GH Repository · NirDiamant
agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
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agent-appJupyter Notebookmcpagentic-aimulti-agent-systemsagent-frameworkagentspythonllmai-agentsobservabilityproductiongenairaggenerative-aillmsmlopsagentdeploymenttutorialslanggraph
A collection of end-to-end, code-first tutorials for building production-grade GenAI agents, written as Jupyter Notebooks in Python. Topics covered include LangGraph, MCP, multi-agent systems, RAG, observability, MLOps, and deployment, moving from prototype to enterprise use.
It gives you runnable, tutorial-style code paths for taking an agent beyond prototype into production.
Use it to
- Follow end-to-end tutorials for production agent builds
- Learn multi-agent and RAG patterns in Python
- Study deployment and observability practices for agents
- Explore LangGraph and MCP through worked examples
For Developers building GenAI agents for production
- Role
- agent-app
- Language
- Jupyter Notebook
- Licence
- custom (licence file present)
- Forks
- 2,848
- Last push
- 2026-09-15
topicsagentsgenaitutorialslanggraphproductionrag