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feat(chatcmpl): 对函数调用进行异常捕获 (#749)
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@ -98,6 +98,7 @@ class OpenAIChatCompletions(api.LLMAPIRequester):
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# req_messages.append({"role": "user", "content": str(query.message_chain)})
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# 首次请求
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msg = await self._closure(req_messages, query.use_model, query.use_funcs)
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yield msg
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@ -106,23 +107,36 @@ class OpenAIChatCompletions(api.LLMAPIRequester):
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req_messages.append(msg.dict(exclude_none=True))
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# 持续请求,只要还有待处理的工具调用就继续处理调用
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while pending_tool_calls:
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for tool_call in pending_tool_calls:
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func = tool_call.function
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try:
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func = tool_call.function
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parameters = json.loads(func.arguments)
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parameters = json.loads(func.arguments)
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func_ret = await self.ap.tool_mgr.execute_func_call(
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query, func.name, parameters
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)
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func_ret = await self.ap.tool_mgr.execute_func_call(
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query, func.name, parameters
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)
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msg = llm_entities.Message(
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role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
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)
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msg = llm_entities.Message(
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role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
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)
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yield msg
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yield msg
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req_messages.append(msg.dict(exclude_none=True))
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req_messages.append(msg.dict(exclude_none=True))
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except Exception as e:
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# 出错,添加一个报错信息到 req_messages
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err_msg = llm_entities.Message(
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role="tool", content=f"err: {e}", tool_call_id=tool_call.id
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)
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yield err_msg
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req_messages.append(
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err_msg.dict(exclude_none=True)
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)
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# 处理完所有调用,继续请求
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msg = await self._closure(req_messages, query.use_model, query.use_funcs)
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