Multimodal Document Processing RAG with LangChain
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ChatPDF leverages Retrieval Augmented Generation (RAG) to let users chat with their PDF documents using natural language. Simply upload a PDF, and interactively query its content with ease. Perfect for extracting information, summarizing text, and enhancing document accessibility.
In this project I have built an end to end advanced RAG project using open source llm model, Mistral using groq inferencing engine.
A knowledge base constructed based on Langchain+RAG+LLM
Chat With Documents is a Streamlit application designed to facilitate interactive, context-aware conversations with large language models (LLMs) by leveraging Retrieval-Augmented Generation (RAG). Users can upload documents or provide URLs, and the app indexes the content using a vector store called Chroma to supply relevant context during chats.
In this end to end project I have built a RAG app using ObjectBox Vector Databse and LangChain. With Objectbox you can do OnDevice AI, without the data ever needing to leave the device.
Implement RAG using LangChain and HuggingFace embedding models
Memomind is a sleek note-taking app built with React 18, Next.js 14, and TypeScript. It features a chat-based RAG workflow, AI-powered insights with Langchain and Llama3, and secure authentication via Clerk. It uses Tailwind CSS for styling and Shadcn-UI for components.
SDLC AI Agent is an AI-powered tool that streamlines the entire Software Development Lifecycle from requirements gathering to code generation and testing.
A ChatBot designed to assist WhatsAgenda customers in configuring their calendar. This tool streamlines the setup of scheduling, managing appointments, and customizing service hours, ensuring an efficient and user-friendly experience.
This project demonstrates a routing agent setup using LlamaIndex, Groq's LLaMA3-70B model, and HuggingFace Embeddings for answering queries from multiple domain-specific documents.
Repo for DermAssist: Your AI Assitant for Skin Problems. Powered by a vision model and a reliable RAG system.
Conversational RAG with PDF and chat history
In this project I have built an advanced RAG Q&A chatbot with chain and retrievers using Langchain
This project combines the power of vector databases, large language models, and chat history management to create an interactive PDF chatbot
Analysis Agent on Llamaindex Typescript with a simple caching mechanism
Retrieval-Augmented Generation on YouTube transcripts and PDFs to deliver accurate and contextual answers.
A RAG Model ChatBot for jamia Millia Islamia
EquiInsight is a specialised user-friendly platform made for investors, analysts, and financial professionals who specialise in equity markets. It is intended to make information retrieval simple. To get pertinent insights from the stock market and financial sphere, users can ask queries and input the URLs of articles.
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