gpt4-pdf-chatbot-langchain VS pdfGPT

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.

From "Artificial intelligence is ineffective and potentially harmful for fact checking" (2023) https://news.ycombinator.com/item?id=37226233 : pdfgpt, knowledge_gpt, elasticsearch

pdfGPT: https://github.com/bhaskatripathi/pdfGPT :

> PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities.

GH "pdfgpt" topic: https://github.com/topics/pdfgpt

knowledge_gpt: https://github.com/mmz-001/knowledge_gpt

From https://news.ycombinator.com/item?id=39112014 : paperai

neuml/paperai:

What about systems like pdfgpt and knowledge_gpt; that, in returning citations from the trained texts, might be useful for legal discovery with admissibility?

pdfgpt: https://github.com/bhaskatripathi/pdfGPT

PDFChatter (Universal Sentence Encoder + GPT-3.5): out of the box, this solution works quite well. However, the need for Q&A prompting (and 'black-box' nature of the solution) seems to disqualify it as an optimal solution.

I was recommended pdfGPT and it looks good. Before I start setting it up, is there anything I should know? Are there better solutions? And how secure would it or they be?

https://github.com/bhaskatripathi/pdfGPT/blob/main/app.py it's a 200 line python script, all you need to do is rewrite pdf_to_text function for whatever format your file is. gpt4 can do it.