langchain: Pydantic error: extra fields not permitted for chain_type_kwargs

I think this is so bad library, no one care about to update the documents.

What I have found is that I need to run pip install -U langchain everyday. And then make sure my code reflects the changes in the Langchain classes. These guys are moving so fast that the source code changes regularly. What worked a week ago might not work today. Its an exciting ride.

🤖

Based on the error message you provided, it seems like the VectorDBQA class is not expecting a chain_type_kwargs argument. The chain_type_kwargs argument is not defined in the VectorDBQA class, and Pydantic is raising an error because it does not allow extra fields that are not explicitly defined in the model.

The VectorDBQA class in the LangChain codebase is a subclass of BaseQAWithSourcesChain. It is used for question-answering with sources over a vector database. The class has the following attributes: vectorstore, k, reduce_k_below_max_tokens, max_tokens_limit, and search_kwargs. It does not have an explicit __init__ method, so it is instantiated with the arguments that correspond to these attributes.

In your code, you are trying to pass chain_type_kwargs as an argument to VectorDBQA.from_chain_type(), but this method does not expect such an argument. Instead, you should pass the prompt directly to the llm (language model) instance. Here’s how you can modify your code:

from langchain.prompts import PromptTemplate
from langchain import OpenAI, VectorDBQA

prompt_template = """Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.

{context}

Question: {question}
Answer in Italian:"""

PROMPT = PromptTemplate(
    template=prompt_template, input_variables=["context", "question"]
)

# Instantiate the language model with the prompt
llm = OpenAI(prompt=PROMPT)

qa = VectorDBQA.from_chain_type(llm=llm, chain_type="stuff", vectorstore=docsearch)

In this modified code, the prompt is passed directly to the OpenAI instance when it is instantiated. Then, this llm instance is passed to VectorDBQA.from_chain_type().

I hope this helps! If you have any other questions or need further clarification, feel free to ask.

Sources

• Missing “Prompt” in Together ai
• docs/extras/modules/chains/how_to/custom_chain.ipynb
• libs/langchain/langchain/chains/qa_with_sources/vector_db.py

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Hi, @keviddles! I’m Dosu, and I’m here to help the LangChain team manage their backlog. I wanted to let you know that we are marking this issue as stale.

Based on the information provided, it seems that users are encountering Pydantic validation errors related to extra fields not being permitted for certain classes in the langchain library, such as VectorDBQA and HuggingFaceInstructEmbeddings. Several users have reported similar errors and have attempted to update and reinstall the library, but the issue persists. Some users have suggested running pip install -U langchain and pip install langchain as a potential solution. However, there hasn’t been an official resolution or response from the repository maintainers.

Could you please confirm if this issue is still relevant to the latest version of the LangChain repository? If it is, kindly let the LangChain team know by commenting on this issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days.

Thank you for your understanding and cooperation. Let me know if you have any further questions or concerns!

still getting the same error with RetrievalQA setting the chain_type as anything different than “stuff”

I think this is so bad library, no one care about to update the documents.

its open source, so you can actually contribute and write better documentation. Its a library with over 55K stars for a reason. 😃

have the same issue but with retrievalQA.from_chain_type(llm=llm,chain_type=“map_reduce”…etc) validation error for map-reducedocumentschain extra fields not permitted(type=value_error.extra)

Worked for me. pip install -U langchain pip install langchain

It works for me that I used the most violent method possible. comment the error code line C:\Users\xxx.conda\envs\chatglm\Lib\site-packages\pydantic\v1\main.py line 341 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data) # if validation_error: # raise validation_error

@baskaryan Could you please help @kennethwork101 with this issue? They are encountering Pydantic validation errors related to extra fields not being permitted for certain classes in the langchain library, even after updating to version 0.0.340. They have provided additional details in their comment. Thank you!

Same issue with ConversationRetrievalChain.from_llm(llm = …, chain_type=“map_reduce”, question_promt=…, combine_prompt=…)