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LANGGRAPH
Build resilient language agents as graphs with durable execution and human-in-the-loop control.
MIT
ABOUT
Building complex, stateful LLM agent applications requires managing persistent state, surviving failures, incorporating human oversight, and maintaining memory across sessions — capabilities absent from simpler agent frameworks that only handle basic single-turn tasks without robust orchestration primitives.
INSTALL
pip install -U langgraphINTEGRATION GUIDE
1. Building multi-agent workflows with complex, customizable control flows for single, multi-agent, and hierarchical architectures
2. Creating stateful conversational agents with both short-term working memory and long-term persistent memory across sessions
3. Implementing human-in-the-loop approval and moderation flows where agents pause for human review before executing critical actions
TAGS
agentsllmstatefulorchestrationmulti-agenthuman-in-the-loopdurable-executiongraphlangchainmemorystreaming