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peterw / Chat-with-Github-Repo

This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake.

Home Page:https://explodinginsights.com/

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ValueError

ArshaanB opened this issue · comments

commented

This is the error I got after process it on this repo: https://github.com/ArshaanB/question-and-answer-contracts

Any tips?

ValueError: shapes (1536,) and (0,) not aligned: 1536 (dim 0) != 0 (dim 0)
Traceback:
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
    exec(code, module.__dict__)
File "/Users/arshaan/Desktop/development/ai/Chat-with-Github-Repo/src/utils/chat.py", line 93, in <module>
    run_chat_app(args.activeloop_dataset_path)
File "/Users/arshaan/Desktop/development/ai/Chat-with-Github-Repo/src/utils/chat.py", line 42, in run_chat_app
    output = search_db(db, user_input)
File "/Users/arshaan/Desktop/development/ai/Chat-with-Github-Repo/src/utils/chat.py", line 85, in search_db
    return qa.run(query)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/chains/base.py", line 213, in run
    return self(args[0])[self.output_keys[0]]
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/chains/base.py", line 116, in __call__
    raise e
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/chains/base.py", line 113, in __call__
    outputs = self._call(inputs)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/chains/retrieval_qa/base.py", line 109, in _call
    docs = self._get_docs(question)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/chains/retrieval_qa/base.py", line 166, in _get_docs
    return self.retriever.get_relevant_documents(question)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/vectorstores/base.py", line 279, in get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/vectorstores/deeplake.py", line 350, in similarity_search
    return self.search(query=query, k=k, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/vectorstores/deeplake.py", line 294, in search
    indices, scores = vector_search(
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/vectorstores/deeplake.py", line 47, in vector_search
    distances = distance_metric_map[distance_metric](query_embedding, data_vectors)
File "/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/langchain/vectorstores/deeplake.py", line 22, in <lambda>
    "cos": lambda a, b: np.dot(a, b.T)
File "<__array_function__ internals>", line 200, in dot