MistralAPIException：无法传输响应。状态：使用 MistralAI API 和 LangChain 创建聊天机器人期间为 400

Question

我正在尝试创建一个聊天机器人来使用 LangChain 和 MistralAI API 与网站进行对话。 但是我在使用 MistralAI API 时遇到问题，使用 OpenAI API 可以工作，但与 Mistral 不一样。

app.py：

import streamlit as st
from langchain_core.messages import AIMessage, HumanMessage
from langchain_community.document_loaders import WebBaseLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.vectorstores import Chroma
from langchain_mistralai import ChatMistralAI, MistralAIEmbeddings
from dotenv import load_dotenv
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.chains import create_history_aware_retriever, create_retrieval_chain
from langchain.chains.combine_documents import create_stuff_documents_chain


load_dotenv()


def get_vectorstore_from_url(url):
    # get the text in document form
    loader = WebBaseLoader(url)
    document = loader.load()

    # split the document into chunks
    text_splitter = RecursiveCharacterTextSplitter()
    document_chunks = text_splitter.split_documents(document)

    # create a vectorstore from the chunks
    vector_store = Chroma.from_documents(document_chunks, MistralAIEmbeddings())

    return vector_store


def get_context_retriever_chain(vector_store):
    llm = ChatMistralAI()
    retriever = vector_store.as_retriever()

    prompt = ChatPromptTemplate.from_messages(
        [
            MessagesPlaceholder(variable_name="chat_history"),
            ("user", "{input}"),
            (
                "user",
                "Given the above conversation, generate a search query to look up in order to get information relevant to the conversation",
            ),
        ]
    )

    retriever_chain = create_history_aware_retriever(llm, retriever, prompt)

    return retriever_chain


def get_conversational_rag_chain(retriever_chain):

    llm = ChatMistralAI()

    prompt = ChatPromptTemplate.from_messages(
        [
            (
                "system",
                "Answer the user's questions based on the below context:\n\n{context}",
            ),
            MessagesPlaceholder(variable_name="chat_history"),
            ("user", "{input}"),
        ]
    )

    stuff_documents_chain = create_stuff_documents_chain(llm, prompt)

    return create_retrieval_chain(retriever_chain, stuff_documents_chain)


def get_response(user_input):
    retriever_chain = get_context_retriever_chain(st.session_state.vector_store)
    conversation_rag_chain = get_conversational_rag_chain(retriever_chain)

    response = conversation_rag_chain.invoke(
        {"chat_history": st.session_state.chat_history, "input": user_input}
    )

    return response["answer"]


# app config
st.set_page_config(page_title="Chat with websites", page_icon="🤖")
st.title("Chat with websites")

# sidebar
with st.sidebar:
    st.header("Settings")
    website_url = st.text_input("Website URL")

if website_url is None or website_url == "":
    st.info("Please enter a website URL")

else:
    # session state
    if "chat_history" not in st.session_state:
        st.session_state.chat_history = [
            AIMessage(content="Hello, I am a bot. How can I help you?"),
        ]
    if "vector_store" not in st.session_state:
        st.session_state.vector_store = get_vectorstore_from_url(website_url)

    # user input
    user_query = st.chat_input("Type your message here...")
    if user_query is not None and user_query != "":
        response = get_response(user_query)
        st.session_state.chat_history.append(HumanMessage(content=user_query))
        st.session_state.chat_history.append(AIMessage(content=response))

    # conversation
    for message in st.session_state.chat_history:
        if isinstance(message, AIMessage):
            with st.chat_message("AI"):
                st.write(message.content)
        elif isinstance(message, HumanMessage):
            with st.chat_message("Human"):
                st.write(message.content)

特别是 Mistral 的嵌入正在工作，相反，LLM 不接受我给出的响应，事实上它给出了这个错误：

MistralAPIException: Cannot stream response. Status: 400
Traceback:

File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 535, in _run_script
    exec(code, module.__dict__)
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\app.py", line 106, in <module>
    response = get_response(user_query)
               ^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\app.py", line 75, in get_response
    response = conversation_rag_chain.invoke(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 4041, in invoke
    return self.bound.invoke(
           ^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 2053, in invoke
    input = step.invoke(
            ^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\passthrough.py", line 415, in invoke
    return self._call_with_config(self._invoke, input, config, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 1246, in _call_with_config
    context.run(
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\config.py", line 326, in call_func_with_variable_args
    return func(input, **kwargs)  # type: ignore[call-arg]
           ^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\passthrough.py", line 402, in _invoke
    **self.mapper.invoke(
      ^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 2692, in invoke
    output = {key: future.result() for key, future in zip(steps, futures)}
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 2692, in <dictcomp>
    output = {key: future.result() for key, future in zip(steps, futures)}
                   ^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\AppData\Local\Programs\Python\Python311\Lib\concurrent\futures\_base.py", line 456, in result
    return self.__get_result()
           ^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\AppData\Local\Programs\Python\Python311\Lib\concurrent\futures\_base.py", line 401, in __get_result
    raise self._exception
File "C:\Users\LENOVO\AppData\Local\Programs\Python\Python311\Lib\concurrent\futures\thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 4041, in invoke
    return self.bound.invoke(
           ^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\branch.py", line 211, in invoke
    output = self.default.invoke(
             ^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\runnables\base.py", line 2053, in invoke
    input = step.invoke(
            ^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\language_models\chat_models.py", line 166, in invoke
    self.generate_prompt(
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\language_models\chat_models.py", line 544, in generate_prompt
    return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\language_models\chat_models.py", line 408, in generate
    raise e
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\language_models\chat_models.py", line 398, in generate
    self._generate_with_cache(
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_core\language_models\chat_models.py", line 577, in _generate_with_cache
    return self._generate(
           ^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_mistralai\chat_models.py", line 263, in _generate
    response = self.completion_with_retry(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_mistralai\chat_models.py", line 207, in completion_with_retry
    return _completion_with_retry(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\tenacity\__init__.py", line 289, in wrapped_f
    return self(f, *args, **kw)
           ^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\tenacity\__init__.py", line 379, in __call__
    do = self.iter(retry_state=retry_state)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\tenacity\__init__.py", line 325, in iter
    raise retry_exc.reraise()
          ^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\tenacity\__init__.py", line 158, in reraise
    raise self.last_attempt.result()
          ^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\AppData\Local\Programs\Python\Python311\Lib\concurrent\futures\_base.py", line 449, in result
    return self.__get_result()
           ^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\AppData\Local\Programs\Python\Python311\Lib\concurrent\futures\_base.py", line 401, in __get_result
    raise self._exception
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\tenacity\__init__.py", line 382, in __call__
    result = fn(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\langchain_mistralai\chat_models.py", line 205, in _completion_with_retry
    return self.client.chat(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\mistralai\client.py", line 160, in chat
    for response in single_response:
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\mistralai\client.py", line 93, in _request
    yield self._check_response(response)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\mistralai\client_base.py", line 92, in _check_response
    self._check_response_status_codes(response)
File "C:\Users\LENOVO\Desktop\LangChain\chatbot_2\chatbot_with_mistralAI\Lib\site-packages\mistralai\client_base.py", line 79, in _check_response_status_codes
    raise MistralAPIException.from_response(

我尝试更改输入并检查文档，但问题仍然存在。 我应该如何修改代码来解决该错误？

Answer 1

您能否向我们展示使用 chat_history 和 user_input 完成后发送的提示？就像整个提示一样。