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question:BMIBaby
answer:BMIBaby was a British low-cost airline that operated from 2002 to 2012. It was a subsidiary of BMI (British Midland International) and operated flights primarily in Europe. BMIBaby was known for its no-frills service and competitive fares. However, the airline struggled financially and eventually ceased operations in September 2012 due to tough market conditions and increased competition.
question:Repeat this string "coffee and flower"
answer:coffee and flower
question:#!/usr/bin/env python """Example of a simple chatbot that just passes current conversation state back and forth between server and client. """ from typing import List, Union from fastapi import FastAPI from langchain_google_genai import ChatGoogleGenerativeAI from langchain_core.messages import AIMessage, HumanMessage, SystemMessage from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langserve import add_routes from langserve.pydantic_v1 import BaseModel, Field app = FastAPI( title="LangChain Server", version="1.0", description="Spin up a simple api server using Langchain's Runnable interfaces", ) # Declare a chain prompt = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful, professional assistant named Cob."), MessagesPlaceholder(variable_name="messages"), ] ) chain = prompt | ChatGoogleGenerativeAI(model="gemini-pro",google_api_key="AIzaSyDvzDtQvKAOpRPP9KNVo_naMSwPhFxnkZM",transport="rest",convert_system_message_to_human=True) class InputChat(BaseModel): """Input for the chat endpoint.""" messages: List[Union[HumanMessage, AIMessage, SystemMessage]] = Field( ..., description="The chat messages representing the current conversation.", ) add_routes( app, chain.with_types(input_type=InputChat), enable_feedback_endpoint=True, enable_public_trace_link_endpoint=True, playground_type="chat", ) if __name__ == "__main__": import uvicorn uvicorn.run(app, host="localhost", port=8000). 看一下这个代码有什么问题？
answer:这个代码示例构建了一个简单的聊天机器人服务器，使用了FastAPI框架以及LangChain和Google Generative AI的集成。然而，有一些注意事项和潜在的问题需要解决： 1. **API密钥的安全性**：代码中直接包含了Google API密钥。这是一个安全风险，因为如果代码被推送到公共仓库，恶意用户可能会获取并滥用这个密钥。建议使用环境变量或安全的秘密管理服务来保护密钥。 2. **错误处理**：示例代码没有显示任何错误处理。在实际部署中，建议添加异常捕获和处理机制来应对API调用失败、无效输入等情况。 3. **依赖性**：代码中引用了`langchain_google_genai`和`langchain_core`等库，但没有提及如何安装这些依赖。在实际部署前，需要确保这些库及其依赖项都已正确安装。 4. **导入的模块**：`from langserve import add_routes`和`from langserve.pydantic_v1 import BaseModel, Field`这两个导入声明没有详细的上下文或来源信息。这可能会导致潜在的导入错误，除非开发者确切知道如何获取`langserve`模块。 5. **性能和扩展性**：这个示例应用是一个简单的API，未明确涉及到性能和扩展性的设计。在大规模部署和应对高并发请求时，可能需要考虑优化数据库访问、增加缓存机制、使用异步处理请求等策略。 6. **数据模型**：虽然有一个`InputChat`的基础模型，但实际API的响应模型并未定义。创建明确的输入和输出数据模型可以提高API的易用性和文档的完整性。 7. **测试和文档**：代码中没有包含测试和文档。在开发API时，编写相应的单元测试和提供API文档（如使用FastAPI的Swagger UI）能够有效提高代码质量和用户体验。 8. **部署注意事项**：代码中的部署是使用`uvicorn`直接运行的，这对于开发和测试环境可能足够。但在生产环境下，可能需要使用更鲁棒的部署方案，例如在Docker容器中部署，并且可能需要使用Nginx等作为反向代理服务器来增强安全性和性能。 修正这些潜在问题和注意事项后，这份代码能够成为一个结构良好且更加安全、健壮的聊天机器人服务。
question:报了错 Traceback (most recent call last): File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 269, in __call__ await wrap(partial(self.listen_for_disconnect, receive)) File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 258, in wrap await func() File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 215, in listen_for_disconnect message = await receive() ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/uvicorn/protocols/http/h11_impl.py", line 538, in receive await self.message_event.wait() File "/usr/local/Cellar/[email protected]/3.11.7_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/asyncio/locks.py", line 213, in wait await fut asyncio.exceptions.CancelledError: Cancelled by cancel scope 1169ad810 During handling of the above exception, another exception occurred: + Exception Group Traceback (most recent call last): | File "/usr/local/lib/python3.11/site-packages/uvicorn/protocols/http/h11_impl.py", line 408, in run_asgi | result = await app( # type: ignore[func-returns-value] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/uvicorn/middleware/proxy_headers.py", line 84, in __call__ | return await self.app(scope, receive, send) | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/fastapi/applications.py", line 1054, in __call__ | await super().