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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.
This repository, titled "Python-Utility-Scripts" encompasses a diverse range of Python scripts that demonstrate practical applications in various domains. These scripts serve as excellent examples for those looking to explore Python's capabilities in automating and handling real-world tasks.
Library PyPDF2_Fields is a complement to PyPDF2. It helps reading and setting a PDF file’s fields, knowing their type and controlling their editability.
A PDF question answering bot utilizing Streamlit, PyPDF2, LangChain, OpenAI GPT-3 model, and FAISS(Facebook AI Similarity Search). The bot allows users to upload PDFs, query information from their content, and receive relevant answers, enhancing document accessibility and searchability.
objective -Implimention of end-to-end automation testing of a Ecommerce application using seleniumwebdriver+python+framewors .The developed Framework is Keyword and data driven.
PDF_Merger is a Python script merging multiple PDFs into one. Utilizing 𝗣𝘆𝗣𝗗𝗙𝟮, it streamlines PDF consolidation for enhanced document management ... ❤️
Using gemini 1.5 pro LLM model to analyze job description through carefully crafted prompt and compared against my resume to give out insights, demo video has been added
This Python script merges all PDF files in the current directory into a single PDF file named "merged.pdf" using the PyPDF2 library. It iterates through the PDF files, appends their content to a PdfWriter object, writes the merged content to a new file, and then closes the PdfWriter object.