https://github.com/arsath-eng/rag1-nvidia-genai
A powerful Retrieval Augmented Generation (RAG) application built with NVIDIA AI endpoints and Streamlit. This solution enables intelligent document analysis and question-answering using state-of-the-art language models, featuring multi-PDF processing, FAISS vector store integration, and advanced prompt engineering.
https://github.com/arsath-eng/rag1-nvidia-genai
document-analysis embeddings faiss langchain llama-models llm nvidia-ai-faundry pdf-processing question-answering rag streamlit vector-store
Last synced: 4 months ago
JSON representation
A powerful Retrieval Augmented Generation (RAG) application built with NVIDIA AI endpoints and Streamlit. This solution enables intelligent document analysis and question-answering using state-of-the-art language models, featuring multi-PDF processing, FAISS vector store integration, and advanced prompt engineering.
- Host: GitHub
- URL: https://github.com/arsath-eng/rag1-nvidia-genai
- Owner: arsath-eng
- License: mit
- Created: 2024-10-01T15:59:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-31T22:00:44.000Z (over 1 year ago)
- Last Synced: 2025-02-12T20:15:04.575Z (over 1 year ago)
- Topics: document-analysis, embeddings, faiss, langchain, llama-models, llm, nvidia-ai-faundry, pdf-processing, question-answering, rag, streamlit, vector-store
- Language: Python
- Homepage: https://huggingface.co/spaces/arsath-sm/Rag_with_documents
- Size: 153 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE