langgraph and qd-langchain-agents

LangGraph provides the foundational graph-based agent orchestration framework, while QD-LangChain Agents is a research tool that uses evolutionary algorithms to optimize agent architectures built within that framework—making them complements where one enhances the other.

langgraph
99
Verified
qd-langchain-agents
32
Emerging
Maintenance 25/25
Adoption 25/25
Maturity 25/25
Community 24/25
Maintenance 2/25
Adoption 6/25
Maturity 9/25
Community 15/25
Stars: 26,286
Forks: 4,544
Downloads: 42,304,147
Commits (30d): 145
Language: Python
License: MIT
Stars: 17
Forks: 5
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No risk flags
Stale 6m No Package No Dependents

About langgraph

langchain-ai/langgraph

Build resilient language agents as graphs.

Supports durable execution with automatic state persistence across failures, human-in-the-loop interrupts for agent inspection/modification, and comprehensive memory management combining short-term working state with long-term persistence. Built as a low-level orchestration framework inspired by Pregel and Apache Beam, it integrates seamlessly with LangChain ecosystem tools including LangSmith for observability and LangSmith Deployments for production scaling of stateful workflows.

About qd-langchain-agents

FareedKhan-dev/qd-langchain-agents

Evolving LangChain agent architectures using the Quality-Diversity (QD) algorithm.

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