mirror of
https://github.com/snailyp/gemini-balance.git
synced 2026-09-04 23:19:17 +08:00
fix: 修复 OpenAI 和 Gemini API 调用重试逻辑及日志记录
This commit is contained in:
yinpeng
+125
-127
@@ -11,61 +11,73 @@ from app.schemas.openai_models import ChatRequest
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logger = get_chat_logger()
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def convert_messages_to_gemini_format(messages: list) -> list:
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"""Convert OpenAI message format to Gemini format"""
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converted_messages = []
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for msg in messages:
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role = "user" if msg["role"] == "user" else "model"
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parts = []
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# 处理文本内容
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if isinstance(msg["content"], str):
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parts.append({"text": msg["content"]})
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# 处理包含图片的消息
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elif isinstance(msg["content"], list):
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for content in msg["content"]:
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if isinstance(content, str):
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parts.append({"text": content})
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elif isinstance(content, dict) and content["type"] == "text":
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parts.append({"text": content["text"]})
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elif isinstance(content, dict) and content["type"] == "image_url":
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# 处理图片URL
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image_url = content["image_url"]["url"]
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if image_url.startswith("data:image"):
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# 处理base64图片
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parts.append(
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{
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"inline_data": {
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"mime_type": "image/jpeg",
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"data": image_url.split(",")[1],
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}
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}
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)
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else:
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# 处理普通URL图片
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parts.append(
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{
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"image_url": {
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"url": image_url,
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}
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}
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)
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converted_messages.append({"role": role, "parts": parts})
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return converted_messages
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def format_execution_result(result_data: dict) -> str:
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"""格式化执行结果输出"""
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outcome = result_data.get("outcome", "")
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output = result_data.get("output", "").strip()
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return f"""\n【执行结果】\n> outcome: {outcome}\n\n【输出结果】\n```plaintext\n{output}\n```\n"""
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def create_search_link(web):
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return f'\n- [{web["title"]}]({web["uri"]})'
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class ChatService:
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def __init__(self, base_url: str, key_manager=None):
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self.base_url = base_url
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self.key_manager = key_manager
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def convert_messages_to_gemini_format(self, messages: list) -> list:
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"""Convert OpenAI message format to Gemini format"""
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converted_messages = []
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for msg in messages:
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role = "user" if msg["role"] == "user" else "model"
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parts = []
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# 处理文本内容
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if isinstance(msg["content"], str):
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parts.append({"text": msg["content"]})
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# 处理包含图片的消息
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elif isinstance(msg["content"], list):
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for content in msg["content"]:
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if isinstance(content, str):
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parts.append({"text": content})
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elif isinstance(content, dict) and content["type"] == "text":
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parts.append({"text": content["text"]})
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elif isinstance(content, dict) and content["type"] == "image_url":
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# 处理图片URL
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image_url = content["image_url"]["url"]
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if image_url.startswith("data:image"):
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# 处理base64图片
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parts.append(
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{
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"inline_data": {
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"mime_type": "image/jpeg",
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"data": image_url.split(",")[1],
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}
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}
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)
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else:
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# 处理普通URL图片
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parts.append(
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{
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"image_url": {
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"url": image_url,
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}
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}
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)
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converted_messages.append({"role": role, "parts": parts})
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return converted_messages
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def convert_gemini_response_to_openai(
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self,
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response: Dict[str, Any],
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model: str,
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stream: bool = False,
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finish_reason: str = None,
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self,
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response: Dict[str, Any],
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model: str,
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stream: bool = False,
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finish_reason: str = None,
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) -> Optional[Dict[str, Any]]:
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"""Convert Gemini response to OpenAI format"""
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if stream:
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@@ -82,28 +94,17 @@ class ChatService:
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elif "codeExecution" in parts[0]:
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text = self.format_code_block(parts[0]["codeExecution"])
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elif "executableCodeResult" in parts[0]:
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text = self.format_execution_result(
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text = format_execution_result(
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parts[0]["executableCodeResult"]
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)
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elif "codeExecutionResult" in parts[0]:
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text = self.format_execution_result(
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text = format_execution_result(
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parts[0]["codeExecutionResult"]
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)
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else:
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text = ""
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if (
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settings.SHOW_SEARCH_LINK
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and model.endswith("-search")
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and "groundingMetadata" in candidate
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and "groundingChunks" in candidate["groundingMetadata"]
