460 lines
18 KiB
Python
460 lines
18 KiB
Python
"""
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改进版Python FastAPI服务器实现，使用DashScope Python SDK连接阿里云百炼平台API
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"""
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import os
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import json
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import uuid
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import asyncio
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from datetime import datetime
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from typing import Dict, List, Optional, Any
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from pathlib import Path
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from enum import Enum
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import dashscope
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from dashscope import Generation
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from dotenv import load_dotenv
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from fastapi import FastAPI, HTTPException, File, UploadFile, Request
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from fastapi.responses import JSONResponse, StreamingResponse
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from pydantic import BaseModel, Field
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import uvicorn
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# 加载环境变量
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load_dotenv()
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# 设置 DashScope API 密钥
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api_key = os.getenv("ALIYUN_API_KEY")
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if not api_key:
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raise ValueError("请在环境变量中设置 ALIYUN_API_KEY")
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dashscope.api_key = api_key
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# 创建 FastAPI 应用
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app = FastAPI(title="AI Chat API Server (Python)", version="2.0.0")
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# 数据模型定义
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class ChatMessage(BaseModel):
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role: str
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content: str
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images: Optional[List[str]] = None
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files: Optional[List[str]] = None
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class ChatRequest(BaseModel):
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model: str = "qwen-plus"
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messages: List[Dict[str, Any]]
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stream: bool = True
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temperature: Optional[float] = 0.7
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max_tokens: Optional[int] = 2000
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class ModelInfo(BaseModel):
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id: str
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name: str
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description: str
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maxTokens: int
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provider: str
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# 模拟数据库 - 实际应用中应使用持久化存储
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conversations_db: Dict[str, dict] = {}
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# 配置上传目录
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upload_dir = Path("uploads")
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upload_dir.mkdir(exist_ok=True)
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@app.middleware("http")
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async def logging_middleware(request: Request, call_next):
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"""中间件：记录请求日志"""
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start_time = datetime.utcnow()
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# 记录请求信息
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print(f"[INFO] {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - "
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f"HTTP {request.method} {request.url.path} - "
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f"IP: {request.client.host if request.client else 'unknown'}")
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response = await call_next(request)
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# 计算处理时间
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process_time = (datetime.utcnow() - start_time).total_seconds() * 1000
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# 记录响应信息
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print(f"[INFO] {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} - "
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f"Response {response.status_code}, Process Time: {process_time:.2f}ms")
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# 在响应头中添加处理时间
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response.headers["X-Process-Time"] = f"{process_time:.2f}ms"
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return response
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@app.get("/health")
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async def health_check():
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"""健康检查端点"""
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return {"status": "healthy", "timestamp": datetime.utcnow().isoformat()}
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@app.post("/api/chat-ui/chat")
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async def chat_endpoint(request: Request):
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"""
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聊天接口 - 与阿里云百炼API兼容的接口
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这个端点会接收前端的聊天请求并转发到阿里云百炼API
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"""
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try:
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# 获取请求体数据
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body = await request.json()
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# 检查请求格式并适配
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# 如果是OpenAI兼容格式 (来自streamChat)
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if 'messages' in body:
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messages = body.get('messages', [])
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model = body.get('model', 'qwen-plus')
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stream = body.get('stream', True)
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temperature = body.get('temperature', 0.7)
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max_tokens = body.get('max_tokens', 2000)
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else:
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# 否则是前端简化格式 (来自chat函数)
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# 需要将其转换为OpenAI兼容格式
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message_text = body.get('message', '')
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# 检查message是否已经是格式化的列表（带图片的情况）
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if isinstance(message_text, list):
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user_content = message_text
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else:
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# 如果是字符串，转换为标准格式
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user_content = [{"type": "text", "text": message_text}]
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messages = [
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{"role": "system", "content": body.get('systemPrompt', '你是一个支持视觉理解的助手。')},
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{"role": "user", "content": user_content}
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]
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model = body.get('model', 'qwen-plus')
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stream = body.get('stream', False) # 默认为非流式
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temperature = body.get('temperature', 0.7)
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max_tokens = body.get('maxTokens', 2000)
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if stream:
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# 流式响应
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async def event_generator():
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try:
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responses = Generation.call(
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model=model,
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messages=messages,
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stream=True,
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max_tokens=max_tokens,
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temperature=temperature
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)
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full_content = "" # 用于累计完整内容
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for idx, response in enumerate(responses):
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if response.status_code == 200:
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# 检查响应是否包含预期的内容
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# DashScope API的响应结构可能是 output.choices 或 output.text
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content = None
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# 尝试从 output.choices 获取内容
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if (hasattr(response, 'output') and
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response.output and
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hasattr(response.output, 'choices') and
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response.output.choices is not None and
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len(response.output.choices) > 0 and
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'message' in response.output.choices[0] and
