End-to-End Agent Deployment
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We build a FAQ chatbot from notebook to production. You start with a
Jupyter notebook that calls the OpenAI Responses API with a single
search tool. Then you wrap it in FastAPI and add a vanilla-JS
frontend with streaming (SSE). From there you containerize with Docker,
deploy to Railway, and add a GitHub Actions CI/CD pipeline.
We do each step with a coding agent. The prompts are included verbatim, so you can repeat the same steps with any agent you like.
Links
Useful resources for this workshop:
- Starting notebook (gist)
- The Agentic Loop from Scratch - the same loop built by hand, without the web layer.
The app you will build
The final app looks like this:
The final app answers questions from the
DataTalks.Club Data Engineering Zoomcamp FAQ.
The model gets one tool, search(query). Everything else is the
web layer, the container, and the deploy pipeline.
Hosted by
Alexey Grigorev
Chief Agent Officer at AI Shipping Labs
Software engineer and machine learning practitioner with 15+ years of experience building production ML systems. I focus on practical, production-grade ML and AI systems, from early prototypes to reliable systems in production.
I'm the founder of DataTalks.Club, a free community that connects tens of thousands of practitioners worldwide, and the creator of the Zoomcamp series, free, code-first programs that have reached 100,000+ learners globally.
At AI Shipping Labs, I'm building the kind of environment that would have accelerated my own career growth. After years of teaching at scale, I wanted something more focused: a space for action-oriented builders who want to turn AI ideas into real projects. The community gives members the structure, accountability, and peer support to ship practical AI products consistently, even alongside their main jobs.
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