This project focuses on developing a real-time, intelligent healthcare assistant powered by Agentic RAG (Retrieval-Augmented Generation) and the LangChain framework. Designed to provide multimodal support—text, image, and document-based inputs—it aims to assist medical personnel and individuals in remote areas.

This project explores various LLMs and embedding models using LangChain, integrating OpenAI, Hugging Face, Google Gemini, and Anthropic. It includes chat models, document similarity search, and embeddings with cosine similarity for retrieval. The setup is simple, making it easy to experiment with LLMs and vector search. 🚀 (Big Thankyou to CampusX)

A modular LangChain-based repository integrating Chat Models, traditional LLMs, and Embedding Models from OpenAI, Anthropic, Google, Hugging Face, and Local Inference. Built with the latest LangChain version for rapid prototyping of modern NLP and AI agent workflows.

smolagents 2.0

Open-source LangChain toolkit with custom Chains, ChatModels, Embeddings, and Output Parsers. Build powerful AI workflows effortlessly. Perfect for developers and businesses leveraging LLMs.

This repository is a hands-on implementation of Generative AI: LangChain Models, Build, and Explore LLM-Models. It showcases the core fundamentals of LangChain, OpenAI/Gemini integrations, and Hugging Face models.

A unified LangChain-based framework that integrates and compares leading LLMs — including OpenAI, Gemini, Claude, and Hugging Face — enabling cross-model experimentation, chat pipelines, and intelligent agent development.