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- title: PDFQueryApplication
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- emoji: πŸŒ–
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- colorFrom: yellow
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- colorTo: green
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  sdk: streamlit
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  sdk_version: 1.42.0
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  app_file: app.py
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ title: πŸ“š RAG-based PDF Query Application
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+ emoji: πŸ“š
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+ colorFrom: purple
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+ colorTo: blue
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  sdk: streamlit
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  sdk_version: 1.42.0
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  app_file: app.py
 
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ # πŸ“š RAG-based PDF Query Application
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+ This application leverages Retrieval-Augmented Generation (RAG) to enable users to ask questions about a PDF document. The PDF is processed and split into chunks, which are then indexed and used to find the most relevant information when the user submits a query.
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+
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+ ## Features
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+ - Upload a PDF and ask questions based on its contents.
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+ - PDF is processed using **PyMuPDF** and text is split into chunks.
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+ - **FAISS** is used to create an index for quick retrieval of relevant text chunks.
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+ - The application uses the **Groq API** for generating answers based on the retrieved context.
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+
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+ ## How it works
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+ 1. Upload a PDF document.
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+ 2. The application extracts text from the PDF and splits it into smaller chunks.
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+ 3. A **FAISS index** is built using embeddings of these chunks.
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+ 4. When you submit a query, the system retrieves the most relevant chunks and sends them to the **Groq API** to generate an answer.
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+ ## Installation
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+ Clone the repository and install the required dependencies:
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+ ```bash
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+ git clone https://huggingface.co/spaces/your-username/your-app-name
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+ cd your-app-name
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+ pip install -r requirements.txt