Repository: imartinez/privateGPT
File: privateGPT.py (Python)

Code before:
        case "LlamaCpp":
            llm = LlamaCpp(model_path=model_path, n_ctx=model_n_ctx, callbacks=callbacks, verbose=False)
        case "GPT4All":
            llm = GPT4All(model=model_path, n_ctx=model_n_ctx, backend='gptj', callbacks=callbacks, verbose=False)
        case _default:
            print(f"Model {model_type} not supported!")
            exit;
    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not hide_source)
    # Interactive questions and answers
    while True:
        query = input("\nEnter a query: ")
        if query == "exit":
            break
        
        # Get the answer from the chain
        res = qa(query)
        answer, docs = res['result'], None if hide_source else res['source_documents']

        # Print the result
        print("\n\n> Question:")
        print(query)
        print("\n> Answer:")
        print(answer)

        # Print the relevant sources used for the answer, if source is True
        if not hide_source and docs:
            for document in docs:
                print("\n> " + document.metadata["source"] + ":")
                print(document.page_content)

def parse_arguments():
    parser = argparse.ArgumentParser()
    parser.add_argument("--hide-source", "-S", action='store_true',
                        help='Use this flag to disable printing of source documents used for answers.')

    parser.add_argument("--mute-stream", "-M",
                        action='store_true',
                        help='Use this flag to disable the streaming StdOut callback for LLMs.')

    return parser.parse_args()


if __name__ == "__main__":
    # Parse the command line arguments
    args = parse_arguments()
    main(hide_source=args.hide_source, mute_stream=args.mute_stream)


Review comment (refactor):
```suggestion
        if docs:
```
Nit:
This should be enough, we already check `hide_source` above, if `docs` is `None` we know there are no documents.

Alternatively, we can remove this `if` statement and just assign to `docs` an empty list instead of `None`.

Code after:
    # Prepare the LLM
    match model_type:
        case "LlamaCpp":
            llm = LlamaCpp(model_path=model_path, n_ctx=model_n_ctx, callbacks=callbacks, verbose=False)
        case "GPT4All":
            llm = GPT4All(model=model_path, n_ctx=model_n_ctx, backend='gptj', callbacks=callbacks, verbose=False)
        case _default:
            print(f"Model {model_type} not supported!")
            exit;
    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not args.hide_source)
    # Interactive questions and answers
    while True:
        query = input("\nEnter a query: ")
        if query == "exit":
            break

        # Get the answer from the chain
        res = qa(query)
        answer, docs = res['result'], [] if args.hide_source else res['source_documents']

        # Print the result
        print("\n\n> Question:")
        print(query)
        print("\n> Answer:")
        print(answer)

        # Print the relevant sources used for the answer
        for document in docs:
            print("\n> " + document.metadata["source"] + ":")
            print(document.page_content)

def parse_arguments():
    parser = argparse.ArgumentParser(description='privateGPT: Ask questions to your documents without an internet connection, '
                                                 'using the power of LLMs.')
    parser.add_argument("--hide-source", "-S", action='store_true',
                        help='Use this flag to disable printing of source documents used for answers.')

    parser.add_argument("--mute-stream", "-M",
                        action='store_true',
                        help='Use this flag to disable the streaming StdOut callback for LLMs.')

    return parser.parse_args()


if __name__ == "__main__":
    main()