Project — Build a Document Processing Agent with Multi-Modal Inputs
Build a LangGraph agent that processes PDFs, images, and text documents — extracting information, cross-referencing sources, and generating structured reports.
Build a LangGraph agent that processes PDFs, images, and text documents — extracting information, cross-referencing sources, and generating structured reports.
Build a production-ready customer support agent in LangGraph that handles queries, searches a knowledge base, escalates to humans, and logs interactions.
Build a LangGraph pipeline that autonomously scrapes websites, extracts structured data, handles pagination and errors, and produces analytical summaries.
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.
Force LangGraph agents to produce validated structured output using Pydantic models, with automatic retry and self-correction on validation failures.
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.
Build a LangGraph agent that converts natural language questions to SQL, queries your database, handles errors, and presents results in clear summaries.
Run graph branches in parallel using LangGraph's Send API and map-reduce pattern to process multiple items concurrently and aggregate results.
Add human approval gates to LangGraph agents. Learn the interrupt mechanism, tool call review, selective approval, multi-step review chains, and state editing — with...
Master all five LangGraph streaming modes — values, updates, messages, custom, and debug. Learn token-level streaming, tool call handling, and how to build responsive...
Learn how LangGraph cycles power agent loops, how recursion_limit prevents runaway execution, and three exit strategies to stop agents gracefully — with full working...
Design multi-agent systems in LangGraph using supervisor, swarm, and network topologies where specialized agents collaborate to solve complex tasks.
Add memory to LangGraph agents with checkpointers. Learn MemorySaver, SqliteSaver, and PostgresSaver — plus state inspection, time travel, and real-world resumable workflows.
Build resilient LangGraph agents that handle tool failures, LLM errors, and unexpected states with retry logic, fallback paths, and graceful degradation.
Build a LangGraph ReAct agent from scratch. Learn the Reason-Act-Observe loop, define tools, wire the graph, and compare manual builds vs create_react_agent — with...
Step-by-step guide to LangGraph tool calling. Learn to define tools with @tool, bind them with .bind_tools(), execute with ToolNode, and build agents that search...
Master LangGraph's three core building blocks: nodes (functions), edges (connections), and state (shared data). Build progressively complex graphs including a conditional order processing pipeline.
Learn how to use conditional edges in LangGraph to build dynamic routing workflows. Master add_conditional_edges(), routing functions, LLM-based branching, parallel paths, and debugging techniques.
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