5 Commits (d481d887bccea9ccbb1fecbfd053fe2acf078199)

Author	SHA1	Message	Date
Quentin Pleplé	126d7f11dd	Fix notebook example (#3142) ... The following calls were throwing an exception: 575b717d10/docs/use_cases/evaluation/agent_vectordb_sota_pg.ipynb?short_path=4b3386c#L192 575b717d10/docs/use_cases/evaluation/agent_vectordb_sota_pg.ipynb?short_path=4b3386c#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!	1 year ago
Harrison Chase	c7b083ab56	bump version to 131 (#2391)	1 year ago
Shrined	10dab053b4	Add Enum for agent types (#2321) ... This pull request adds an enum class for the various types of agents used in the project, located in the `agent_types.py` file. Currently, the project is using hardcoded strings for the initialization of these agents, which can lead to errors and make the code harder to maintain. With the introduction of the new enums, the code will be more readable and less error-prone. The new enum members include: - ZERO_SHOT_REACT_DESCRIPTION - REACT_DOCSTORE - SELF_ASK_WITH_SEARCH - CONVERSATIONAL_REACT_DESCRIPTION - CHAT_ZERO_SHOT_REACT_DESCRIPTION - CHAT_CONVERSATIONAL_REACT_DESCRIPTION In this PR, I have also replaced the hardcoded strings with the appropriate enum members throughout the codebase, ensuring a smooth transition to the new approach.	1 year ago
Harrison Chase	47d37db2d2	WIP: Harrison/base retriever (#1765)	1 year ago
Harrison Chase	2d098e8869	Harrison/agent eval (#1620) ... Co-authored-by: jerwelborn <jeremy.welborn@gmail.com>	2 years ago