A tutorial based on MetaGPT to quickly help you understand the concept of agent and muti-agent and get started with coding development. 基于MetaGPT的多智能体入门与开发教程

This repository will contain projects on multi-agent applications using frameworks such as crewai, langchain, gradio, hugging face etc.

A Streamlit webapp deployed on Hugging Face Spaces featuring multiple AI agents built using LangGraph, LangChain, and LLMs. Includes a Startup Idea Validator, Travel Planner, and Agentic AI Chatbot with tools like web search and code execution etc. A modular platform for real-world, graph-driven multi-agent AI interactions.

LangGraph-based AI agents tackling complex tasks from the GAIA benchmark. Final project for the Hugging Face Agents course. Includes ReAct, Reflection, Plan-Execute, and Multi-Agent systems.

An end‑to‑end multi‑agent pipeline that turns a simple topic into a 30‑second video by researching the niche, writing a 6‑segment script, generating AI voiceover and images (OpenAI, Hugging Face, or Pollinations), animating clips with MoviePy, and assembling the final MP4.

A comprehensive implementation of the HuggingFace and Langchain-academy Agentic AI course. Explore LLM-powered agents using transformers-agents, custom tools, multi-step reasoning, and real-world deployment workflows across Hugging Face's agent framework and inference APIs.

A multi-agent system leveraging Hugging Face's smolagents to automate content creation by coordinating research, writing, and editing tasks through collaborative AI agents.

A compact of multi-agent mission planning using LangChain + Hugging Face Transformers with a simple grid/maze environment. The LLM acts as a high-level planner assigning subgoals to agents, and agents execute them using A* style pathfinding.

Multi-agent AI system for veterinary text analysis using synthetic data. Fine-tuned VetBERT classifies pet owner notes, Qdrant retrieves relevant cases, and T5 explains clinical terms and assists with appointment scheduling. Built with Flask API and managed on Hugging Face.

Learn how to build a powerful AI agent that runs entirely on your computer using Ollama and Hugging Face's smolagents. Unlike traditional AI chatbots, this agent thinks in Python code to solve problems - from complex calculations to multi-step reasoning. Complete setup guide included with no API keys, cloud services, or recurring costs required.

Hugging Face Multi-Agent Geospatial Analysis System

Multi‐agent legal RAG based chatbot using LangChain, Pinecone, Docling, Hugging Face

A modular, multi-agent based system for PyTorch, Hugging Face, and AWS.

This implementation highlights the Agentic RAG implementation using ApertureDB data store, which is a graph-based multimodal database. Hugging Face SmolAgents will be employed for implementing a multi-agent LLM workflow.

My free to run solution for the Hugging Face final agents course assignment, featuring a resilient multi-key failover mechanism, tool integrations and really robust retry logic.

SentinelOne 🛰️ – Climate Risk Agents Multi-agent platform built with Gradio & Smolagents to monitor, process, and analyze environmental data. Provides real-time climate risk assessment & actionable recommendations. 🏆 2nd place at Hugging Face Agents & MCP Hackathon (600+ projects).

A deployable, multi-agent system that mimics a radiologist’s diagnostic workflow using cutting-edge vision-language models (VLMs), cross-modal retrieval, and structured agent collaboration. Built with CrewAI and deployed on Hugging Face Spaces.

Hands-on collection of Generative AI apps and notebooks using LLMs, LangChain, RAG, vector databases, Hugging Face, NVIDIA NIM, and multi-agent systems—showcasing real-world AI/ML engineering skills.

An experimental Python framework for building modular multi-agent systems with support for OpenAI, Anthropic, Perplexity, and Hugging Face LLMs. Features tool routing, authentication, logging, and feedback. Ideal for prototyping and research in AI agent architectures.

Multi-agent research assistant powered by smolagents & Hugging Face. Automatically searches arXiv, downloads papers, extracts PDFs, and generates summaries using BART. Synthesizes comprehensive research reports from multiple sources. Built with transformers, PyPDF2, and Gradio UI.

AI Agent achieving 100% accuracy on GAIA benchmark. Features multi-model LLM orchestration with automatic Groq fallback, tool integration (web search, file processing, mathematical computation), and comprehensive API architecture. Built with Python, Hugging Face Transformers, and Gradio.

Production-grade Multi-Agent AI Knowledge Assistant using RAG, FastAPI, Hugging Face, Qdrant, Redis, PostgreSQL, Docker, Terraform, and Cloud Platform (AWS ECS). Demonstrates end-to-end AI engineering, MLOps, cloud deployment, and observability with Prometheus and Grafana.

Build and run a lightweight multi-agent AI system in Google Colab that summarizes English text and translates it into Spanish or Urdu — using Hugging Face models and GenAI protocol decorators. Created for the LeadWithAI Hackathon 2025.

A modular, multi-agent based system for PyTorch, Hugging Face, and AWS.

I have used pre-trained models of hugging face transformers as tools for agents in multi agent system

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Multi-Agent AI Response Engine with Hugging Face Models

A high-performance, multi-agent chatbot framework leveraging LangGraph for orchestration, Groq’s Gemma-2 LLM for fast inference, HuggingFace for embeddings, and Cassandra (Astra DB) as the vector store.

Multi-agent framework for turning research papers into Hugging Face-compatible PyTorch repositories

Multi AI Agent weather alert system using LLM and Langchain from hugging face