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):
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groundingChunks = candidate["groundingMetadata"]["groundingChunks"]
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text += "\n\n---\n\n"
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text += f"**【引用来源】**\n\n"
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for _, groundingChunk in enumerate(groundingChunks, 1):
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if "web" in groundingChunk:
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text += self.create_search_link(groundingChunk["web"])
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text = self.add_search_link_text(model, candidate, text)
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else:
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text = ""
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@@ -131,37 +132,26 @@ class ChatService:
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"created": int(time.time()),
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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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"message": {
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"role": "assistant",
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"content": response["candidates"][0]["content"]["parts"][0]["text"],
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},
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"finish_reason": finish_reason,
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}
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],
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"usage": {
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"prompt_tokens": 0,
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"completion_tokens": 0,
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"total_tokens": 0,
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},
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}
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": response["candidates"][0]["content"]["parts"][0]["text"],
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},
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"finish_reason": finish_reason,
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}
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],
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"usage": {
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"prompt_tokens": 0,
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"completion_tokens": 0,
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"total_tokens": 0,
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},
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}
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try:
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if response.get("candidates"):
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text = response["candidates"][0]["content"]["parts"][0]["text"]
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candidate = response["candidates"][0]
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if (
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settings.SHOW_SEARCH_LINK
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and model.endswith("-search")
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and "groundingMetadata" in candidate
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and "groundingChunks" in candidate["groundingMetadata"]
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):
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groundingChunks = candidate["groundingMetadata"]["groundingChunks"]
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text += "\n\n---\n\n"
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text += f"**【引用来源】**\n\n"
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for _, groundingChunk in enumerate(groundingChunks, 1):
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if "web" in groundingChunk:
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text += self.create_search_link(groundingChunk["web"])
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text = self.add_search_link_text(model, candidate, text)
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res["choices"][0]["message"]["content"] = text
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return res
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else:
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@@ -173,10 +163,27 @@ class ChatService:
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res["choices"][0]["message"]["content"] = f"Error converting Gemini response: {str(e)}"
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return res
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def add_search_link_text(self, model, candidate, text):
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if (
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settings.SHOW_SEARCH_LINK
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and model.endswith("-search")
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and "groundingMetadata" in candidate
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and "groundingChunks" in candidate["groundingMetadata"]
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):
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grounding_chunks = candidate["groundingMetadata"]["groundingChunks"]
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text += "\n\n---\n\n"
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text += f"**【引用来源】**\n\n"
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for _, grounding_chunk in enumerate(grounding_chunks, 1):
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if "web" in grounding_chunk:
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text += create_search_link(grounding_chunk["web"])
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return text
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else:
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return text
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async def create_chat_completion(
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self,
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request: ChatRequest,
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api_key: str,
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self,
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request: ChatRequest,
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api_key: str,
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) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
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"""Create chat completion using either Gemini or OpenAI API"""
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model = request.model
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@@ -184,7 +191,7 @@ class ChatService:
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if tools is None:
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tools = []
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if settings.TOOLS_CODE_EXECUTION_ENABLED and not (
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model.endswith("-search") or "-thinking" in model
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model.endswith("-search") or "-thinking" in model
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):
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tools.append({"code_execution": {}})
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if model.endswith("-search"):
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@@ -192,10 +199,10 @@ class ChatService:
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return await self._gemini_chat_completion(request, api_key, tools)
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async def _gemini_chat_completion(
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self,
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request: ChatRequest,
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api_key: str,
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tools: Optional[list] = None,
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self,
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request: ChatRequest,
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api_key: str,
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tools: Optional[list] = None,
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) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
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"""Handle Gemini API chat completion"""
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model = request.model
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@@ -210,7 +217,7 @@ class ChatService:
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gemini_model = model[:-7] # Remove -search suffix
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else:
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gemini_model = model
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gemini_messages = self.convert_messages_to_gemini_format(messages)
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gemini_messages = convert_messages_to_gemini_format(messages)
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if not stream:
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# 非流式模式下，移除代码执行工具
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@@ -247,26 +254,26 @@ class ChatService:
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if stream:
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async def generate():
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retries = 0
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MAX_RETRIES = 3
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max_retries = 3
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current_api_key = api_key
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while retries < MAX_RETRIES:
