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LLMs prompt augmentation with RAG by integrating external custom data from a variety of sources, allowing chat with such documents

License: MIT License

Python 100.00%
chat-application chatbot chatgpt custom-data llm llm-apps llm-framework llms llama llama-index rag retrieval-augmented-generation chatapp rag-embeddings llama2 llamacpp local-llama local-llm mixtral mixtral-8x7b

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llm-rag's Issues

question

hey,

you have no discussion are so here ;)

what is better in RAG than "pdfgear"
https://www.pdfgear.com/de/
its 300MB (offline) and better than all i tryed before ...

how you prevent in your software that the model is halucinating an tell somwhat that the model knows but its not based on the document, i allways had that impression in privategpt in gpt4all and khoj-ai !
PDFgear says "no i dont found it" or "you are shure you talk about that document" ...

btw, you have a GUI or its possible as an extention in oobabooga - text-generation-webui ?

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