__call__(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/applications.py", line 123, in __call__ | await self.middleware_stack(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/middleware/errors.py", line 186, in __call__ | raise exc | File "/usr/local/lib/python3.11/site-packages/starlette/middleware/errors.py", line 164, in __call__ | await self.app(scope, receive, _send) | File "/usr/local/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 62, in __call__ | await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app | raise exc | File "/usr/local/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app | await app(scope, receive, sender) | File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 758, in __call__ | await self.middleware_stack(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 778, in app | await route.handle(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 299, in handle | await self.app(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 79, in app | await wrap_app_handling_exceptions(app, request)(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app | raise exc | File "/usr/local/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app | await app(scope, receive, sender) | File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 77, in app | await response(scope, receive, send) | File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 255, in __call__ | async with anyio.create_task_group() as task_group: | File "/usr/local/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 678, in __aexit__ | raise BaseExceptionGroup( | ExceptionGroup: unhandled errors in a TaskGroup (1 sub-exception) +-+---------------- 1 ---------------- | Traceback (most recent call last): | File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 258, in wrap | await func() | File "/usr/local/lib/python3.11/site-packages/sse_starlette/sse.py", line 245, in stream_response | async for data in self.body_iterator: | File "/usr/local/lib/python3.11/site-packages/langserve/api_handler.py", line 1077, in _stream_log | async for chunk in self._runnable.astream_log( | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 686, in astream_log | async for item in _astream_log_implementation( # type: ignore | File "/usr/local/lib/python3.11/site-packages/langchain_core/tracers/log_stream.py", line 612, in _astream_log_implementation | await task | File "/usr/local/lib/python3.11/site-packages/langchain_core/tracers/log_stream.py", line 566, in consume_astream | async for chunk in runnable.astream(input, config, **kwargs): | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 4144, in astream | async for item in self.bound.astream( | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 2449, in astream | async for chunk in self.atransform(input_aiter(), config, **kwargs): | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 2432, in atransform | async for chunk in self._atransform_stream_with_config( | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 1595, in _atransform_stream_with_config | chunk: Output = await asyncio.create_task( # type: ignore[call-arg] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/langchain_core/tracers/log_stream.py", line 237, in tap_output_aiter | async for chunk in output: | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 2402, in _atransform | async for output in final_pipeline: | File "/usr/local/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 1071, in atransform | async for output in self.astream(final, config, **kwargs): | File "/usr/local/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 308, in astream | raise e | File "/usr/local/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 