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A comprehensive collection of practical examples, tutorials and recipes showcasing how to build powerful LLM-powered applications using various frameworks and tools.

From simple chatbots and MCP examples to advance AI Agents, this repository serves as your guide to building some cool AI applications.

• Google Agent Development Kit (ADK)
• OpenAI Agents SDK
• LangChain
• LlamaIndex
• Agno
• CrewAI
• AWS Strands Agent
• Pydantic AI

Quick-start agents for learning and extending:

• Agno HackerNews Analysis - Agno-based agent for trend analysis on HackerNews.
• OpenAI SDK Starter - OpenAI Agents SDK based email helper & haiku writer.
• LlamaIndex Task Manager - LlamaIndex-powered task assistant.
• CrewAI Research Crew - Multi-agent research team.
• PydanticAI Weather Bot - Real-time weather info.
• LangChain-LangGraph Starter - LangChain + LangGraph starter.
• AWS Strands Agent Starter - Weather report Agent.

Straightforward, practical use-cases:

• Finance Agent - Tracks live stock & market data.
• Human-in-the-Loop Agent - HITL actions for safe AI tasks.
• Newsletter Generator - AI newsletter builder with Firecrawl.
• Reasoning Agent - Financial reasoning step-by-step.
• Agno UI Example - UI for web & finance agents.
• Mastra Weather Bot - Weather updates with Mastra AI.
• Calendar Assistant - Calendar scheduling with Cal.com.
• Memory Agent - Simple Memory Agent implementation with .
• Nebius Chat - Nebius AI Studio Chat interface.

Examples using Managed Compute Providers:

• Doc-MCP - Semantic RAG docs & Q&A.
• LangGraph MCP Agent - LangChain ReAct agent with Couchbase.
• GitHub MCP Agent - Repo insights via MCP.
• MCP Starter - GitHub repo analyzer starter.

Retrieve-augmented generation examples:

• Resume Optimizer - Boost resumes with AI.
• LlamaIndex RAG Starter - LlamaIndex + Nebius RAG starter.
• PDF RAG Analyzer - Chat with multiple PDFs.
• Qwen3 RAG Chat - PDF chatbot with Streamlit.
• Chat with Code - Conversational code explorer.
• Gemma3 OCR - OCR-based document and image processor using Gemma3

Complex pipelines for end-to-end workflows:

• Deep Researcher - Multi-stage research with Agno & Scrapegraph AI.
• Candilyzer - Analyze GitHub/LinkedIn profiles.
• Job Finder - LinkedIn job search with Bright Data.
• AI Trend Analyzer - AI trend mining with Google ADK.
• Conference Talk Generator - Draft talk abstracts with Google ADK & Couchbase.
• Finance Service Agent - FastAPI server for stock data and predictions with Agno.

• Build with MCP
• Build AI Agents
• AI Agents, MCP and more...

• Python 3.10 or higher
• Git
• pip (Python package manager) or uv

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

We welcome contributions from the community! Whether you're a beginner or an expert, your examples and tutorials can help others learn and grow. Here's how you can contribute:

1. Submit a Pull Request with your LLM application example
2. Add detailed documentation and setup instructions
3. Include requirements.txt or environment.yml
4. Share your experience and best practices

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