✨ AI interface for tinkerers (Ollama, Haystack RAG, Python)
🔥 Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation 🔥
BestRAG: A library for hybrid RAG, combining dense, sparse, and late interaction methods for efficient document storage and search.
Multimodal Document Processing RAG with LangChain
Just some initial learning for usage of AI models within .NET platform with Semantic Kernel APIs
Dataviz AI is an AI powered web application that enables users to generate animated infographic videos based on input Data , text,files. This MVP leverages the Pexels API for video content and incorporates advanced natural language processing (NLP) techniques, including LangChain and stable diffusion techniques, to analyze and create visual impact
An AI-powered email assistant that retrieves emails and generates intelligent responses
This repository highlights my learning journey in building Retrieval-Augmented Generation (RAG) pipelines using DeepSeek on Lightning AI, covering document ingestion, retrieval, and integration with generative AI. It showcases fine-tuning, evaluation, and optimization for accurate open-domain QA and knowledge management.
Simple rag implementation for any WordPress blog. Leverages the bootstrap, python, milvus vector dB, and configurable options for LLM providers (Open AI, Anthropic) and embeddings.
A football domain-specific knowledge dialogue model implemented using Retrieval-Augmented Generation (RAG) + GPT-3.5 API + Gradio frontend~
Intent API enables the management of network devices with the help of ChatGPT by utilizing Netmiko for SSH control and NetBox for centralized network data management to perform vendor-agnostic, intent-based operations.
Needle components for Haystack projects.
A simple framework for packing source packages written in any programming language into a text file and restoring them into the original directory structure
A medical NLP project developed for the WS2023 course, focusing on extracting, processing, and analyzing medical text data using advanced NLP techniques. This project aims to improve information retrieval and decision-making in healthcare.
An on-going chatbot project. Deployed on Heroku and Github Page.
RAG (Retrieval-augmented generation) app made with Flutter, Firebase, Gemini, LangChain and Pinecone.
Retrieval-Augmented Generation on YouTube transcripts and PDFs to deliver accurate and contextual answers.
An interactive AI-powered study assistant that helps users engage with their study materials through a chat interface. The application uses LangChain and Ollama to provide intelligent responses based on uploaded PDF documents.
A platform built to make learning easy and collaborative. With Library, users get filtered YouTube content for better understanding, real-time doubt-solving, and quick revision tools—all in one place.
A question-answering framework empowered with a custom retrieval-augmented generation (RAG) pipeline to answer queries on local documents
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