Project 5 — LangGraph Research Agent¶
Build a multi-node LangGraph agent that takes a research question, plans sub-questions, researches each one, synthesizes findings, and runs a critic loop to ensure quality. This is the most architecturally complex project — it demonstrates stateful, conditional, multi-agent reasoning.
What you'll build¶
A LangGraph graph with: - Planner node — decomposes the research question into 3–5 sub-questions - Researcher node — answers each sub-question (in parallel, with asyncio.gather) - Writer node — synthesizes findings into a structured report - Critic node — evaluates quality and provides feedback - Conditional router — loops back to writer if quality is below threshold (max 3 loops) - A FastAPI endpoint that exposes the agent as a streaming API
Skills covered¶
| Skill | Where |
|---|---|
| LangGraph StateGraph | 02-implementation |
| Conditional routing | 02-implementation |
| Parallel node execution | 02-implementation |
| MemorySaver checkpointing | 03-advanced-features |
| Agent quality evaluation | 04-evaluation |
| LangSmith tracing | 03-advanced-features |
Prerequisites¶
- Week 02 Day 03 Part 1 — AI Agents
- Week 02 Day 03 Part 2 — LangGraph
Tech stack¶
langchain==0.3.7
langchain-openai==0.2.3
langgraph==0.2.28
langsmith==0.1.147
fastapi==0.115.0
uvicorn==0.30.6
pydantic==2.9.0
python-dotenv==1.0.1