openai-cookbook
gpt4-pdf-chatbot-langchain
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| openai-cookbook | gpt4-pdf-chatbot-langchain | |
|---|---|---|
| 214 | 32 | |
| 55,805 | 14,548 | |
| 2.9% | - | |
| 9.5 | 3.9 | |
| 7 days ago | about 1 month ago | |
| MDX | TypeScript | |
| MIT License | - |
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openai-cookbook
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Ask HN: High quality Python scripts or small libraries to learn from
https://github.com/openai/openai-cookbook/blob/main/examples...
- Collection of notebooks showcasing some fun and effective ways of using Claude
- OpenAI Cookbook: Techniques to improve reliability
- OpenAI Cookbooks
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How to fine tune vit/convnet to focus on the layout of the input room image and ignore other things ?
It sounds like you are trying to tweak embeddings for similarity search. Rather than fine-tune the model's layers, you may want to try training a linear transformation the existing model's output embedding. Openai has a cookbook on how to do that. You will need some data though - but I think you can try it with ~20 pieces of synthetically generated data.
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Best base model 1B or 7B for full finetuning
tutorial from OpenAI https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb
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Resources to learn ChatGPT and the OpenAI API
OpenAI Cookbook
- OpenAI Cookbook
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Another Major Outage Across ChatGPT and API
OpenAI community repo with lots of examples: https://github.com/openai/openai-cookbook
gpt4-pdf-chatbot-langchain
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Back and forth conversations before a vector search?
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.
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How do I ask a meta question to a document? (Retrieval augmented generation, langchain, pinecone)
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?”
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Recently I launched dataspot Ai tool for students and academics, that turns any type of content such as research paper, website, or YouTube video into interactive chatbot. You can effortlessly retrieve information, obtain summaries. Google "dataspot ai" & let me know what you think :)
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.
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Chat with Documents using Open source LLMs
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
- Using ChatGPT to read multiple PDFs and create writing using them as sources
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How do you train GPT on your own documents?
Follow this guide https://github.com/mayooear/gpt4-pdf-chatbot-langchain
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Best GPT-based tool for summarizing PDFs/long docs
I am using this one on windows 10. Took 2 evenings to set up: https://github.com/mayooear/gpt4-pdf-chatbot-langchain
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Earthling Ed ChatGPT type AI
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.
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Seeking Cost-Effective Alternatives and Optimization Tips for a GPT-based PDF Chatbot
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.
- ChatGPT for your files - Discovered an AI research tool that allows you to ask questions across multiple files all at once and get instant answers with highlighted references
What are some alternatives?
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
askai - Command Line Interface for OpenAi ChatGPT
marqo - Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
chatpdf-gpt - ChatPDF-GPT is an innovative chat interface application powered by LangChain and OpenAI, allowing users to upload and chat with PDF documents, stored in Pinecone vector database and Supabase storage.
knowledge_gpt - Accurate answers and instant citations for your documents.
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data