9/ DeepSeek-Prover – introduces an approach to generate Lean 4 proof data from high-school and undergraduate-level mathematical competition problems; it uses the synthetic data, comprising of 8 million formal statements and proofs, to fine-tune a DeepSeekMath 7B model…
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RAG Application Cost Estimation for PDF Question Answering
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In a Retrieval-Augmented Generation (RAG) application, the process involves reading the PDF to extract relevant context and then generating answers based on that context. Here's an estimated cost of asking 5 questions from a single pdf. 1. Reading the PDF:
– Let's assume the -
Local RAG App with PDF Support Using Llama-3
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You can build a local RAG app that works with PDF and runs on Llama-3 deployed locally.
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Generic Research Assistant for Academic Papers Interaction
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If you want to generally chat with research papers or want to build a generic research assistant. You can check this one out.
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Awesome LLM Apps with RAG GitHub Repository
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Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support
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Streamlit Application Demo for ArXiv Chat Integration
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Working Application demo using Streamlit Paste the above code in vscode or pycharm and run the following command: 'streamlit run chat_arxiv.py'
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Full RAG Application Code Chat Research Papers
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Full RAG Application code to chat with research papers
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Chat Interface for Research Papers Query System
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5. Chat with Research papers • Create a text input for the user to enter their query using 'st.text_input()'
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Building AI Assistant with OpenAI API and ArxivToolkit
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4. Create and Initialize the AI assistant • Create a text input to enter their OpenAI API key using 'st.text_input()'
• If the OpenAI API key is provided, create an instance of Assistant with gpt-40 as LLM and ArxivToolkit as the tool.