mirror of
https://github.com/hwchase17/langchain
synced 2024-10-27 21:46:30 +00:00
126d7f11dd
The following calls were throwing an exception:575b717d10/docs/use_cases/evaluation/agent_vectordb_sota_pg.ipynb (L192)575b717d10/docs/use_cases/evaluation/agent_vectordb_sota_pg.ipynb (L239)Exception: ``` --------------------------------------------------------------------------- ValidationError Traceback (most recent call last) Cell In[14], line 1 ----> 1 chain_sota = RetrievalQA.from_chain_type(llm=OpenAI(temperature=0), chain_type="stuff", retriever=vectorstore_sota, input_key="question") File ~/github/langchain/venv/lib/python3.9/site-packages/langchain/chains/retrieval_qa/base.py:89, in BaseRetrievalQA.from_chain_type(cls, llm, chain_type, chain_type_kwargs, **kwargs) 85 _chain_type_kwargs = chain_type_kwargs or {} 86 combine_documents_chain = load_qa_chain( 87 llm, chain_type=chain_type, **_chain_type_kwargs 88 ) ---> 89 return cls(combine_documents_chain=combine_documents_chain, **kwargs) File ~/github/langchain/venv/lib/python3.9/site-packages/pydantic/main.py:341, in pydantic.main.BaseModel.__init__() ValidationError: 1 validation error for RetrievalQA retriever instance of BaseRetriever expected (type=type_error.arbitrary_type; expected_arbitrary_type=BaseRetriever) ``` The vectorstores had to be converted to retrievers: `vectorstore_sota.as_retriever()` and `vectorstore_pg.as_retriever()`. The PR also: - adds the file `paul_graham_essay.txt` referenced by this notebook - adds to gitignore *.pkl and *.bin files that are generated by this notebook Interestingly enough, the performance of the prediction greatly increased (new version of langchain or ne version of OpenAI models since the last run of the notebook): from 19/33 correct to 28/33 correct!
147 lines
1.9 KiB
Plaintext
147 lines
1.9 KiB
Plaintext
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