deploy: Launch ap3 service on port 7862
Browse files- Dockerfile +14 -0
- README.md +10 -6
- app.py +368 -0
- requirements.txt +5 -0
Dockerfile
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FROM python:3.11-slim
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WORKDIR /app
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COPY ./requirements.txt /app/requirements.txt
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RUN pip install --no-cache-dir --upgrade -r /app/requirements.txt
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COPY ./app.py /app/
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# Hugging Face 通过下面的 README.md 中的 app_port 来映射端口
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EXPOSE 7862
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# 直接运行 uvicorn,监听 7862 端口
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CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7862"]
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README.md
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---
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-
title:
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emoji:
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colorFrom:
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colorTo:
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sdk: docker
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-
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---
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-
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---
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title: GenAI API Service (ap3)
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emoji: 🛰️
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colorFrom: red
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colorTo: yellow
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sdk: docker
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app_port: 7862
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---
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This is a professional-grade FastAPI application that proxies requests to the Google GenAI API on port 7862.
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- **`POST /v1/chat/completions`**: Main endpoint for chat, supports streaming.
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- **`GET /v1/models`**: Lists available models.
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- **`GET /health`**: Health check.
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- **`GET /`**: API Info.
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app.py
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import logging
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import json
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import time
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import asyncio
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import os
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import traceback
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import sys
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from contextlib import asynccontextmanager
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import random
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import uvicorn
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from fastapi import FastAPI, Request, HTTPException
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from fastapi.responses import StreamingResponse, JSONResponse
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from fastapi.middleware.cors import CORSMiddleware
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# 正确的导入方式
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import google.generativeai as genai
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from typing import Optional, List, Dict, Any
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# 简化日志配置
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s]: %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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logger = logging.getLogger(__name__)
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# 模型配置
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GEMINI_MODELS = {
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"gemini-2.0-flash-exp": "gemini-2.0-flash-exp",
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"gemini-2.5-flash-preview-05-20": "gemini-2.5-flash-preview-05-20",
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"gemini-2.5-flash": "gemini-2.5-flash",
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"gemini-2.5-flash-preview-04-17": "gemini-2.5-flash-preview-04-17"
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}
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# 支持的模型列表
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SUPPORTED_MODELS = [
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{
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"id": "gemini-2.5-flash-preview-05-20",
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"object": "model",
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"created": int(time.time()),
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"owned_by": "google",
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"permission": [],
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"root": "gemini-2.5-flash-preview-05-20",
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"parent": None,
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"description": "Gemini 2.5 Flash Preview - 最新实验性模型"
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},
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{
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"id": "gemini-2.5-flash-preview-04-17",
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"object": "model",
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"created": int(time.time()),
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"owned_by": "google",
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"permission": [],
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"root": "gemini-2.5-flash-preview-04-17",
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"parent": None,
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"description": "gemini-2.5-flash-preview-04-17- 经典专业模型"
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},
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{
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"id": "gemini-2.5-flash",
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"object": "model",
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"created": int(time.time()),
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"owned_by": "google",
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"permission": [],
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"root": "gemini-2.5-flash",
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"parent": None,
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"description": "gemini-2.5-flash稳定经典专业模型"
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}
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]
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def get_model_name(requested_model: str) -> str:
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"""获取实际的Gemini模型名称"""
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return GEMINI_MODELS.get(requested_model, "gemini-2.5-flash")
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def convert_messages(messages):
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content_parts = []
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system_instruction = None
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for message in messages:
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role = message.get("role", "user")
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content = message.get("content", "")
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if role == "system":
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system_instruction = content
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elif role == "assistant":
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content_parts.append({
