If you’ve been wanting to build real AI apps—without starting from scratch—this curated collection is for you. It brings together practical, copy-pasteable projects that show how to build everything from simple chatbots to advanced multi-agent workflows. The entire library is powered by Nebius AI Studio, a one-stop platform for building and deploying AI applications.
Why this collection?
- Hands-on, not theoretical. Every item is a working example you can run and extend.
- Covers the full stack. Starters, simple agents, RAG apps, MCP agents, and advanced workflows—organized and easy to browse.
- Open source & framework-agnostic. Examples span LangChain, LlamaIndex, CrewAI, Agno, OpenAI Agents SDK, and more—so you can pick what fits your stack.
Quick start (2 minutes)
git clone https://github.com/Arindam200/awesome-ai-apps.git
cd awesome-ai-apps/<pick-a-project-folder>
pip install -r requirements.txt
# Then follow the README in that folder
Each folder has its own README with setup notes and usage instructions.
Featured AI Agent Frameworks (at a glance)
Google ADK • OpenAI Agents SDK • LangChain • LlamaIndex • Agno • CrewAI • AWS Strands Agent • Pydantic AI • CAMEL-AI. Use them across the projects below to learn by doing.
🧩 Starter Agents (learn fast, extend easily)
- Agno HackerNews Analysis — trend analysis starter: starter_ai_agents/agno_starter. (GitHub)
- OpenAI SDK Starter — email helper & haiku writer: starter_ai_agents/openai_sdk_starter. (GitHub)
- LlamaIndex Task Manager — task assistant: starter_ai_agents/llamaindex_starter. (GitHub)
- CrewAI Research Crew — multi-agent team: starter_ai_agents/crewai_starter. (GitHub)
- PydanticAI Weather Bot — real-time weather: starter_ai_agents/pydantic_starter. (GitHub)
- LangChain-LangGraph Starter — graph-based flows: starter_ai_agents/langchain_langgraph_starter. (GitHub)
- AWS Strands Agent Starter — weather agent: starter_ai_agents/aws_strands_starter. (GitHub)
- CAMEL-AI Starter — model benchmarking: starter_ai_agents/camel_ai_starter. (GitHub)
🪶 Simple Agents (practical, plug-and-play)
- Finance Agent — live stocks & market data: simple_ai_agents/finance_agent. (GitHub)
- Human-in-the-Loop Agent — safe actions with approval: simple_ai_agents/human_in_the_loop_agent. (GitHub)
- Newsletter Generator — builds AI newsletters (Firecrawl): simple_ai_agents/newsletter_agent. (GitHub)
- Reasoning Agent — step-by-step finance reasoning: simple_ai_agents/reasoning_agent. (GitHub)
- Agno UI Example — UI for web & finance agents: simple_ai_agents/agno_ui_agent. (GitHub)
- Mastra Weather Bot — weather with Mastra AI: simple_ai_agents/mastra_ai_weather_agent. (GitHub)
- Calendar Assistant — scheduling with Cal.com: simple_ai_agents/cal_scheduling_agent. (GitHub)
- Memory Agent — simple memory via Agno: simple_ai_agents/memory_agent. (GitHub)
- Web Automation Agent — browser automation: simple_ai_agents/browser_agent. (GitHub)
- Nebius Chat — Nebius AI Studio chat UI: simple_ai_agents/nebius_chat. (GitHub)
- Talk to Your DB — chat with your database: simple_ai_agents/talk_to_db. (GitHub)
🗂️ MCP Agents (Model Context Protocol)
- Doc-MCP — semantic RAG + Q&A: mcp_ai_agents/doc_mcp. (GitHub)
- LangGraph MCP Agent — ReAct + Couchbase: mcp_ai_agents/langgraph_mcp_agent. (GitHub)
- GitHub MCP Agent — repo insights via MCP: mcp_ai_agents/github_mcp_agent. (GitHub)
- MCP Starter — analyzer starter: mcp_ai_agents/mcp_starter.
- Talk to Your Docs — documentation Q&A: mcp_ai_agents/talk_to_docs.
📚 RAG Applications (retrieve-augment-generate)
- Agentic RAG — agent-orchestrated RAG: rag_apps/agentic_rag. (GitHub)
- Resume Optimizer — boost resumes with AI: rag_apps/resume_optimizer. (GitHub)
- LlamaIndex RAG Starter — RAG + LlamaIndex: rag_apps/llamaindex_rag_starter. (GitHub)
- PDF RAG Analyzer — chat with multiple PDFs: rag_apps/pdf_rag_analyzer. (GitHub)
- Qwen3 RAG Chat — PDF chatbot (Streamlit): rag_apps/qwen_rag_chat.
- Chat with Code — conversational code explorer: rag_apps/chat_with_code. (GitHub)
- Gemma3 OCR — OCR for docs & images: rag_apps/gemma3_ocr.
🔬 Advanced Agents (end-to-end workflows)
- Deep Researcher — multi-stage research with Agno & Scrapegraph: advance_ai_agents/deep_researcher_agent. (GitHub)
- Candilyzer (Candidate Analyzer) — profile analysis: advance_ai_agents/candidate_analyser. (GitHub)
- Job Finder — LinkedIn job search with Bright Data: advance_ai_agents/job_finder_agent. (GitHub)
- AI Trend Analyzer — trend mining with Google ADK: advance_ai_agents/trend_analyzer_agent. (GitHub)
- Conference Talk Generator — abstracts with ADK & Couchbase: advance_ai_agents/conference_talk_abstract_generator. (GitHub)
- Finance Service Agent — FastAPI + predictions: advance_ai_agents/finance_service_agent. (GitHub)
- Price Monitoring Agent — alerts via CrewAI, Twilio & Nebius: advance_ai_agents/price_monitoring_agent. (GitHub)
What to build next?
- Start with a starter. Pick the framework you prefer and run a starter to get the wiring right.
- Swap the tools. Replace the sample data sources (news, PDFs, weather, DB) with your own.
- Go agentic. Move to MCP or advanced agents when you need orchestration, browsing, or multi-step workflows.
Credits
This collection is maintained on GitHub and is powered by Nebius AI Studio. Explore the repo, star it, and remix the projects for your own use cases.
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