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

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Awesome AI Apps Awesome

Arindam200%2Fawesome-ai-apps | Trendshift

This repository is a comprehensive collection of practical examples, tutorials, and recipes for building powerful LLM-powered applications. From simple chatbots to advanced AI agents, these projects serve as a guide for developers working with various AI frameworks and tools.


πŸ’Ž Sponsors

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

Bright Data - Web Data Platform
Web Data Platform
Visit Bright Data website
Nebius AI - AI Platform
AI Inference Provider
Visit Nebius AI website
ScrapeGraphAI - Web Scraping Library
AI Web Scraping framework
View ScrapeGraphAI on GitHub
GibsonAI - AI for Databases
AI for Databases
Visit GibsonAI website

πŸ’Ž Become a Sponsor

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


πŸŽ“ NEW: AWS Strands Course for Beginners

Comprehensive hands-on course on building AI agents with AWS Strands SDK:

  • AWS Strands Course - Complete 8-lesson course covering agent fundamentals to production patterns
    • Foundation: Basic agents, session management, structured output
    • Integration: MCP agents, human-in-the-loop patterns
    • Multi-Agent: Orchestrator agents, swarm intelligence, graph workflows
    • Production: Observability, safety guardrails, and best practices

πŸš€ Featured AI Apps

🧩 Starter Agents

Quick-start agents for learning and extending:

πŸͺΆ Simple Agents

Straightforward, practical use-cases:

πŸ—‚οΈ MCP Agents

Examples using Model Context Protocol:

🧠 Memory Agents

Agents with advanced memory capabilities:

πŸ“š RAG Applications

Retrieve-augmented generation examples:

πŸ”¬ Advanced Agents

Complex pipelines for end-to-end workflows:

πŸ“Ί Playlist of Demo Videos & Tutorials

πŸŽ“ Course Playlists

πŸ”§ Framework Tutorials


πŸ“₯ 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 or higher
  • Git
  • pip (Python package manager) or uv

Installation Steps

  1. Clone the repository

    git clone https://github.com/Arindam200/awesome-ai-apps.git
  2. Navigate to the desired project directory

    cd awesome-ai-apps/starter_ai_agents/agno_starter
  3. Install the required dependencies

    pip install -r requirements.txt
  4. Follow project-specific instructions

    • Each project has its own README.md with detailed setup and usage instructions
    • Make sure to read the project-specific documentation before running the application

🀝 Contributing

We welcome contributions from the community! If you'd like to contribute, please see our Contributing Guidelines for more information on how to get started.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

πŸ“œ License

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

Thank You for the Support! πŸ™

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