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"role": "model",
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"parts": [{"text": content}]
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})
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elif role == "user":
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content_parts.append({
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"role": "user",
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"parts": [{"text": content}]
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})
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return content_parts, system_instruction
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def handle_error(error):
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"""简化的错误处理"""
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error_str = str(error).lower()
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if "prompt_feedback" in error_str:
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if "other" in error_str:
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return "您的输入内容可能过长或触发了安全策略。请尝试缩短您的问题。", "length"
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elif "safety" in error_str:
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return "您的请求被安全策略阻止。请尝试修改您的问题。", "content_filter"
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elif "safety" in error_str:
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return "您的请求被安全策略过滤。请尝试修改您的问题。", "content_filter"
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return "生成内容时遇到错误。请稍后重试。", "stop"
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def get_random_api_key():
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"""获取随机API密钥"""
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return random.choice(API_KEYS)
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def setup_gemini(api_key=None):
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"""配置Gemini API"""
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if not api_key:
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api_key = get_random_api_key()
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if not API_KEYS:
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logger.error("请设置有效的API密钥列表")
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raise ValueError("API_KEYS未设置")
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genai.configure(api_key=api_key)
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return api_key
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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try:
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setup_gemini()
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logger.info("应用启动完成")
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yield
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except Exception as e:
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logger.error(f"应用启动失败: {str(e)}")
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finally:
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logger.info("应用关闭")
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# 创建FastAPI应用实例
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app = FastAPI(
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lifespan=lifespan,
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title="Gemini Official API (ap3)",
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version="1.3.0"
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)
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# 添加CORS中间件
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# API密钥列表 (已更新为您提供的新密钥)
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API_KEYS = [
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'AIzaSyDglvTu5EbXfcBMsv1gBjSH7TOtZxNsQuo',
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160 |
+
'AIzaSyBOT0mNoemVm-VEwL3YNOAQu_tirwYJDyE'
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]
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162 |
+
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163 |
+
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164 |
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# 配置安全设置
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SAFETY_SETTINGS = [
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genai.types.SafetySetting(
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category=genai.types.HarmCategory.HARM_CATEGORY_HARASSMENT,
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threshold=genai.types.HarmBlockThreshold.BLOCK_NONE,
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),
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genai.types.SafetySetting(
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category=genai.types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
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threshold=genai.types.HarmBlockThreshold.BLOCK_NONE,
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),
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genai.types.SafetySetting(
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category=genai.types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
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threshold=genai.types.HarmBlockThreshold.BLOCK_NONE,
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177 |
+
),
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178 |
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genai.types.SafetySetting(
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category=genai.types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
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180 |
+
threshold=genai.types.HarmBlockThreshold.BLOCK_NONE,
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181 |
+
),
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182 |
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genai.types.SafetySetting(
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183 |
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category=genai.types.HarmCategory.HARM_CATEGORY_CIVIC_INTEGRITY,
|
184 |
+
threshold=genai.types.HarmBlockThreshold.BLOCK_NONE,
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185 |
+
),
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186 |
+
]
|
187 |
+
|
188 |
+
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189 |
+
async def try_generate_content(model_name, content_parts, system_instruction, config, max_retries=3):
|
190 |
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"""带重试机制的内容生成"""
|
191 |
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last_error = None
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192 |
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used_keys = set()
|
193 |
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model = None
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194 |
+
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195 |
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for attempt in range(max_retries):
|
196 |
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try:
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197 |
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available_keys = [key for key in API_KEYS if key not in used_keys]
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198 |
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if not available_keys:
|
199 |
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used_keys.clear()
|
200 |
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available_keys = API_KEYS
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201 |
+
|
202 |
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api_key = random.choice(available_keys)
|
203 |
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used_keys.add(api_key)
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204 |
+
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205 |
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setup_gemini(api_key)
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206 |
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model = genai.GenerativeModel(model_name, system_instruction=system_instruction)
|
207 |
+
logger.info(f"尝试第 {attempt + 1} 次,使用密钥: {api_key[:10]}...")
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208 |
+
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209 |
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response = await model.generate_content_async(
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210 |
+
contents=content_parts,
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211 |
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generation_config=config,
|
212 |
+
safety_settings=SAFETY_SETTINGS,
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213 |
+
)
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214 |
+
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215 |
+
return response, api_key
|
216 |
+
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217 |
+
except Exception as e:
|
218 |
+
last_error = e
|
219 |
+
error_str = str(e).lower()
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220 |
+
|
221 |
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if any(code in error_str for code in ['400', '401', '403', '429', '500', '502', '503', '504']):
|
222 |
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logger.warning(f"第 {attempt + 1} 次尝试失败: {str(e)}")
|
223 |
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if attempt < max_retries - 1:
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await asyncio.sleep(1)
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continue
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226 |
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else:
|
227 |
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raise e
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229 |
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raise last_error
|
230 |
+
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231 |
+
|
232 |
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@app.post("/v1/chat/completions")
|
233 |
+
async def chat_completions(request: Request):
|
234 |
+
"""聊天对话接口"""
|
235 |
+
try:
|
236 |
+
body = await request.json()
|
237 |
+
messages = body.get('messages', [])
|
238 |
+
stream = body.get('stream', False)
|
239 |
+
|
240 |
+
requested_model = body.get('model', 'gemini-2.5-flash')
|
241 |
+
model_name = get_model_name(requested_model)
|
242 |
+
|
243 |
+
content_parts, system_instruction = convert_messages(messages)
|
244 |
+
|
245 |
+
config = genai.types.GenerationConfig(
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246 |
+
max_output_tokens=body.get('max_tokens', 65536),
|
247 |
+
temperature=body.get('temperature', 1.0),
|
248 |
+
top_p=body.get('top_p', 1.0),
|
249 |
+
)
|
250 |
+
|
251 |
+
if stream:
|
252 |
+
return StreamingResponse(
|
253 |
+
stream_response_with_retry(model_name, content_parts, system_instruction, config),
|
254 |
+
media_type='text/event-stream'
|
255 |
+
)
|
256 |
+
else:
|
257 |
+
response, used_key = await try_generate_content(model_name, content_parts, system_instruction, config)
|
258 |
+
response_text = response.text if response else ""
|
259 |
+
finish_reason = "stop"
|
260 |
+
|
261 |
+
if not response_text:
|
262 |
+
response_text = "无法生成回复。请尝试修改您的问题。"
|
263 |
+
|
264 |
+
logger.info(f"成功生成回复,使用密钥: {used_key[:10]}...")
|
265 |
+
return {
|
266 |
+
'id': f'chatcmpl-{int(time.time())}-{random.randint(1000, 9999)}',
|
267 |
+
'object': 'chat.completion', 'created': int(time.time()), 'model': requested_model,
|
268 |
+
'choices': [{'index': 0, 'message': {'role': 'assistant', 'content': response_text}, 'finish_reason': finish_reason}],
|
269 |
+
'usage': {'prompt_tokens': 0, 'completion_tokens': 0, 'total_tokens': 0}
|
270 |
+
}
|
271 |
+
except Exception as e:
|
272 |
+
logger.error(f"处理聊天请求出错: {traceback.format_exc()}")
|
273 |
+
error_message, finish_reason = handle_error(e)
|
274 |
+
raise HTTPException(status_code=500, detail=error_message)
|
275 |
+
|
276 |
+
|
277 |
+
async def stream_response_with_retry(model_name, content_parts, system_instruction, config, max_retries=3):
|
278 |
+
"""带重试机制的流式响应生成器"""
|
279 |
+
last_error = None
|
280 |
+
used_keys = set()
|
281 |
+
for attempt in range(max_retries):
|
282 |
+
try:
|
283 |
+
available_keys = [key for key in API_KEYS if key not in used_keys]
|
284 |
+
if not available_keys:
|
285 |
+
used_keys.clear()
|
286 |
+
available_keys = API_KEYS
|
287 |
+
api_key = random.choice(available_keys)
|
288 |
+
used_keys.add(api_key)
|
289 |
+
|
290 |
+
setup_gemini(api_key)
|
291 |
+
model = genai.GenerativeModel(model_name, system_instruction=system_instruction)
|
292 |
+
logger.info(f"流式响应尝试第 {attempt + 1} 次,使用密钥: {api_key[:10]}...")
|
293 |
+
|
294 |
+
async for chunk in await model.generate_content_async(contents=content_parts, generation_config=config, safety_settings=SAFETY_SETTINGS, stream=True):
|
295 |
+
if chunk and hasattr(chunk, 'text') and chunk.text:
|
296 |
+
data = {'id': f'chatcmpl-{int(time.time())}', 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': model_name, 'choices': [{'index': 0, 'delta': {'role': 'assistant', 'content': chunk.text}, 'finish_reason': None}]}
|
297 |
+
yield f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
|
298 |
+
|
299 |
+
final_data = {'id': f'chatcmpl-{int(time.time())}', 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': model_name, 'choices': [{'index': 0, 'delta': {}, 'finish_reason': 'stop'}]}
|
300 |
+
yield f'data: {json.dumps(final_data, ensure_ascii=False)}\n\n'
|
301 |
+
yield 'data: [DONE]\n\n'
|
302 |
+
|
303 |
+
logger.info(f"流式响应成功,使用密钥: {api_key[:10]}...")
