privateGPT VS gpt4-pdf-chatbot-langchain

# install developer tools xcode-select --install # create python sandbox mkdir PrivateGTP cd privateGTP/ python3 -m venv . # actiavte local context source bin/activate # privateGTP uses poetry for python module management privateGTP> pip install poetry # sync privateGTP project privateGTP> git clone https://github.com/imartinez/privateGPT # enable MPS for model loading and processing privateGTP> CMAKE_ARGS="-DLLAMA_METAL=on" pip install --force-reinstall --no-cache-dir llama-cpp-python privateGTP> cd privateGPT # Import configure python dependencies privateGTP> poetry run python3 scripts/setup # launch web interface to confirm operational on default model privateGTP> python3 -m private_gpt # navigate safari browser to http://localhost:8001/ # To bulk import documentation needed to stop the web interface as vector database not in multi-user mode privateGTP> [control] + "C" # import some PDFs privateGTP> curl "https://docs.intersystems.com/irislatest/csp/docbook/pdfs.zip" -o /tmp/pdfs.zip privateGTP> unzip /tmp/pdfs.zip -d /tmp # took a few hours to process privateGTP> make ingest /tmp/pdfs/pdfs/ # launch web interface again for query documentation privateGTP> python3 -m private_gpt

I am playing around with this github project, which takes a user question as input and immediately runs a vector search on it to find relevant storied information before delivering an answer.

I am using this https://github.com/mayooear/gpt4-pdf-chatbot-langchain as a reference to ingest PDFs into pinecone and chat with a document, but my results aren’t good. Since it’s looking for related documents, there’s no good relation to the meta question: “What questions were asked in this interview?”

Anyone can already do this locally with their own API keys for free, with no technical knowledge by cloning a github repo (e.g. https://github.com/mayooear/gpt4-pdf-chatbot-langchain - this one can also chat with multiple pdfs which is much better). Even with gpt-4, I just don't find the responses useful usually. I find the model doesn't do great with scientific stuff aside from asking very basic things. Might have to wait for gpt-5.

https://github.com/mayooear/gpt4-pdf-chatbot-langchain this repo uses gpt-3.5/4 which uses OpenAI API. Is there any work donw with free/open-source LLMs

Follow this guide https://github.com/mayooear/gpt4-pdf-chatbot-langchain

I am using this one on windows 10. Took 2 evenings to set up: https://github.com/mayooear/gpt4-pdf-chatbot-langchain

Thanks for your take on the subject. I agree that starting from scratch would be too much. I think my post above might be misleading in regard to training. I wouldn't suggest to start from scratch but to provide additional data to a pretrained AI. But you can use GPT-4 (through API) in combination with pinecone to provide data. Here is a project, where someone implemented this to work with large PDF files. I don't think it would be too hard, to start from there and adapt the project to the requirements of OP. Obviously this would require paid for API keys. LLama could be also a good starting point, with a lot of resources available.

I'm currently developing a chatbot application that interacts with PDF documents using GPT API, Langchain, and a Pinecone vector database. The project is built on this repository: mayooear/gpt4-pdf-chatbot-langchain.