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while retries < max_retries:
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try:
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timeout = httpx.Timeout(
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60.0, read=60.0
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) # 连接超时60秒，读取超时60秒
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async with httpx.AsyncClient(timeout=timeout) as client:
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async with httpx.AsyncClient(timeout=timeout) as async_client:
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stream_url = f"https://generativelanguage.googleapis.com/v1beta/models/{gemini_model}:streamGenerateContent?alt=sse&key={current_api_key}"
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async with client.stream(
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"POST", stream_url, json=payload
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) as response:
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if response.status_code != 200:
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error_content = await response.read()
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async with async_client.stream(
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"POST", stream_url, json=payload
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) as async_response:
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if async_response.status_code != 200:
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error_content = await async_response.read()
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error_msg = error_content.decode("utf-8")
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logger.error(
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f"API error: {response.status_code}, {error_msg}"
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f"API error: {async_response.status_code}, {error_msg}"
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)
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if retries < MAX_RETRIES - 1:
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if retries < max_retries - 1:
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current_api_key = (
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await self.key_manager.handle_api_failure(
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current_api_key
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@@ -276,12 +283,12 @@ class ChatService:
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continue
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else:
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logger.error(
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f"Max retries reached. Final error: {response.status_code}, {error_msg}"
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f"Max retries reached. Final error: {async_response.status_code}, {error_msg}"
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)
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yield f"data: {json.dumps({'error': f'API error: {response.status_code}, {error_msg}'})}\n\n"
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yield f"data: {json.dumps({'error': f'API error: {async_response.status_code}, {error_msg}'})}\n\n"
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return
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async for line in response.aiter_lines():
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async for line in async_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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@@ -297,7 +304,7 @@ class ChatService:
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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 f"data: {json.dumps(self.convert_gemini_response_to_openai({}, model,stream=True, finish_reason='stop'))}\n\n"
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yield f"data: {json.dumps(self.convert_gemini_response_to_openai({}, model, stream=True, finish_reason='stop'))}\n\n"
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yield "data: [DONE]\n\n"
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return
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@@ -305,7 +312,7 @@ class ChatService:
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logger.warning(
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f"Read timeout occurred, attempting retry {retries + 1}"
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)
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if retries < MAX_RETRIES - 1:
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if retries < max_retries - 1:
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current_api_key = await self.key_manager.handle_api_failure(
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current_api_key
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)
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@@ -322,7 +329,7 @@ class ChatService:
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logger.exception(
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f"Stream error: {str(e)}, attempting retry {retries + 1}"
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)
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if retries < MAX_RETRIES - 1:
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if retries < max_retries - 1:
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current_api_key = await self.key_manager.handle_api_failure(
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current_api_key
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)
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@@ -362,14 +369,8 @@ class ChatService:
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return f"""\n【代码执行】\n```{language}\n{code}\n```\n"""
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def format_execution_result(self, result_data: dict) -> str:
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"""格式化执行结果输出"""
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outcome = result_data.get("outcome", "")
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output = result_data.get("output", "").strip()
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return f"""\n【执行结果】\n> outcome: {outcome}\n\n【输出结果】\n```plaintext\n{output}\n```\n"""
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async def generate_content(
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self, model_name: str, request: GeminiRequest, api_key: str
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self, model_name: str, request: GeminiRequest, api_key: str
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) -> dict:
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"""调用Gemini API生成内容"""
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url = f"{self.base_url}/models/{model_name}:generateContent?key={api_key}"
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@@ -392,7 +393,7 @@ class ChatService:
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raise
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async def stream_generate_content(
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self, model_name: str, request: GeminiRequest, api_key: str
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self, model_name: str, request: GeminiRequest, api_key: str
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) -> AsyncGenerator:
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"""调用Gemini API流式生成内容"""
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retries = 0
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@@ -406,7 +407,7 @@ class ChatService:
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async with httpx.AsyncClient(timeout=timeout) as client:
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async with client.stream(
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"POST", url, json=request.model_dump()
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"POST", url, json=request.model_dump()
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) as response:
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if response.status_code != 200:
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error_text = await response.text()
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@@ -451,6 +452,3 @@ class ChatService:
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retries += 1
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continue
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raise
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def create_search_link(self, web):
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return f'\n- [{web["title"]}]({web["uri"]})'
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@@ -1,5 +1,8 @@
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from typing import Union, List
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import openai
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from typing import Union, List, Dict, Any
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from openai.types import CreateEmbeddingResponse
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from app.core.logger import get_embeddings_logger
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logger = get_embeddings_logger()
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@@ -11,7 +14,7 @@ class EmbeddingService:
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async def create_embedding(
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self, input_text: Union[str, List[str]], model: str, api_key: str
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) -> Dict[str, Any]:
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) -> CreateEmbeddingResponse:
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"""Create embeddings using OpenAI API"""
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try:
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client = openai.OpenAI(api_key=api_key, base_url=self.base_url)
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