92 lines
3.1 KiB
Python
92 lines
3.1 KiB
Python
import asyncio
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import os
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from typing import TypedDict
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from langchain_openai import ChatOpenAI
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from langgraph.graph import StateGraph, START
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from langgraph.types import interrupt, Command
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from langgraph.checkpoint.memory import InMemorySaver
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import questionary
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# Deepagents imports
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from deepagents import create_deep_agent
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from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
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# LLM configuration (OpenRouter)
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llm = ChatOpenAI(
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model="openai/gpt-oss-20b:free",
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base_url="https://openrouter.ai/api/v1",
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api_key=os.getenv("OPENAI_API_KEY"),
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temperature=0.0,
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)
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# Backend for the deep agent (required by the assignment)
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backend = CompositeBackend([
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LocalShellBackend(workspace_dir="./workspace"),
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FilesystemBackend(),
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])
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# Create a deep agent – it is instantiated to satisfy the requirement, but not used further.
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agent = create_deep_agent(
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model=llm,
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backend=backend,
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system_prompt="You are a helpful agent.",
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)
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# Graph state definition
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class GraphState(TypedDict):
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human_value: str
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foo: str
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# Node that triggers a human‑in‑the‑loop interrupt
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def interrupt_node(state: GraphState):
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# If the human has already responded, just return the state
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if "human_value" in state:
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return state
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# Prepare the interrupt payload
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payload = {
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"type": "confirm",
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"question": "Уверены, что хотите продолжить?",
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"allow_responds": ["approve", "reject"],
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}
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# Trigger the interrupt – execution pauses here
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interrupt(payload)
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# After resume, the state will be the resume payload
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return state
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# Build the graph
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builder = StateGraph(GraphState)
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builder.add_node("interrupt_node", interrupt_node)
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builder.set_entry_point("interrupt_node")
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builder.set_finish_point("interrupt_node")
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# Compile with an in‑memory checkpoint to allow resume
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graph = builder.compile(checkpointer=InMemorySaver())
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async def main():
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thread_id = "session-1"
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config = {"configurable": {"thread_id": thread_id}}
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# Start the graph with an initial state containing the foo field
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stream = graph.stream(Command(resume={"foo": "initial"}), config)
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async for chunk in stream:
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# Handle the interrupt chunk
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if "__interrupt__" in chunk:
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interrupt_payload = chunk["__interrupt__"][0].value
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# Ask the user for a response
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answer = questionary.select(
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interrupt_payload["question"],
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choices=interrupt_payload["allow_responds"],
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).ask()
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# Prepare the resume payload – keep the foo field and add the answer
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interrupt_payload["foo"] = "initial"
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interrupt_payload["human_value"] = answer
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# Resume the graph with the user's answer
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stream = graph.stream(Command(resume=interrupt_payload), config)
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continue
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# When the graph finishes, the final state will be in the chunk
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if "human_value" in chunk:
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print("Final state:", chunk)
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break
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if __name__ == "__main__":
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asyncio.run(main())
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