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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.
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.
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.
Resume Smart ATS is an innovative web application designed. Users simply copy and paste job descriptions from platforms like LinkedIn,Indeed, then upload resumes to the web app. By click on Submit button, Resume Smart ATS analyzes the resumes against the job description, providing users with valuable insights such as JD match perce
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
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