Langchain：根据输入动态路由逻辑

Question

我正在尝试动态绑定两个链。当问题是关于“langchain”时它会起作用，但否则会失败并出现以下错误。

RAG 链单独工作正常。

classification_chain = (
    PromptTemplate.from_template(
        """Given the user question below, classify it as either being about 'Langchain' or 'something else'\
        Do not respond with more than one word.

        <question>
        {question}
        </question>

Classification:"""
    )
    | get_llm()
    | StrOutputParser()
)



langchain_chain = (
    PromptTemplate.from_template(
        """You are an expert in langchain. Always answer with Daddy says.\
            <question>
            {question}
            </question>
            Answer:"""
    )
    | get_llm()
    | StrOutputParser()
)


retrieval_chain = '' 

def route(info):
    if "langchain" in info["topic"].lower():
        return langchain_chain
    else:
        print('-'*100)
        print(retrieval_chain)
        return retrieval_chain


def get_RAG_response(collection_name: str, question: str):
    db = get_vector_db(collection_name)
    retriever = db.as_retriever()
    model = get_llm()
    template = """Answer the following question based only on the provided context:
    {context}
    
    Question: {question}
    """
    prompt = ChatPromptTemplate.from_template(template)
    global retrieval_chain
    retrieval_chain = (
        {"context": retriever, "question": RunnablePassthrough()}
        | prompt
        | model
        | StrOutputParser()
    )
    # response = retreival_chain.invoke(question)

    full_chain = {"topic": classification_chain, "question": lambda x: x["question"]} | RunnableLambda(
    route
)
    response = full
        | StrOutputParser()
    )
    # response = retreival_chain.invoke(question)

    full_chain = {"topic": classification_chain, "question": lambda x: x["question"]} | RunnableLambda(
    route
)
    response = full_chain.invoke({"question": question})
    print('*'*100)
    print('response:', response)
    return response

错误：

INFO:     127.0.0.1:47854 - "POST /chat/chats HTTP/1.1" 500 Internal Server Error
ERROR:    Exception in ASGI application
Traceback (most recent call last):
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/uvicorn/protocols/http/httptools_impl.py", line 426, in run_asgi
    result = await app(  # type: ignore[func-returns-value]
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/uvicorn/middleware/proxy_headers.py", line 84, in __call__
    return await self.app(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/fastapi/applications.py", line 1054, in __call__
    await super().__call__(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/applications.py", line 116, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/middleware/errors.py", line 186, in __call__
    raise exc
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/middleware/errors.py", line 164, in __call__
    await self.app(scope, receive, _send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/middleware/cors.py", line 91, in __call__
    await self.simple_response(scope, receive, send, request_headers=headers)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/middleware/cors.py", line 146, in simple_response
    await self.app(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/middleware/exceptions.py", line 62, in __call__
    await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/_exception_handler.py", line 55, in wrapped_app
    raise exc
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/_exception_handler.py", line 44, in wrapped_app
    await app(scope, receive, sender)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/routing.py", line 746, in __call__
    await route.handle(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/routing.py", line 288, in handle
    await self.app(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/routing.py", line 75, in app
    await wrap_app_handling_exceptions(app, request)(scope, receive, send)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/_exception_handler.py", line 55, in wrapped_app
    raise exc
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/_exception_handler.py", line 44, in wrapped_app
    await app(scope, receive, sender)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/routing.py", line 70, in app
    response = await func(request)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/fastapi/routing.py", line 299, in app
    raise e
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/fastapi/routing.py", line 294, in app
    raw_response = await run_endpoint_function(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/fastapi/routing.py", line 193, in run_endpoint_function
    return await run_in_threadpool(dependant.call, **values)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/starlette/concurrency.py", line 35, in run_in_threadpool
    return await anyio.to_thread.run_sync(func, *args)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/anyio/to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "/home/garg10may/coding/pipa/backend/app/api/chat/chat_router.py", line 107, in create_chat_route
    return create_chat_service(db, chatCreate)
  File "/home/garg10may/coding/pipa/backend/app/api/chat/chat_service.py", line 146, in create_chat_service
    bot_message = get_RAG_response(file_group.group_name, chatCreate.message)
  File "/home/garg10may/coding/pipa/backend/app/api/chat/utility.py", line 288, in get_RAG_response
    response = full_chain.invoke({"question": question})
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 2446, in invoke
    input = step.invoke(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3908, in invoke
    return self._call_with_config(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 1625, in _call_with_config
    context.run(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/config.py", line 347, in call_func_with_variable_args
    return func(input, **kwargs)  # type: ignore[call-arg]
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3792, in _invoke
    output = output.invoke(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 2446, in invoke
    input = step.invoke(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3091, in invoke
    output = {key: future.result() for key, future in zip(steps, futures)}
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3091, in <dictcomp>
    output = {key: future.result() for key, future in zip(steps, futures)}
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 458, in result
    return self.__get_result()
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
    raise self._exception
  File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 141, in invoke
    return self.get_relevant_documents(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 245, in get_relevant_documents
    raise e
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 238, in get_relevant_documents
    result = self._get_relevant_documents(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/vectorstores.py", line 696, in _get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/vectorstores/pgvector.py", line 543, in similarity_search
    embedding = self.embedding_function.embed_query(text=query)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 697, in embed_query
    return self.embed_documents([text])[0]
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 668, in embed_documents
    return self._get_len_safe_embeddings(texts, engine=engine)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 471, in _get_len_safe_embeddings
    token = encoding.encode(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/tiktoken/core.py", line 116, in encode
    if match := _special_token_regex(disallowed_special).search(text):
TypeError: expected string or buffer
File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3091, in invoke
    output = {key: future.result() for key, future in zip(steps, futures)}
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/runnables/base.py", line 3091, in <dictcomp>
    output = {key: future.result() for key, future in zip(steps, futures)}
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 458, in result
    return self.__get_result()
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
    raise self._exception
  File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 141, in invoke
    return self.get_relevant_documents(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 245, in get_relevant_documents
    raise e
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/retrievers.py", line 238, in get_relevant_documents
    result = self._get_relevant_documents(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_core/vectorstores.py", line 696, in _get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/vectorstores/pgvector.py", line 543, in similarity_search
    embedding = self.embedding_function.embed_query(text=query)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 697, in embed_query
    return self.embed_documents([text])[0]
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 668, in embed_documents
    return self._get_len_safe_embeddings(texts, engine=engine)
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/langchain_community/embeddings/openai.py", line 471, in _get_len_safe_embeddings
    token = encoding.encode(
  File "/home/garg10may/coding/pipa/backend/venv/lib/python3.10/site-packages/tiktoken/core.py", line 116, in encode
    if match := _special_token_regex(disallowed_special).search(text):
TypeError: expected string or buffer

Answer 1

因为

retrieval_chain

和

langchain_chain

都期望不同的输入格式，并且

route

使用相同的

dic

输入调用。我使用

retrieval_chain

界面将输入格式化为

runnableLambda

。

  retrieval_chain = (
        RunnableLambda(lambda x: x['question']) | 
        {"context": retriever, "question": RunnablePassthrough()}
        | prompt
        | model
        | StrOutputParser()
    )