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https://github.com/snailyp/gemini-balance.git
synced 2026-09-08 01:06:37 +08:00
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yinpeng
@@ -40,40 +40,56 @@ API_KEYS = config.settings.API_KEYS
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# 创建一个循环迭代器
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# 创建一个循环迭代器
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key_cycle = cycle(API_KEYS)
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key_cycle = cycle(API_KEYS)
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key_lock = asyncio.Lock()
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# 创建两个独立的锁
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key_cycle_lock = asyncio.Lock()
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failure_count_lock = asyncio.Lock()
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# 添加key失败计数记录
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# 添加key失败计数记录
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key_failure_counts = {key: 0 for key in API_KEYS}
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key_failure_counts = {key: 0 for key in API_KEYS}
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MAX_FAILURES = 1 # 最大失败次数阈值
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MAX_FAILURES = 10 # 最大失败次数阈值
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MAX_RETRIES = 3 # 最大重试次数
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async def get_next_key():
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"""仅获取下一个key,不检查失败次数"""
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async with key_cycle_lock:
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return next(key_cycle)
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async def is_key_valid(key):
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"""检查key是否有效"""
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async with failure_count_lock:
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return key_failure_counts[key] < MAX_FAILURES
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async def reset_failure_counts():
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"""重置所有key的失败计数"""
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async with failure_count_lock:
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for key in key_failure_counts:
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key_failure_counts[key] = 0
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async def get_next_working_key():
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async def get_next_working_key():
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"""获取下一个可用的API key"""
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"""获取下一个可用的API key"""
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async with key_lock:
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initial_key = await get_next_key()
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current_key = next(key_cycle)
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current_key = initial_key
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initial_key = current_key
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while True:
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while key_failure_counts[current_key] >= MAX_FAILURES:
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if await is_key_valid(current_key):
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current_key = next(key_cycle)
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return current_key
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if current_key == initial_key: # 已经循环了一圈
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# 重置所有失败计数
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current_key = await get_next_key()
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for key in key_failure_counts:
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if current_key == initial_key: # 已经循环了一圈
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key_failure_counts[key] = 0
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await reset_failure_counts()
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break
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return current_key
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return current_key
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async def handle_api_failure(api_key):
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async def handle_api_failure(api_key):
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"""处理API调用失败"""
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"""处理API调用失败"""
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async with key_lock:
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async with failure_count_lock:
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key_failure_counts[api_key] += 1
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key_failure_counts[api_key] += 1
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if key_failure_counts[api_key] >= MAX_FAILURES:
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if key_failure_counts[api_key] >= MAX_FAILURES:
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logger.warning(
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logger.warning(f"API key {api_key} has failed {MAX_FAILURES} times, switching to next key")
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f"API key {api_key} has failed {MAX_FAILURES} times, switching to next key"
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)
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# 在锁外获取新的key
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return await get_next_working_key()
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return await get_next_working_key()
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return api_key
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class ChatRequest(BaseModel):
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class ChatRequest(BaseModel):
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@@ -206,9 +222,8 @@ def convert_gemini_response_to_openai(response, model, stream=False):
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@app.get("/hf/v1/models")
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@app.get("/hf/v1/models")
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async def list_models(authorization: str = Header(None)):
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async def list_models(authorization: str = Header(None)):
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await verify_authorization(authorization)
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await verify_authorization(authorization)
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async with key_lock:
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api_key = await get_next_working_key()
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api_key = next(key_cycle)
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logger.info(f"Using API key: {api_key}")
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logger.info(f"Using API key: {api_key}")
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try:
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try:
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response = get_gemini_models(api_key)
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response = get_gemini_models(api_key)
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logger.info("Successfully retrieved models list")
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logger.info("Successfully retrieved models list")
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@@ -223,95 +238,124 @@ async def list_models(authorization: str = Header(None)):
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async def chat_completion(request: ChatRequest, authorization: str = Header(None)):
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async def chat_completion(request: ChatRequest, authorization: str = Header(None)):
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await verify_authorization(authorization)
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await verify_authorization(authorization)
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api_key = await get_next_working_key()
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api_key = await get_next_working_key()
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logger.info(f"Using API key: {api_key}")
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logger.info(f"Chat completion request - Model: {request.model}")
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retries = 0
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while retries < MAX_RETRIES:
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try:
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logger.info(f"Attempt {retries + 1} with API key: {api_key}")
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if request.model in config.settings.MODEL_SEARCH:
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# Gemini API调用部分
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gemini_messages = convert_messages_to_gemini_format(request.messages)
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# 调用Gemini API
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payload = {
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"contents": gemini_messages,
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"generationConfig": {
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"temperature": request.temperature,
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},
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"tools": [{"googleSearch": {}}],
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}
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if request.stream:
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logger.info("Streaming response enabled")
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try:
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async def generate():
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logger.info(f"Chat completion request - Model: {request.model}")
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nonlocal api_key, retries
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if request.model in config.settings.MODEL_SEARCH:
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while retries < MAX_RETRIES:
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# 转换消息格式
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try:
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gemini_messages = convert_messages_to_gemini_format(request.messages)
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async with httpx.AsyncClient() as client:
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stream_url = f"https://generativelanguage.googleapis.com/v1beta/models/{request.model}:streamGenerateContent?alt=sse&key={api_key}"
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# 调用Gemini API
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async with client.stream("POST", stream_url, json=payload) as response:
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non_stream_url = f"https://generativelanguage.googleapis.com/v1beta/models/{request.model}:generateContent?key={api_key}"
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if response.status_code == 429:
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stream_url = f"https://generativelanguage.googleapis.com/v1beta/models/{request.model}:streamGenerateContent?alt=sse&key={api_key}"
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logger.warning(f"Rate limit reached for key: {api_key}")
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payload = {
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api_key = await handle_api_failure(api_key)
