ProjectBuild an Agentic Content Studio: the explanation · Module 9: The research agent and web search · part 11 of 22
Part 11 · Module 9: The research agent and web search

Module 9: The research agent and web search

21 min read·
About 40 minutes · Needs: Module 8 (the LangGraph pipeline), Module 3 (the Ollama model client) · Code: backend/app/ai/agents/research.py, backend/app/ai/search.py, backend/app/ai/prompts.py (research_queries, research_facts)

Where this fits

WHERE THIS FITS Slidesmith Studio this module BROWSER React FRONT DOOR AND API nginx, FastAPI BACKGROUND AGENTS LangGraph MODELS Ollama RENDERING Playwright DATA Postgres 17 OPERATIONS evals, Docker, Cloud Run Studio app React pages /render page same renderer nginx proxy, headers Auth sessions, CSRF Brand kit onboarding, uploads Projects deck spec, edits Job runner progress over SSE Research search, facts Strategist outline Designer slide JSON Check fit, else repair LangGraph pipeline state graph, JSON repair Ideas post ideas from pillars qwen3.8:27b Ollama, local GPU Web search Ollama API Chromium render, measure Exports PDF, PNG, ZIP, HTML PostgreSQL users, decks, jobs Uploads disk or GCS Evaluation suites, gate Insights usage, timings Containers Docker Compose Deploy Cloud Run, CI/CD
The research agent (blue: this module) is the first node of the pipeline. It asks the model (amber) for queries and facts and calls Ollama's web search API (amber: outside our control).

Research is the first node of the generate graph. Before the strategist plans a single slide, this agent looks up the topic on the web, reads a few pages and hands the next agents a short list of facts, each tied to the page it came from. It is optional by design: when it is off or fails, the deck is still made, and the deck says honestly that its claims are unverified.

The rest of this project is yours to keep

This project is bought on its own, once, and stays readable afterwards, including the parts added to it later.

Or open everything with a plan