awesome-ai-apps

Arindam200 / awesome-ai-apps

Python AI/ML 项目,涉及agents、AI、hacktoberfest

Python RAG LLM 应用 agents AI hacktoberfest 大语言模型 mcp

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Awesome AI Apps Awesome

This repository is a comprehensive collection of 132 projects, tutorials, and recipes for building powerful LLM-powered applications, including text agents, voice assistants, RAG apps, and MCP-backed tools. These projects serve as a guide for developers working with various AI frameworks and stacks.

📋 Table of Contents


💎 Sponsors

A huge thank you to our sponsors for their generous support!

Web Data Platform AI Inference Provider AI Web Scraping framework
SQL Native Memory for AI Agentic Application Platform Auth Stack for AI
AI Observability Platform Kubernetes for AI Agents

💎 Become a Sponsor

Interested in sponsoring this project? Feel free to reach out!


🧩 Starter Agents

Quick-start agents for learning and extending different AI frameworks. 20 projects

🪶 Simple Agents

Straightforward, practical use-cases for everyday AI applications. 18 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. 34 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


📥 Stay Updated with Daily AI Insight!

Get easy-to-follow weekly tutorials and deep dives on AI, LLMs, and agent frameworks. Perfect for developers who want to learn, build, and stay ahead with new tech. Subscribe our Newsletter!

Subscribe to our Newsletter


Getting Started

Prerequisites

  • Python 3.10+ (Python 3.11+ recommended for newer projects)
  • Git for cloning the repository
  • Package Manager: pip or uv (recommended for faster installs)
  • API Keys: Most projects require API keys (see individual project READMEs)

Quick Start

  1. Clone the repository

bash git clone https://github.com/Arindam200/awesome-ai-apps.git cd awesome-ai-apps

  1. Choose a project and navigate to its directory

bash cd starter_ai_agents/agno_starter # Example: Start with Agno starter

  1. Set up environment variables

bash cp .env.example .env # Copy example environment file # Edit .env with your API keys

  1. Install dependencies

```bash # Using pip pip install -r requirements.txt

# OR using uv (recommended - faster) uv sync # or uv pip install -e . ```

  1. Run the project

bash python main.py # or for Streamlit apps streamlit run app.py

🤝 Contributing

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

  • 💡 Add new projects: Submit your own AI agent examples
  • 🔧 Fix issues: Contribute code improvements and bug fixes
  • 📝 Improve documentation: Help make projects more accessible
  • 🐛 Report bugs or suggest improvements via GitHub Issues

Before contributing:

  • Read our Contributing Guidelines for detailed information
  • Check existing issues to avoid duplicates
  • Follow the project structure and naming conventions
  • Ensure your project includes a comprehensive README.md

Important: This project follows a Contributor Code of Conduct. By participating, you agree to abide by its terms.

📜 License

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

👥 Core Maintainers

This project is actively maintained by:

       

Arindam Majumder  ·  Shivay Lamba  ·  Amitesh Anand

For any questions, suggestions, or contributions, feel free to reach out to the maintainers.

Thank You for the Support! 🙏

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文档抓取自 GitHub 仓库 README,版权归原作者所有;已过滤徽章等噪音并经安全消毒后展示。