Skip to content
Projects

Arindam200/awesome-ai-apps has 16,744 GitHub stars and 1,889 forks. GitHot measured -1 stars in 24 hours, +24 in 7 days, and +94 in 15 days. Last checked 2026-11-12 08:19 UTC. Last push 2026-10-30.

How these counts are measured

A collection of projects showcasing RAG, agents, workflows, and other AI use cases

Measured star growth

in 24h
-1
in 7 days
+24
in 15 days
+94
in 1 month
Update delayed

Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.

README.md

Original
Awesome AI Apps

Awesome AI Apps Awesome

138 runnable LLM apps and agents, from 5-minute framework starters to production-grade multi-agent systems.

GitHub stars Forks Contributors Last commit License: MIT PRs welcome

Browse projects · Quick start · Contribute · Sponsor · Newsletter

Awesome AI Apps is a hands-on collection of projects, tutorials and recipes for building LLM-powered applications: text agents, voice assistants, RAG apps, MCP tools and fine-tuning pipelines. Each project lives in its own folder with a README, its own dependencies and a .env.example, so you can clone the repo, open one folder and run it.

💎 Sponsors

A huge thank you to the companies supporting Awesome AI Apps.

Bright Data
Web Data Platform
Nebius Token Factory
AI Inference Provider
ScrapeGraphAI
ScrapeGraphAI · AI Web Scraping
Memori
SQL Native Memory for AI
CopilotKit
Agentic Application Platform
ScaleKit
Auth Stack for AI
Okahu
AI Observability Platform
AgentField
Kubernetes for AI Agents
Byteful
Residential & ISP Proxies

Want your product in front of developers building with LLMs?
Become a sponsor →

🧭 Browse by Category

Category What you'll find Projects
🧩 Starter Agents One minimal agent per framework: Agno, LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, Mastra and more 22
🪶 Simple Agents Single-purpose agents for everyday tasks: finance, calendars, browser automation, SQL 20
🎙️ Voice Agents Real-time voice assistants with LiveKit, Pipecat, Gradium and Deepgram 9
🗂️ MCP Agents Model Context Protocol servers and agents wired to external tools 14
🧠 Memory Agents Agents that remember users and context across sessions 13
📚 RAG Applications Retrieval, reranking, GraphRAG, OCR and citation checking 18
🔬 Advanced Agents Multi-agent pipelines and production-shaped end-to-end workflows 36
🧬 Fine-Tuning LoRA fine-tuning, distillation and deployment of open models 6

Also here: Tutorials & Videos · Quick Start · Contributing · Contributors · Maintainers · License

🚀 Featured AI Apps

🧩 Starter Agents

Quick-start agents for learning and extending different AI frameworks. 22 projects

🪶 Simple Agents

Straightforward, practical use-cases for everyday AI applications. 20 projects

🎙️ Voice Agents

Real-time voice assistants and streaming speech pipelines, including LiveKit, Pipecat, Gradium, and VoxCode (Deepgram + Cursor SDK). 9 projects

🗂️ MCP Agents

Examples using Model Context Protocol for external tool integration. 14 projects

🧠 Memory Agents

Agents with advanced memory capabilities for context retention and personalization. 13 projects

📚 RAG Applications

Retrieval-augmented generation examples for document understanding and knowledge bases. 18 projects

🔬 Advanced Agents

Complex multi-agent pipelines for production-ready end-to-end workflows. 36 projects

🧬 Fine-Tuning

End-to-end examples of fine-tuning open-source LLMs, from data prep to deployment. 6 projects

📺 Tutorials & Videos

🎓 Course Playlists

🔧 Framework Tutorials

⚡ Quick Start

You need Python 3.10+, uv or pip, and the API keys listed in the project's README. Most projects run on Nebius Token Factory.

# 1. Clone the repo and pick a project
git clone https://github.com/Arindam200/awesome-ai-apps.git
cd awesome-ai-apps/starter_ai_agents/agno_starter

# 2. Add your API keys
cp .env.example .env

# 3. Install dependencies
uv sync                              # or: pip install -r requirements.txt

# 4. Run it (each project's README has the exact command)
uv run main.py                       # or: python main.py / streamlit run app.py

🤝 Contributing

We welcome contributions from the community! Here's how you can help:

  • 💡 Add a new project: a self-contained, runnable example with its own README, dependencies and .env.example
  • 🔧 Fix issues: code improvements and bug fixes for existing projects
  • 📝 Improve documentation: help make projects easier to set up and understand
  • 🐛 Report bugs or suggest improvements via GitHub Issues

Before you open a PR, read the Contributing Guidelines, check existing issues to avoid duplicates, and follow the project README template. This project follows a Contributor Code of Conduct; by participating, you agree to abide by its terms.

🌟 Contributors

Awesome AI Apps is built by its community. Thank you to everyone who has shipped a project, fixed a bug or improved the docs! 💜

Want to see your avatar here? Pick an open issue or add a project.

👥 Maintainers

Arindam Majumder
Arindam Majumder

@Arindam200
Shivay Lamba
Shivay Lamba

@shivaylamba
Amitesh Anand
Amitesh Anand

@Astrodevil

For questions, suggestions or partnerships, reach out to the maintainers on GitHub or at [email protected].

📬 Stay Updated

Easy-to-follow weekly tutorials and deep dives on AI, LLMs and agent frameworks, for developers who want to learn, build and stay ahead. Subscribe to our newsletter!

Subscribe to our Newsletter

📜 License

This repository is licensed under the MIT License. Feel free to use and modify the examples for your projects.

⭐ Star History

If this collection helped you, consider giving it a ⭐. It helps other developers find it.

Explore related projects