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It uses a Retrieval-Augmented Generation (RAG) approach to provide accurate, context-aware answers by incorporating previous chat history of the current session.               \n\n[App in Hugging Face Space](https://huggingface.co/spaces/AkashVD26/pdfsense)\n\n## 🚀 Features\n- Upload and analyze PDF documents.\n- Ask questions about the uploaded PDF in natural language.\n- Retrieve answers using LangChain, FAISS indexing, and Hugging Face embeddings.\n- Maintain conversation context for coherent responses.    \n\n## 📚 How It Works\n- Upload PDF: Drag and drop your PDF file into the uploader.\n- Ask Questions: Type a question about the PDF's content.\n- Contextual Answers: PDFSense retrieves answers using FAISS and LLMs while maintaining chat history for context.\n\n## 🛠️ Technologies Used         \n- Streamlit: Interactive web application framework.\n- LangChain: Framework for creating LLM-based applications.\n- FAISS: Vector search for efficient retrieval.\n- Hugging Face: Pretrained embeddings for document processing.\n- Groq: LLM used for generating responses.\n- PyPDFLoader: Document loader for processing PDFs.             \n\n## 🧩 Prerequisites\nMake sure you have the following prerequisites:\n\n- [Python 3.8 and above](https://www.python.org)\n- [Hugging Face account](https://huggingface.co)\n- [Hugging Face Access Token](https://huggingface.co/settings/tokens)\n- [Groq API key](https://console.groq.com/keys)\n\n## 📦 Installation\nIf you want to use this locally on your system:\n\n```\ngit clone https://github.com/Akashvarma26/PDFSense.git\n```\n\n```\npip install -r requirements.txt\n```\n\n## ▶️ Usage\nRun the Streamlit app locally:\n```\nstreamlit run app.py\n```\n\n## 🙋‍♂️ Acknowledgments\n- [LangChain](https://www.langchain.com)\n- [Hugging Face](https://huggingface.co)\n- [FAISS](https://ai.meta.com/tools/faiss/)\n- [Groq](https://groq.com)\n- [streamlit](https://www.langchain.com)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakashvarma26%2Fpdfsense","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakashvarma26%2Fpdfsense","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakashvarma26%2Fpdfsense/lists"}