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- ### πŸš€ **Features**
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- - **PDF & PPT Extraction**: Upload PDF and PowerPoint files to extract text! πŸ“„βž‘οΈπŸ“
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- - **Vector Store**: Automatically stores extracted text in a **Cassandra** vector store. πŸ”πŸ“š
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- - **Ask Anything**: Ask questions about the document, and get answers powered by **OpenAI**! πŸ€–β“
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- ### πŸ› οΈ **Tech Stack**
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- - **Streamlit**: Frontend framework to interact with the app.
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- - **LangChain**: For seamless document processing and querying.
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- - **OpenAI**: For LLM integration to provide intelligent responses.
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- - **Astra DB**: Database for storing and managing vectorized text data.
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- - **Python Libraries**: PyPDF2, python-pptx, cassio, and more.
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- ### 🌍 **Deployment**
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- This project is designed to be deployed on **Hugging Face Spaces**. Just upload your code, and it will run in the cloud! 🌩️
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- Make sure to configure the **Secrets** in Hugging Face Spaces for storing your sensitive API keys securely! πŸ”’
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- ### πŸ’‘ **How It Works**
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- - Upload a **PDF** or **PPT** file using the file uploader. πŸ“€
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- - The app will extract text from the file using **PyPDF2** (for PDFs) or **python-pptx** (for PPTs). πŸ“„βž‘οΈπŸ“
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- - The extracted text is split into manageable chunks using **LangChain's CharacterTextSplitter**. βœ‚οΈ
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- - The chunks are then added to **Cassandra** as vectorized data using **OpenAI embeddings**. πŸ”„
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- - Ask any query about the content of your document, and the app will respond using the power of **OpenAI**! πŸ€–πŸ’¬
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- ### 🎯 **Why Use This?**
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- - **Make documents interactive**: Easily explore the content of your documents by asking questions.
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- - **Quick retrieval**: With the text stored in a vector store, you can query the content efficiently.
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- - **Secure API keys**: API keys are securely managed using environment variables and **Hugging Face Spaces Secrets**. πŸ”‘πŸ’Ό
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- ### ✨ **Enjoy the App!** ✨
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- Now, go ahead and chat with your documents! πŸ˜„
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- This version now only focuses on the app’s features and deployment, making it more suited for hosting and sharing on Hugging Face Spaces!
 
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