主要修改在asr-monitor-test 修改小程序手机号码登录 小程序的TTS生成(查一查、AI) 增加和支付相关的功能

asr-monitor-test/app/chat_service.py

@@ -0,0 +1,148 @@
+import array
+import asyncio
+import base64
+import binascii
+import datetime
+import gzip
+import io
+import json
+import logging
+import os
+import queue
+import re
+import threading
+import time
+import time
+import uuid
+from collections import deque
+from concurrent.futures import ThreadPoolExecutor
+from copy import deepcopy
+from datetime import timedelta
+from io import BytesIO
+from threading import Lock, Thread
+from timeit import default_timer as timer
+from typing import Optional, Dict, Any
+
+from fastapi import FastAPI, UploadFile, File, Form, Header
+from fastapi import WebSocket, APIRouter, WebSocketDisconnect, Request, Body, Query, Depends
+from fastapi.responses import StreamingResponse, JSONResponse, Response
+from openai import OpenAI
+chat_router = APIRouter()
+
+# 从环境变量读取 OpenAI API 密钥
+openai_api_key = os.getenv("DASHSCOPE_API_KEY")
+if not openai_api_key:
+    raise RuntimeError("DASHSCOPE_API_KEY environment variable not set")
+
+class MillisecondsFormatter(logging.Formatter):
+    """自定义日志格式器，添加毫秒时间戳"""
+    def formatTime(self, record, datefmt=None):
+        # 将时间戳转换为本地时间元组
+        ct = self.converter(record.created)
+        # 格式化为 "小时:分钟:秒"
+        t = time.strftime("%H:%M:%S", ct)
+        # 添加毫秒（3位）
+        return f"{t}.{int(record.msecs):03d}"
+
+# 配置全局日志格式
+def configure_logging():
+    # 创建 Formatter
+    log_format = "%(asctime)s - %(levelname)s - %(message)s"
+    formatter = MillisecondsFormatter(log_format)
+
+    # 获取根 Logger 并清除已有配置
+    root_logger = logging.getLogger()
+    root_logger.handlers = []
+
+    # 创建并配置 Handler（输出到控制台）
+    console_handler = logging.StreamHandler()
+    console_handler.setFormatter(formatter)
+
+    # 设置日志级别并添加 Handler
+    root_logger.setLevel(logging.INFO)
+    root_logger.addHandler(console_handler)
+
+# 调用配置函数（程序启动时运行一次）
+configure_logging()
+
+# 简单的 API 密钥验证（可选）
+def verify_api_key(request: Request):
+    """简单的 API 密钥验证"""
+    if request.headers.get("X-API-KEY") != os.getenv("APP_API_KEY", "default_key"):
+        raise HTTPException(status_code=401, detail="Invalid API key")
+    return True
+
+
+@chat_router.post("/completion")
+async def chat_completion(request: Request):
+    """
+    与大语言模型进行对话
+
+    请求体示例:
+    {
+        "messages": [
+            {"role": "system", "content": "你是一个有帮助的助手"},
+            {"role": "user", "content": "你好，请介绍一下FastAPI"}
+        ],
+        "model": "gpt-3.5-turbo",
+        "temperature": 0.7,
+        "max_tokens": 500
+    }
+    """
+    try:
+        # 手动解析请求体
+        request_data = await request.json()
+
+        # 验证必需字段
+        if "messages" not in request_data or not isinstance(request_data["messages"], list):
+            raise HTTPException(status_code=400, detail="Missing or invalid 'messages' field")
+
+        # 提取参数并提供默认值
+        messages = request_data["messages"]
+        model = request_data.get("model", "qwen-plus-latest")
+        temperature = float(request_data.get("temperature", 0.7))
+        max_tokens = int(request_data.get("max_tokens", 500))
+
+        # 验证消息结构
+        for msg in messages:
+            if "role" not in msg or "content" not in msg:
+                raise HTTPException(status_code=400, detail="Invalid message structure")
+            if not isinstance(msg["role"], str) or not isinstance(msg["content"], str):
+                raise HTTPException(status_code=400, detail="Message content must be strings")
+
+        logging.info(f"Received chat request: model={model}, messages={len(messages)}")
+        client = OpenAI(
+            # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx",
+            api_key=os.getenv("DASHSCOPE_API_KEY"),
+            base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
+        )
+
+        # 调用 OpenAI API
+        response = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature
+        )
+
+        # 处理响应
+        if not response.choices:
+            raise HTTPException(status_code=500, detail="No response from AI model")
+
+        choice = response.choices[0]
+        message = choice.message
+
+        return {
+            "message": {
+                "role": message.role,
+                "content": message.content
+            },
+            "finish_reason": choice.finish_reason
+        }
+
+    except json.JSONDecodeError:
+        raise HTTPException(status_code=400, detail="Invalid JSON format")
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logging.exception("Internal server error")
+        raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")