Project — Build a Multi-Agent Research Assistant in LangGraph
Build a multi-agent research system in LangGraph where a planner, researcher, and writer collaborate to produce comprehensive research reports from web sources.
Build a multi-agent research system in LangGraph where a planner, researcher, and writer collaborate to produce comprehensive research reports from web sources.
Build a complete AI application from scratch — a FastAPI backend powered by a LangGraph agent with streaming, persistence, auth, and a chat frontend.
Build a LangGraph agent that writes Python code, executes it in a sandbox, inspects the output, and iterates until the code works correctly.
Deploy your LangGraph agents as production APIs using LangGraph Platform — covering LangGraph Server, the SDK client, and cloud deployment options.
Design multi-agent systems in LangGraph using supervisor, swarm, and network topologies where specialized agents collaborate to solve complex tasks.
Learn what large language models are, how they work, and how to use the OpenAI API in Python to generate text, build multi-turn conversations,...
Learn the four building blocks of LangChain: chat models, prompt templates, output parsers, and chains. Build a real meeting summary pipeline in under 25...
Learn the five core prompt engineering techniques — zero-shot, few-shot, role-based, chain-of-thought, and structured output — to get reliable, parseable results from LLMs using...
Learn what LangGraph is, how it differs from LangChain, and why graph-based orchestration is the right tool for AI agents that loop, branch, and...
Install LangGraph, set up your API key, and build your first working graph — a greeting pipeline and an LLM-calling chatbot — in under...
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