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--- |
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title: Pdfsense |
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emoji: 📜 |
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colorFrom: red |
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colorTo: red |
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sdk: streamlit |
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sdk_version: 1.40.2 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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short_description: PDF Answering Assistant |
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--- |
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Check out the configuration reference at [Hugging Face Spaces Config](https://huggingface.co/docs/hub/spaces-config-reference). |
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# 📜 PDFSense : PDF Question Answering Assistant with Chat History |
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PDFSense is an LLM-powered Streamlit application that enables users to upload PDFs and ask questions based on the document's content. It uses a Retrieval-Augmented Generation (RAG) approach to provide accurate, context-aware answers by incorporating previous chat history of the current session. |
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[App in Hugging Face Space](https://huggingface.co/spaces/AkashVD26/pdfsense) |
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## 🚀 Features |
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- Upload and analyze PDF documents. |
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- Ask questions about the uploaded PDF in natural language. |
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- Retrieve answers using LangChain, FAISS indexing, and Hugging Face embeddings. |
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- Maintain conversation context for coherent responses. |
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## 📚 How It Works |
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- Upload PDF: Drag and drop your PDF file into the uploader. |
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- Ask Questions: Type a question about the PDF's content. |
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- Contextual Answers: PDFSense retrieves answers using FAISS and LLMs while maintaining chat history for context. |
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## 🛠️ Technologies Used |
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- Streamlit: Interactive web application framework. |
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- LangChain: Framework for creating LLM-based applications. |
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- FAISS: Vector search for efficient retrieval. |
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- Hugging Face: Pretrained embeddings for document processing. |
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- Groq: LLM used for generating responses. |
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- PyPDFLoader: Document loader for processing PDFs. |
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## 🧩 Prerequisites |
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Make sure you have the following prerequisites: |
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- [Python 3.8 and above](https://www.python.org) |
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- [Hugging Face account](https://huggingface.co) |
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- [Hugging Face Access Token](https://huggingface.co/settings/tokens) |
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- [Groq API key](https://console.groq.com/keys) |
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## 📦 Installation |
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If you want to use this locally on your system: |
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``` |
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git clone https://github.com/Akashvarma26/PDFSense.git |
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``` |
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``` |
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pip install -r requirements.txt |
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``` |
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## ▶️ Usage |
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Run the Streamlit app locally: |
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``` |
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streamlit run app.py |
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``` |
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## 🙋♂️ Acknowledgments |
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- [LangChain](https://www.langchain.com) |
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- [Hugging Face](https://huggingface.co) |
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- [FAISS](https://ai.meta.com/tools/faiss/) |
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- [Groq](https://groq.com) |
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- [streamlit](https://www.langchain.com) |
