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141 repositories
- A smart movie chatbot built with the Agent-to-Agent (A2A) protocol and Google’s Genkit AI. It features real-time movie data, quote generation, and interactive chat via API and CLI. Ask ChatGPT
- A scalable AI chatbot platform built with FastAPI and LangGraph, featuring multi-agent orchestration, multi-tenant vector storage, cross-chat memory, and voice call capabilities through LiveKit integration.
- A sophisticated AI-powered study companion chatbot that leverages advanced AI capabilities with vector store memory retention and Model Context Protocol (MCP) integration. This project combines modern technologies for both backend and frontend to deliver a seamless learning experience with both text and voice chat capabilities.
- A sophisticated healthcare chatbot that leverages advanced AI capabilities with memory retention to provide personalized medical information and assistance. This project combines modern technologies for both backend and frontend to deliver a seamless user experience.
- A TypeScript-based Ai agent with MCP integration. This project provides a unified interface to access financial market information and relevant news articles through MCP servers with tool calling.
- Livekit voice assistant for integration with flutter
- An intelligent healthcare assistant with memory capabilities, built using FastAPI, Chainlit, and mem0. This bot can remember patient information across conversations, providing personalized healthcare support.
- A voice assistant application developed with Flutter, leveraging the Vapi SDK for smooth voice interactions and a raw WebSocket implementation for tailored, custom solutions.
- Podcast Summary & Q&A App is project takes podcast episodes from the Podcast Index, converts the audio into text, summarizes the content, generates an image based on the summary, translates the summary into French, and allows users to ask questions about the episode. ElevenLabs, HuggingFace, Replicate services are used
- The LinkedIn Profile Search Assistant is a tool designed to streamline the process of finding the most relevant LinkedIn profiles based on company information provided through Google search results. This service automates the task of identifying and selecting the appropriate LinkedIn account, saving time and ensuring accuracy
ai-diagram-service
PublicThis Java Spring Boot service leverages TogetherAI's advanced models to convert image and text inputs into PlantUML diagrams- The AI Video Insights Assistant is a backend service that uses advanced AI orchestration to analyze YouTube video content and accurately answer user questions. Built on LangChain4j or Spring AI, it leverages embeddings and similarity search for precise responses and includes fallback options for comprehensive coverage.
ai-museum-app
PublicMuseo Insight is a virtual museum guide offering rich insights into artworks. Built with Java 21, Spring Boot 3.3.3, and LangChain4J, it integrates the MET Museum API for easy searches and image access. AI-driven descriptions reveal historical, cultural, and visual details, plus artist background and creation year for each piece.movies-ai-search-demo
PublicLangChain4j Neo4j Graph RAG - Movies Search Demo. An AI-powered movie database application built with Java 21, Spring Boot 3.3.3, and Neo4j. The app uses LangChain4j to enable natural language queries, providing personalized recommendations, interactive graph visualizations, and dynamic data exploration.- A collection of demonstrations showcasing different patterns for implementing multi-agent workflows using LangGraph. Each example highlights specific orchestration approaches to help developers understand and build collaborative AI systems.
- A self-reflective and adaptive RAG system that dynamically routes queries between web search and vector retrieval, assesses document relevance, checks for hallucinations, and ensures answer quality using a graph-based flow architecture.
- A showcase implementation demonstrating how to build an intelligent Q&A system using LangGraph and Neo4j Graph Database. This project combines the power of Large Language Models (LLMs) with graph database capabilities to answer questions about movie data.
- This application is a full-stack document indexing and retrieval system that allows users to upload documents, index their content, and perform natural language queries against the indexed documents. It utilizes LlamaIndex, OpenAI embeddings, and a modern React frontend to provide an interactive experience for semantic search and document retrieval
- This repository contains a collection of demonstration projects showcasing various capabilities and applications of LlamaIndex, a powerful data framework for building LLM applications with custom data. Each tutorial focuses on a specific aspect of LlamaIndex functionality, ranging from basic usage to advanced features like RAG, chatbots, etc.
advanced_rag_techniques
PublicThis repository contains a series of lessons demonstrating advanced Retrieval-Augmented Generation (RAG) techniques using LangChain. Each lesson focuses on a specific approach to improve retrieval quality and efficiency.- This repository contains a collection of scripts demonstrating advanced Retrieval-Augmented Generation (RAG) techniques using LlamaIndex and OpenAI. Each lesson focuses on a specific aspect of modern RAG systems, providing hands-on examples and evaluation methods and evaluation capabilities using TruLens
- This repository contains an intelligent web scraping solution that uses ScrapeGraphAI for LLM-powered content extraction and LangGraph for orchestrating the scraping workflow. The system can intelligently crawl websites, extract content using natural language instructions, and search for specific information.
- This repository contains an intelligent web scraping solution that uses Firecrawl for content extraction and LangGraph for orchestrating the scraping workflow. The system can automatically crawl websites, extract content, and search for specific keywords or information.
- A FastAPI-based backend service for a personal assistant voice agent integrated with Vapi AI. This project demonstrates how to build a structured API that handles todo lists, reminders, calendar events, and phone calls through voice commands processed by AI.
- AI-powered support system for EV charging stations with LangGraph orchestration, multi-provider LLM support, and voice interface through VAPI integration for phone calling. This system allows users to check station status, reboot charging stations, and get assistance through text or voice interactions.
- A modular system for creating AI agents using the Model Context Protocol (MCP). This framework allows connecting to multiple MCP servers simultaneously, aggregating tools, and executing queries using LangChain agents
extra-clarity
Publicai-study-companion-app
PublicFlutter mobile and web app for simplifying learning process. Capable of working with pdf, jpeg, txt, doc files. Can summarize documents and create quizes based on summary