### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

embeddings = OpenAIEmbeddings()
    vectorstore = FAISS.load_local(f"{directory_path}", embeddings)
    retriever_list = vectorstore.as_retriever(search_kwargs={"score_threshold": 0.65, "k": 6 })
    
    
    model = "gpt-3.5-turbo-0125"
    llm = ChatOpenAI(model=model, temperature=0)
    streaming_llm = ChatOpenAI(
        model=model,
        streaming=True,
        callbacks=[callback],
        temperature=0
    )

    question_generator = LLMChain(llm=llm, prompt=QA_PROMPT)
    doc_chain = load_qa_chain(streaming_llm, chain_type="stuff", prompt=QA_PROMPT)

    conversation_chain = ConversationalRetrievalChain(
        retriever=retriever_list,
        return_source_documents=True,
        # verbose=True,
        combine_docs_chain=doc_chain,
        question_generator=question_generator
    )

### Error Message and Stack Trace (if applicable)

_No response_

### Description

Hello all. 
I am experiencing an issue when using ConversationalRetrievalChain with multiple vectorstores and merging them. I notice that when querying, the content returned is not complete. Upon checking, I found that the content is divided into two parts, but the query only retrieves the first part. How can I resolve this issue? and ConversationalRetrievalChain does not correctly answer some questions in the document

### System Info

langchain==0.0.327
ConversationalRetrievalChain does not correctly answer some questions in the document
This is a GitHub Issue
repo:langchain
owner:hwchase17
Title : ConversationalRetrievalChain does not correctly answer some questions in the document
Issue date:

--- start body ---
### Checked other resources

- [X] I added a very descriptive title to this issue.
- [X] I searched the LangChain documentation with the integrated search.
- [X] I used the GitHub search to find a similar question and didn't find it.
- [X] I am sure that this is a bug in LangChain rather than my code.
- [X] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

embeddings = OpenAIEmbeddings()
    vectorstore = FAISS.load_local(f"{directory_path}", embeddings)
    retriever_list = vectorstore.as_retriever(search_kwargs={"score_threshold": 0.65, "k": 6 })
    
    
    model = "gpt-3.5-turbo-0125"
    llm = ChatOpenAI(model=model, temperature=0)
    streaming_llm = ChatOpenAI(
        model=model,
        streaming=True,
        callbacks=[callback],
        temperature=0
    )

    question_generator = LLMChain(llm=llm, prompt=QA_PROMPT)
    doc_chain = load_qa_chain(streaming_llm, chain_type="stuff", prompt=QA_PROMPT)

    conversation_chain = ConversationalRetrievalChain(
        retriever=retriever_list,
        return_source_documents=True,
        # verbose=True,
        combine_docs_chain=doc_chain,
        question_generator=question_generator
    )

### Error Message and Stack Trace (if applicable)

_No response_

### Description

Hello all. 
I am experiencing an issue when using ConversationalRetrievalChain with multiple vectorstores and merging them. I notice that when querying, the content returned is not complete. Upon checking, I found that the content is divided into two parts, but the query only retrieves the first part. How can I resolve this issue? and ConversationalRetrievalChain does not correctly answer some questions in the document

### System Info

langchain==0.0.327
--- end body ---
