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pypdf2-library

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A Retrieval-Augmented Generation (RAG) app for chatting with content from uploaded PDFs. Built using Streamlit (frontend), FAISS (vector store), Langchain (conversation chains), and local models for word embeddings. Hugging Face API powers the LLM, supporting natural language queries to retrieve relevant PDF information.

  • Updated Oct 13, 2024
  • Python

The response pdf is neatly organized in a table format in PDF, contains 15 distinct questions and corresponding 106 student answers. Performed sentiment analysis on pdf by extracting the raw data from pdf and convert it into data frame for easy analysis. Then perform column wise and row wise sentiment analysis and shown the result along with graph

  • Updated Apr 22, 2024
  • Jupyter Notebook

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