292, in astream | async for chunk in self._astream( | File "/usr/local/lib/python3.11/site-packages/langchain_google_genai/chat_models.py", line 619, in _astream | async for chunk in await _achat_with_retry( | ^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/langchain_google_genai/chat_models.py", line 185, in _achat_with_retry | return await _achat_with_retry(**kwargs) | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/tenacity/_asyncio.py", line 88, in async_wrapped | return await fn(*args, **kwargs) | ^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/tenacity/_asyncio.py", line 47, in __call__ | do = self.iter(retry_state=retry_state) | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/tenacity/__init__.py", line 314, in iter | return fut.result() | ^^^^^^^^^^^^ | File "/usr/local/Cellar/[email protected]/3.11.7_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/_base.py", line 449, in result | return self.__get_result() | ^^^^^^^^^^^^^^^^^^^ | File "/usr/local/Cellar/[email protected]/3.11.7_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result | raise self._exception | File "/usr/local/lib/python3.11/site-packages/tenacity/_asyncio.py", line 50, in __call__ | result = await fn(*args, **kwargs) | ^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/langchain_google_genai/chat_models.py", line 183, in _achat_with_retry | raise e | File "/usr/local/lib/python3.11/site-packages/langchain_google_genai/chat_models.py", line 176, in _achat_with_retry | return await generation_method(**kwargs) | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/google/generativeai/generative_models.py", line 537, in send_message_async | response = await self.model.generate_content_async( | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/google/generativeai/generative_models.py", line 263, in generate_content_async | iterator = await self._async_client.stream_generate_content( | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/google/api_core/retry/retry_unary_async.py", line 230, in retry_wrapped_func | return await retry_target( | ^^^^^^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/google/api_core/retry/retry_unary_async.py", line 160, in retry_target | _retry_error_helper( | File "/usr/local/lib/python3.11/site-packages/google/api_core/retry/retry_base.py", line 212, in _retry_error_helper | raise final_exc from source_exc | File "/usr/local/lib/python3.11/site-packages/google/api_core/retry/retry_unary_async.py", line 155, in retry_target | return await target() | ^^^^^^^^^^^^^^ | File "/usr/local/lib/python3.11/site-packages/google/api_core/grpc_helpers_async.py", line 187, in error_remapped_callable | raise TypeError("Unexpected type of call %s" % type(call)) | TypeError: Unexpected type of call <class 'google.api_core.rest_streaming.ResponseIterator'>
answer:从这个报错信息来看，问题似乎出现在与Google Generative AI的通信中，特别是在处理异步请求时。错误的核心信息是： ```plaintext TypeError: Unexpected type of call <class 'google.api_core.rest_streaming.ResponseIterator'> ``` 这表明`google.api_core.grpc_helpers_async.error_remapped_callable`函数收到了一个它不期望的调用类型，即`google.api_core.rest_streaming.ResponseIterator`。这可能是由于以下某个或多个原因导致的： 1. **不兼容的API调用**：你可能正在使用的Google Generative AI库（特别是`google.api_core`和相关组件）版本与你的代码不完全兼容。Google API的某些版本可能期望特定的调用类型，如果提供了错误的类型，就会触发此类型的错误。 2. **环境和依赖问题**：确保你的环境中安装的所有库都是最新的，或者至少是与你的代码兼容的版本。依赖项之间的不兼容可能会导致不可预知的问题。 3. **代码实现问题**：可能是在与Google Generative AI库进行异步通信的过程中，代码实现方式不正确或者用法不当。 # 解决步骤 1. **检查库版本**：确保你的`google-cloud`, `google-api-core`和任何相关Google API库的版本都是最新的，或者至少是与当前API兼容的。查阅官方文档以获取有关兼容版本的信息。 2. **更新和测试依赖**：更新所有相关依赖到最新版本，并彻底测试你的应用。有时候，依赖库之间的微妙差异可能导致问题。 ```bash pip install --upgrade google-cloud google-api-core ``` 3. **代码审查**：仔细检查与`langchain_google_genai`和`google.api_core`相关的代码部分，确保按照官方文档和最佳实践调用API。特别是关注你如何构建和执行异步API调用。 4. **寻求帮助**：如果问题仍然存在，寻求来自Google API和/或langchain库的维护者的帮助可能会很有用。他们可能能提供更具体的指导，或者有可能是一个已知的库问题，正在等待修复。 5. **回退到同步调用**：如果可能并且适用，考虑将异步调用更改为同步调用，看看是否可以绕过问题。这可能不是最理想的解决方案，但可能是一个临时的解决方法，直到找到根本原因。