Powered by Nebius AI Studio - Your one-stop platform for building and deploying AI applications.
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.
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.
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.
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.
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.
- Python 3.10 or higher
- Git
- pip (Python package manager) or uv
-
Clone the repository
git clone https://github.com/Arindam200/awesome-ai-apps.git
-
Navigate to the desired project directory
cd awesome-ai-apps/starter_ai_agents/agno_starter
-
Install the required dependencies
pip install -r requirements.txt
-
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:
- Submit a Pull Request with your LLM application example
- Add detailed documentation and setup instructions
- Include requirements.txt or environment.yml
- 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.