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'content' in response.output.choices[0]['message']):
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content = response.output.choices[0]['message']['content']
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# 只有当内容发生变化时才发送增量
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if len(content) > len(full_content):
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delta_content = content[len(full_content):]
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full_content = content
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if delta_content.strip(): # 只有当有非空白新内容时才发送
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# 构建 SSE 数据块
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data = {
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"id": f"chatcmpl-{uuid.uuid4()}",
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"object": "chat.completion.chunk",
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"created": int(datetime.utcnow().timestamp()),
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"model": model,
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"choices": [
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{
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"index": 0,
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"delta": {"content": delta_content},
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"finish_reason": None
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}
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]
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}
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yield f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
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# 否则尝试从 output.text 获取内容（DashScope特定格式）
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elif (hasattr(response, 'output') and
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response.output and
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'text' in response.output):
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content = response.output.get('text')
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# 只有当内容发生变化时才发送增量
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if len(content) > len(full_content):
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delta_content = content[len(full_content):]
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full_content = content
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if delta_content.strip(): # 只有当有非空白新内容时才发送
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# 构建 SSE 数据块
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data = {
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"id": f"chatcmpl-{uuid.uuid4()}",
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"object": "chat.completion.chunk",
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"created": int(datetime.utcnow().timestamp()),
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"model": model,
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"choices": [
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{
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"index": 0,
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"delta": {"content": delta_content},
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"finish_reason": None
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}
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]
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}
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yield f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
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else:
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# 错误处理
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error_data = {
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"error": {
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"message": f"API Error: {response.code} - {response.message}",
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"type": "api_error",
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"param": None,
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"code": response.code
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}
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}
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yield f"data: {json.dumps(error_data, ensure_ascii=False)}\n\n"
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break
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# 发送结束信号
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finish_data = {
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"id": f"chatcmpl-{uuid.uuid4()}",
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"object": "chat.completion.chunk",
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"created": int(datetime.utcnow().timestamp()),
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"model": model,
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"choices": [
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{
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"index": 0,
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"delta": {},
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"finish_reason": "stop"
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}
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]
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}
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yield f"data: {json.dumps(finish_data, ensure_ascii=False)}\n\n"
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yield "data: [DONE]\n\n"
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except Exception as e:
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error_data = {
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"error": {
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"message": str(e),
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"type": "server_error"
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}
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}
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yield f"data: {json.dumps(error_data, ensure_ascii=False)}\n\n"
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return StreamingResponse(event_generator(), media_type="text/event-stream")
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else:
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# 非流式响应
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response = Generation.call(
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model=model,
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messages=messages,
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stream=False,
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max_tokens=max_tokens,
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temperature=temperature
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)
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if response.status_code == 200:
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# 检查响应是否包含预期的内容
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# DashScope API的响应结构可能是 output.choices 或 output.text
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content = None
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# 尝试从 output.choices 获取内容
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if (hasattr(response, 'output') and
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response.output and
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hasattr(response.output, 'choices') and
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response.output.choices is not None and
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len(response.output.choices) > 0 and
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'message' in response.output.choices[0] and
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'content' in response.output.choices[0]['message']):
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content = response.output.choices[0]['message']['content']
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# 否则尝试从 output.text 获取内容（DashScope特定格式）
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elif (hasattr(response, 'output') and
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response.output and
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'text' in response.output):
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content = response.output.get('text')
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if content:
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# 构建前端期望的响应格式
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chat_response = {
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"id": str(uuid.uuid4()),
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"conversationId": body.get('conversationId', str(uuid.uuid4())),
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"content": content,
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"model": model,
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"createdAt": int(datetime.utcnow().timestamp())
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}
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if hasattr(response, 'usage') and response.usage:
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chat_response["usage"] = {
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"promptTokens": response.usage.input_tokens,
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"completionTokens": response.usage.output_tokens,
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"totalTokens": response.usage.total_tokens
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}
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return JSONResponse(content=chat_response, ensure_ascii=False)
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else:
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raise HTTPException(
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status_code=500,
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detail="API Response does not contain expected content"
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)
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else:
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raise HTTPException(
