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Workshop Basic or above

End-to-End Agent Deployment

April 21, 2026 Alexey Grigorev

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 wrap it in FastAPI, add a vanilla-JS frontend with streaming (SSE), containerize with Docker, deploy to Railway, and wire up a GitHub Actions CI/CD pipeline. Each step is done alongside a coding agent. The prompts are included verbatim so you can reproduce the workflow with any agent you like.

Links

Useful resources for this workshop:

The app you will build

The final app looks like this:

flowchart LR UI["Frontend UI<br/>vanilla JS, SSE"] API["FastAPI app"] AGENT["Agent loop"] SEARCH["FAQ search tool<br/>minsearch"] OPENAI["OpenAI Responses API"] UI -->|POST /ask or /ask/stream| API API --> AGENT AGENT -->|tool call| SEARCH AGENT -->|model call| OPENAI API -->|JSON or SSE| UI

The final app is a minimal teaching-assistant chatbot for the DataTalks.Club Data Engineering Zoomcamp FAQ. One tool is exposed to the model: search(query). Everything else is the web layer, the container, and the deploy pipeline.

Tutorial pages

  1. Overview and setup
  2. Part 1: The starting notebook
  3. Part 2: Notebook to FastAPI backend
  4. Part 3: Vanilla-JS frontend with Vite
  5. Part 4: Streaming with Server-Sent Events
  6. Part 5: Dockerize as one container
  7. Part 6: Deploy to Railway via CLI
  8. Part 7: GitHub Actions CI/CD
  9. Deferred items
  10. Q&A: side discussions
  11. Appendix: file inventory

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