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  pinned: false
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  short_description: Streamlit template space
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  ---
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- # πŸš€ Streamlit RAG Powered by Mistral 7B (4-bit)
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- ---
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  ## πŸ“Œ Overview
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  This project implements a Retrieval-Augmented Generation (RAG) system powered by the Mistral 7B model quantized to 4-bit, hosted on Runpod. The frontend uses Streamlit for an easy-to-use UI and it is hosted on Hugging Face Spaces. This system is designed for users who want to quickly extract relevant information from their uploaded documents (.txt, .pdf).
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  You can upload files here to create a temporary knowledge base that helps the AI give you relevant answers.
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  What this implementation does:
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  - Lets you upload multiple text files to build a searchable knowledge base for the LLM.
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  - Retrieves relevant information from your documents using RAG.
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- ---
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-
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  ## πŸ“ Usage
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  1. **Upload Files:** Drag and drop or select files to build the knowledge base.
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  2. **Generate Response:** Enter a custom prompt and click the 'Generate Response' button.
 
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  pinned: false
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  short_description: Streamlit template space
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  ---
 
 
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+ # πŸš€ Streamlit RAG Powered by Mistral 7B (4-bit)
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+
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  ## πŸ“Œ Overview
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  This project implements a Retrieval-Augmented Generation (RAG) system powered by the Mistral 7B model quantized to 4-bit, hosted on Runpod. The frontend uses Streamlit for an easy-to-use UI and it is hosted on Hugging Face Spaces. This system is designed for users who want to quickly extract relevant information from their uploaded documents (.txt, .pdf).
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  You can upload files here to create a temporary knowledge base that helps the AI give you relevant answers.
 
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  What this implementation does:
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  - Lets you upload multiple text files to build a searchable knowledge base for the LLM.
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  - Retrieves relevant information from your documents using RAG.
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+
 
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  ## πŸ“ Usage
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  1. **Upload Files:** Drag and drop or select files to build the knowledge base.
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  2. **Generate Response:** Enter a custom prompt and click the 'Generate Response' button.