|
304 |
+
return
|
305 |
+
except Exception as e:
|
306 |
+
last_error = e
|
307 |
+
error_str = str(e).lower()
|
308 |
+
if any(code in error_str for code in ['400', '401', '403', '429', '500', '502', '503', '504']):
|
309 |
+
logger.warning(f"流式响应第 {attempt + 1} 次尝试失败: {str(e)}")
|
310 |
+
if attempt < max_retries - 1:
|
311 |
+
await asyncio.sleep(1)
|
312 |
+
continue
|
313 |
+
else:
|
314 |
+
break
|
315 |
+
logger.error(f"流式响应所有重试失败: {traceback.format_exc()}")
|
316 |
+
error_message, finish_reason = handle_error(last_error)
|
317 |
+
error_data = {'id': f'chatcmpl-{int(time.time())}-error', 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': model_name, 'choices': [{'index': 0, 'delta': {'role': 'assistant', 'content': error_message}, 'finish_reason': finish_reason}]}
|
318 |
+
yield f'data: {json.dumps(error_data, ensure_ascii=False)}\n\n'
|
319 |
+
yield 'data: [DONE]\n\n'
|
320 |
+
|
321 |
+
|
322 |
+
@app.get("/v1/models")
|
323 |
+
async def list_models():
|
324 |
+
return {"object": "list", "data": SUPPORTED_MODELS}
|
325 |
+
|
326 |
+
@app.get("/v1/models/{model_id}")
|
327 |
+
async def get_model_info(model_id: str):
|
328 |
+
for model in SUPPORTED_MODELS:
|
329 |
+
if model["id"] == model_id:
|
330 |
+
return model
|
331 |
+
raise HTTPException(status_code=404, detail=f"模型 {model_id} 未找到")
|
332 |
+
|
333 |
+
@app.get("/v1/chat/completions/v1/models")
|
334 |
+
async def list_models_alternative():
|
335 |
+
return {"object": "list", "data": SUPPORTED_MODELS}
|
336 |
+
|
337 |
+
@app.get("/health")
|
338 |
+
async def health_check():
|
339 |
+
return {"status": "healthy", "timestamp": int(time.time()), "api": "gemini-official", "available_models": [model["id"] for model in SUPPORTED_MODELS], "version": "1.3.0"}
|
340 |
+
|
341 |
+
@app.get("/")
|
342 |
+
async def root():
|
343 |
+
return {"name": "Gemini Official API (ap3)", "version": "1.3.0", "description": "Google Gemini官方API接口服务", "endpoints": {"models": "/v1/models", "models_alt": "/v1/chat/completions/v1/models", "chat": "/v1/chat/completions", "health": "/health"}}
|
344 |
+
|
345 |
+
@app.exception_handler(404)
|
346 |
+
async def not_found_handler(request: Request, exc: HTTPException):
|
347 |
+
"""处理404错误"""
|
348 |
+
content = {
|
349 |
+
"error": "未找到",
|
350 |
+
"requested_path": str(request.url.path),
|
351 |
+
"message": "请求的路径不存在",
|
352 |
+
"available_endpoints": {
|
353 |
+
"models": "/v1/models",
|
354 |
+
"models_alt": "/v1/chat/completions/v1/models",
|
355 |
+
"chat": "/v1/chat/completions",
|
356 |
+
"health": "/health",
|
357 |
+
"info": "/"
|
358 |
+
}
|
359 |
+
}
|
360 |
+
return JSONResponse(status_code=404, content=content)
|
361 |
+
|
362 |
+
if __name__ == "__main__":
|
363 |
+
port = int(os.environ.get("PORT", 7862))
|
364 |
+
print(f"🚀 启动Gemini官方API服务器于端口 {port}")
|
365 |
+
print(f"📊 支持的模型: {[model['id'] for model in SUPPORTED_MODELS]}")
|
366 |
+
print(f"🔑 已配置 {len(API_KEYS)} 个API密钥")
|
367 |
+
print("🔄 支持自动重试和密钥轮换")
|
368 |
+
uvicorn.run("app:app", host="0.0.0.0", port=port, reload=True)
|
requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
fastapi
|
2 |
+
uvicorn
|
3 |
+
google-genai
|
4 |
+
loguru
|
5 |
+
httpx
|