mirror of
https://github.com/langchain-ai/langgraph.git
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42 lines
2.2 KiB
YAML
42 lines
2.2 KiB
YAML
#A list of third-party packages to surface on the third-party page.
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packages:
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- name: "trustcall"
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repo: "hinthornw/trustcall"
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description: "Tenacious tool calling built on LangGraph."
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- name: "breeze-agent"
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repo: "andrestorres123/breeze-agent"
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description: "A streamlined research system built inspired on STORM and built on LangGraph."
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- name: "langgraph-supervisor"
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repo: "langchain-ai/langgraph-supervisor-py"
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description: "Build supervisor multi-agent systems with LangGraph."
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- name: "langmem"
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repo: "langchain-ai/langmem"
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description: "Build agents that learn and adapt from interactions over time."
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- name: "langchain-mcp-adapters"
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repo: "langchain-ai/langchain-mcp-adapters"
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description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
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- name: "open-deep-research"
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repo: "langchain-ai/open_deep_research"
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description: "Open source assistant for iterative web research and report writing."
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- name: "langgraph-swarm"
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repo: "langchain-ai/langgraph-swarm-py"
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description: "Build swarm-style multi-agent systems using LangGraph."
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- name: "delve-taxonomy-generator"
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repo: "andrestorres123/delve"
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description: "A taxonomy generator for unstructured data"
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- name: "nodeology"
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repo: "xyin-anl/Nodeology"
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description: "Enable researcher to build scientific workflows easily with simplified interface."
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- name: "langgraph-bigtool"
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repo: "langchain-ai/langgraph-bigtool"
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description: "Build LangGraph agents with large numbers of tools."
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- name: "ai-data-science-team"
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repo: "business-science/ai-data-science-team"
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description: "An AI-powered data science team of agents to help you perform common data science tasks 10X faster."
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- name: "langgraph-reflection"
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repo: "langchain-ai/langgraph-reflection"
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description: "LangGraph agent that runs a reflection step."
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- name: "langmanus"
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repo: "langmanus/langmanus"
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description: "A community-driven AI automation framework that builds upon the incredible work of the open source community. Our goal is to combine language models with specialized tools for tasks like web search, crawling, and Python code execution, while giving back to the community that made this possible."
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