🦜🕸️ Using Composio With LangGraph

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pip install composio-langgraph

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from typing import Literal
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from langchain_openai import ChatOpenAI
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from langgraph.graph import MessagesState, StateGraph
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from langgraph.prebuilt import ToolNode
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from composio_langgraph import Action, ComposioToolSet, App
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composio_toolset = ComposioToolSet()
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tools = composio_toolset.get_tools(
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    apps=[App.GITHUB]
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)
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tool_node = ToolNode(tools)
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model = ChatOpenAI(temperature=0, streaming=True)
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model_with_tools = model.bind_tools(tools)

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def call_model(state: MessagesState):
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    """
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    Process messages through the LLM and return the response
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    """
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    messages = state["messages"]
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    response = model_with_tools.invoke(messages)
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    return {"messages": [response]}

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def should_continue(state: MessagesState) -> Literal["tools", "__end__"]:
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    """
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    Determine if the conversation should continue to tools or end
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    Returns:
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        - "tools" if the last message contains tool calls
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        - "__end__" otherwise
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    """
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    messages = state["messages"]
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    last_message = messages[-1]
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    if last_message.tool_calls:
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        return "tools"
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    return "__end__"

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workflow = StateGraph(MessagesState)
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workflow.add_node("agent", call_model)
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workflow.add_node("tools", tool_node)
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workflow.add_edge("__start__", "agent")
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workflow.add_conditional_edges(
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    "agent",
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    should_continue,
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)
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workflow.add_edge("tools", "agent")
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app = workflow.compile()

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for chunk in app.stream(
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    {
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        "messages": [
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            (
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                "human",
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                "Star the Github Repository composiohq/composio",
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            )
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        ]
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    },
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    stream_mode="values",
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):
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    chunk["messages"][-1].pretty_print()