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status_code=500,
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detail=f"API Error: {response.code} - {response.message}"
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)
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except Exception as e:
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print(f"[ERROR] Error in chat endpoint: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/api/chat-ui/models")
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async def get_models():
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"""获取模型列表"""
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models = [
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ModelInfo(
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id="qwen-max",
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name="通义千问 Max",
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description="最强大的模型",
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maxTokens=8192,
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provider="Aliyun"
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),
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ModelInfo(
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id="qwen-plus",
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name="通义千问 Plus",
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description="能力均衡",
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maxTokens=8192,
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provider="Aliyun"
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),
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ModelInfo(
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id="qwen-turbo",
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name="通义千问 Turbo",
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description="速度更快、成本更低",
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maxTokens=8192,
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provider="Aliyun"
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)
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]
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return [model.dict() for model in models]
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@app.get("/api/chat-ui/conversations")
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async def get_conversations():
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"""获取所有对话"""
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return list(conversations_db.values())
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@app.get("/api/chat-ui/conversations/{conversation_id}")
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async def get_conversation(conversation_id: str):
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"""获取特定对话"""
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conversation = conversations_db.get(conversation_id)
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if not conversation:
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raise HTTPException(status_code=404, detail="对话不存在")
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return conversation
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@app.post("/api/chat-ui/conversations")
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async def save_conversation(request: Request):
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"""保存或更新对话"""
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try:
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data = await request.json()
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conversation_id = data.get('id') or str(uuid.uuid4())
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conversation = {
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"id": conversation_id,
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"title": data.get('title', '新对话'),
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"messages": data.get('messages', []),
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"updatedAt": datetime.utcnow().isoformat(),
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"createdAt": data.get('createdAt', datetime.utcnow().isoformat())
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}
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conversations_db[conversation_id] = conversation
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return conversation
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except Exception as e:
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print(f"[ERROR] Error saving conversation: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.delete("/api/chat-ui/conversations/{conversation_id}")
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async def delete_conversation(conversation_id: str):
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"""删除对话"""
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if conversation_id in conversations_db:
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del conversations_db[conversation_id]
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return {"success": True, "message": "删除成功"}
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else:
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raise HTTPException(status_code=404, detail="对话不存在")
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@app.post("/api/chat-ui/upload")
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async def upload_file(file: UploadFile = File(...)):
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"""文件上传接口"""
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try:
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# 检查文件类型
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allowed_types = ['image/jpeg', 'image/png', 'image/gif', 'image/webp', 'text/plain', 'application/pdf']
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if file.content_type not in allowed_types:
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raise HTTPException(status_code=400, detail=f"不支持的文件类型: {file.content_type}")
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# 生成唯一文件名
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file_extension = Path(file.filename).suffix.lower()
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unique_filename = f"{int(datetime.utcnow().timestamp())}_{uuid.uuid4()}{file_extension}"
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file_path = upload_dir / unique_filename
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# 保存文件
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with open(file_path, "wb") as f:
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content = await file.read()
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f.write(content)
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# 返回文件信息
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file_url = f"http://localhost:8000/uploads/{unique_filename}"
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result = {
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"url": file_url,
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"name": file.filename,
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"size": len(content),
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"mimeType": file.content_type
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}
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print(f"[INFO] File uploaded: {result}")
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return result
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except Exception as e:
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print(f"[ERROR] Upload error: {str(e)}")
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raise HTTPException(status_code=500, detail=f"上传失败: {str(e)}")
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@app.get("/uploads/{filename}")
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async def serve_upload(filename: str):
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"""提供上传文件的访问"""
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file_path = upload_dir / filename
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if not file_path.exists():
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raise HTTPException(status_code=404, detail="文件不存在")
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from fastapi.responses import FileResponse
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return FileResponse(str(file_path))
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@app.post("/api/chat-ui/stop")
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async def stop_generation():
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"""停止生成接口"""
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# 在实际实现中，这里可能需要维护正在运行的任务ID列表
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# 目前只是返回成功消息
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return {"success": True, "message": "已发出停止指令"}
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@app.post("/api/chat-ui/stop/{message_id}")
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async def stop_generation_by_id(message_id: str):
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"""根据消息ID停止生成"""
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return {"success": True, "message": "已发出停止指令，消息ID: " + message_id}
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if __name__ == "__main__":
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port = int(os.getenv("PORT", 8000))
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print("="*50)
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print(f"Python AI Chat Server 启动中...")
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print(f"监听端口: {port}")
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print(f"API Key 状态: {'已配置' if api_key else '未配置'}")
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print("="*50)
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if not api_key:
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print("警告: 未在环境变量中检测到 ALIYUN_API_KEY!")
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print("请在 .env 文件中添加您的百炼 API Key。")
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else:
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print("API Key 已检测到。")
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uvicorn.run(app, host="0.0.0.0", port=port) |