Harness the Power of Intelligent Search to Uncover Relevant Information from your Documents Instantly using generative AI

A template repository for multi-agents architecture using LangGraph tool from LangChain

Django-based text utility service, offering multi-language translation, sentiment analysis, and text summarization, all seamlessly deployed on AWS Lambda with Docker for robust and scalable performance.

Literature Review Generator

This project allows you to search for academic papers on arXiv, download and process them, and generate responses to specific questions using embeddings and language models. The application leverages several tools including Gradio for the interface, ChromaDB for embedding storage, and LangChain for text processing.

This project showcases how Retrieval-Augmented Generation (RAG) can be applied to create an efficient and user-friendly system for querying large text documents. With this approach, users can easily extract and interact with relevant information from PDFs in real time.

A chat-based agent utilizing the Mistral 7B Large Language Model (LLM), Langchain, Ollama, and Streamlit to answer questions about files through Retrieval-Augmented Generation (RAG).

Trackify offers helpful insights, including thorough descriptions of the CV's strengths, recommendations for improving skills, the discovery of missing keywords, and an overall percentage match, by examining the content of the job description and the resume.

Users can upload documents and seamlessly ask questions about their content, leveraging Retrieval-Augmented Generation (RAG) for precise and context-aware answers.

This repository offers a hands-on guide to mastering Generative AI with Langchain and Huggingface. It covers key concepts, practical implementation, and deployment strategies to help AI enthusiasts, developers, and professionals build and optimize AI models efficiently