stream( + 'POST', + dify_endpoint, + json=dify_request, + headers={ + **headers, + 'Accept': 'text/event-stream', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive' + } + ) as response: + generate.message_id = None + buffer = "" + + for raw_bytes in response.iter_raw(): + if not raw_bytes: + continue + + try: + buffer += raw_bytes.decode('utf-8') + + while '\n' in buffer: + line, buffer = buffer.split('\n', 1) + line = line.strip() + + if not line or not line.startswith('data: '): + continue + + try: + json_str = line[6:] + dify_chunk = json.loads(json_str) + + if dify_chunk.get("event") == "message" and "answer" in dify_chunk: + current_answer = dify_chunk["answer"] + if not current_answer: + continue + + message_id = dify_chunk.get("message_id", "") + if not generate.message_id: + generate.message_id = message_id + + # 将当前批次的字符添加到输出缓冲区 + for char in current_answer: + output_buffer.append((char, generate.message_id)) + + # 根据缓冲区大小动态调整输出速度 + while output_buffer: + char, msg_id = output_buffer.pop(0) + yield send_char(char, msg_id) + # 根据剩余缓冲区大小计算延迟 + delay = calculate_delay(len(output_buffer)) + time.sleep(delay) + + # 立即继续处理下一个请求 + continue + + elif dify_chunk.get("event") == "message_end": + # 快速输出剩余内容 + while output_buffer: + char, msg_id = output_buffer.pop(0) + yield send_char(char, msg_id) + time.sleep(0.001) # 固定使用最小延迟快速输出剩余内容 + + final_chunk = { + "id": generate.message_id, + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "delta": {}, + "finish_reason": "stop" + }] + } + yield flush_chunk(f"data: {json.dumps(final_chunk)}\n\n") + yield flush_chunk("data: [DONE]\n\n") + + except json.JSONDecodeError as e: + logger.error(f"JSON decode error: {str(e)}") + continue + + except Exception as e: + logger.error(f"Error processing chunk: {str(e)}") + continue + + finally: + client.close() + + return Response( + stream_with_context(generate()), + content_type='text/event-stream', + headers={ + 'Cache-Control': 'no-cache, no-transform', + 'Connection': 'keep-alive', + 'Transfer-Encoding': 'chunked', + 'X-Accel-Buffering': 'no', + 'Content-Encoding': 'none' + }, + direct_passthrough=True + ) + else: + async def sync_response(): + try: + async with httpx.AsyncClient() as client: + response = await client.post( + dify_endpoint, + json=dify_request, + headers=headers + ) + + if response.status_code != 200: + error_msg = f"Dify API error: {response.text}" + logger.error(f"Request failed: {error_msg}") + return { + "error": { + "message": error_msg, + "type": "api_error", + "code": response.status_code + } + }, response.status_code + + dify_response = response.json() + logger.info(f"Received response from Dify: {json.dumps(dify_response, ensure_ascii=False)}") + openai_response = transform_dify_to_openai(dify_response, model=model) + return openai_response + except httpx.RequestError as e: + error_msg = f"Failed to connect to Dify: {str(e)}" + logger.error(error_msg) + return { + "error": { + "message": error_msg, + "type": "api_error", + "code": "connection_error" + } + }, 503 + + return asyncio.run(sync_response()) + + except Exception as e: + logger.exception("Unexpected error occurred") + return { + "error": { + "message": str(e), + "type": "internal_error", + } + }, 500 + +@app.route('/v1/models', methods=['GET']) +def list_models(): + """返回可用的模型列表""" + logger.info("Listing available models") + # 过滤掉没有API密钥的模型 + available_models = [ + model for model in AVAILABLE_MODELS + if MODEL_TO_API_KEY.get(model["id"]) + ] + + response = { + "object": "list", + "data": available_models + } + logger.info(f"Available models: {json.dumps(response, ensure_ascii=False)}") + return response + +if __name__ == '__main__': + host = os.getenv("SERVER_HOST", "127.0.0.1") + port = int(os.getenv("SERVER_PORT", 5000)) + logger.info(f"Starting server on http://{host}:{port}") + app.run(debug=True, host=host, port=port) diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..c5c715e --- /dev/null +++ b/requirements.txt @@ -0,0 +1,4 @@ +flask +httpx +python-dotenv +logging \ No newline at end of file