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"contents": gemini_messages,
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logger.info(f"Retrying with new API key: {api_key}")
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"generationConfig": {
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retries += 1
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"temperature": request.temperature,
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if retries >= MAX_RETRIES:
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},
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yield f"data: {json.dumps({'error': 'Max retries reached'})}\n\n"
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"tools": [{"googleSearch": {}}],
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break
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}
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continue
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if request.stream:
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if response.status_code != 200:
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logger.error(f"Error in streaming response: {response.status_code}")
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yield f"data: {json.dumps({'error': f'API error: {response.status_code}'})}\n\n"
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break
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async for line in response.aiter_lines():
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if line.startswith("data: "):
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try:
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chunk = json.loads(line[6:])
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openai_chunk = convert_gemini_response_to_openai(
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chunk, request.model, stream=True
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)
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if openai_chunk:
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yield f"data: {json.dumps(openai_chunk)}\n\n"
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except json.JSONDecodeError:
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continue
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yield "data: [DONE]\n\n"
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return
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except Exception as e:
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logger.error(f"Stream error: {str(e)}")
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api_key = await handle_api_failure(api_key)
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retries += 1
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if retries >= MAX_RETRIES:
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yield f"data: {json.dumps({'error': 'Max retries reached'})}\n\n"
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break
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continue
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return StreamingResponse(content=generate(), media_type="text/event-stream")
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else:
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# 非流式响应
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async with httpx.AsyncClient() as client:
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non_stream_url = f"https://generativelanguage.googleapis.com/v1beta/models/{request.model}:generateContent?key={api_key}"
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response = await client.post(non_stream_url, json=payload)
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gemini_response = response.json()
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logger.info("Chat completion successful")
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return convert_gemini_response_to_openai(gemini_response, request.model)
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# OpenAI API调用部分
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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response = client.chat.completions.create(
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model=request.model,
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messages=request.messages,
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temperature=request.temperature,
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stream=request.stream if hasattr(request, "stream") else False,
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)
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if hasattr(request, "stream") and request.stream:
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logger.info("Streaming response enabled")
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logger.info("Streaming response enabled")
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async def generate():
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async def generate():
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async with httpx.AsyncClient() as client:
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for chunk in response:
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async with client.stream(
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yield f"data: {chunk.model_dump_json()}\n\n"
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"POST", stream_url, json=payload
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) as response:
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async for line in response.aiter_lines():
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if line.startswith("data: "):
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try:
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chunk = json.loads(line[6:])
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openai_chunk = (
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convert_gemini_response_to_openai(
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chunk, request.model, stream=True
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)
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)
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if openai_chunk:
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yield f"data: {json.dumps(openai_chunk)}\n\n"
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except json.JSONDecodeError:
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continue
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yield "data: [DONE]\n\n"
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return StreamingResponse(
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content=generate(), media_type="text/event-stream"
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)
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else:
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# 非流式响应
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async with httpx.AsyncClient() as client:
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response = await client.post(non_stream_url, json=payload)
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gemini_response = response.json()
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openai_response = convert_gemini_response_to_openai(
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gemini_response, request.model
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)
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logger.info("Chat completion successful")
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logger.info("Chat completion successful")
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return openai_response
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return StreamingResponse(content=generate(), media_type="text/event-stream")
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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response = client.chat.completions.create(
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logger.info("Chat completion successful")
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model=request.model,
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return response
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messages=request.messages,
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temperature=request.temperature,
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stream=request.stream if hasattr(request, "stream") else False,
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)
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if hasattr(request, "stream") and request.stream:
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except Exception as e:
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logger.info("Streaming response enabled")
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logger.error(f"Error in chat completion: {str(e)}")
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api_key = await handle_api_failure(api_key)
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retries += 1
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if retries >= MAX_RETRIES:
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logger.error("Max retries reached, giving up")
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raise HTTPException(status_code=500, detail="Max retries reached with all available API keys")
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logger.info(f"Retrying with new API key: {api_key}")
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continue
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async def generate():
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raise HTTPException(status_code=500, detail="Unexpected error in chat completion")
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for chunk in response:
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yield f"data: {chunk.model_dump_json()}\n\n"
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return StreamingResponse(content=generate(), media_type="text/event-stream")
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logger.info("Chat completion successful")
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return response
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except Exception as e:
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logger.error(f"Error in chat completion: {str(e)}")
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api_key = await handle_api_failure(api_key) # 处理失败并可能切换key
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/v1/embeddings")
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@app.post("/v1/embeddings")
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@app.post("/hf/v1/embeddings")
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@app.post("/hf/v1/embeddings")
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async def embedding(request: EmbeddingRequest, authorization: str = Header(None)):
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async def embedding(request: EmbeddingRequest, authorization: str = Header(None)):
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await verify_authorization(authorization)
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await verify_authorization(authorization)
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async with key_lock:
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api_key = await get_next_working_key()
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api_key = next(key_cycle)
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logger.info(f"Using API key: {api_key}")
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logger.info(f"Using API key: {api_key}")
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try:
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try:
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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