add: main.py — Human-in-the-loop (interrupt / resume)

main.py

@@ -0,0 +1,135 @@
+import os
+import asyncio
+from typing import TypedDict, Annotated, List, Any
+
+from langgraph.graph import StateGraph, START, END
+from langgraph.checkpoint.memory import InMemorySaver
+from langgraph.types import interrupt, Command
+from langgraph.graph.message import add_messages
+
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import HumanMessage
+from langchain.tools import tool
+
+from deepagents import create_deep_agent
+from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
+
+# ---------- LLM ----------
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://openrouter.ai/api/v1",
+    api_key=os.getenv("OPENAI_API_KEY"),
+    temperature=0.0,
+)
+
+# ---------- Backend for deepagents ----------
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# ---------- Example tool ----------
+@tool
+def echo_tool(text: str) -> str:
+    """Return the same text back."""
+    return text
+
+# ---------- DeepAgent ----------
+agent = create_deep_agent(
+    model=llm,
+    tools=[echo_tool],
+    backend=backend,
+    system_prompt="You are a helpful assistant.",
+)
+
+# ---------- Graph state ----------
+class GraphState(TypedDict):
+    messages: Annotated[List[Any], add_messages]
+    human_value: str
+
+# ---------- Node that triggers interrupt ----------
+def ask_human_node(state: GraphState):
+    # Prepare payload for interrupt
+    payload = {
+        "type": "confirm",
+        "question": "Do you want to continue?",
+        "options": ["approve", "reject"],
+    }
+    # Raise interrupt; execution will pause here
+    return interrupt(payload)
+
+# ---------- Node after resume ----------
+def after_human_node(state: GraphState):
+    # The resumed payload will contain the answer under key 'answer'
+    answer = state.get("human_value", "no answer")
+    # Use deepagent to produce a final message
+    result = asyncio.run(
+        agent.ainvoke(
+            {"messages": [HumanMessage(content=f"User answered: {answer}")]},
+            {"configurable": {"thread_id": "deepagent-session"}},
+        )
+    )
+    # Append the agent's response to the message list
+    state["messages"].append(result["messages"][-1])
+    return state
+
+# ---------- Build graph ----------
+graph = StateGraph(GraphState)
+
+graph.add_node("ask_human", ask_human_node)
+graph.add_node("after_human", after_human_node)
+
+graph.add_edge(START, "ask_human")
+graph.add_edge("ask_human", "after_human")
+graph.add_edge("after_human", END)
+
+# Use in-memory checkpointing
+graph.set_checkpoint_saver(InMemorySaver())
+app = graph.compile()
+
+# ---------- Runtime loop handling interrupt ----------
+async def run():
+    thread_id = "example-thread"
+    config = {"configurable": {"thread_id": thread_id}}
+
+    # Initial stream
+    stream = app.stream(
+        {"messages": []},
+        config,
+    )
+
+    async for chunk in stream:
+        # Check for interrupt signal
+        if "__interrupt__" in chunk:
+            interrupt_payload = chunk["__interrupt__"][0].value
+            print("\n--- Interrupt received ---")
+            print(f"Type: {interrupt_payload.get('type')}")
+            print(f"Question: {interrupt_payload.get('question')}")
+            # Simple console input (could use questionary)
+            while True:
+                answer = input(f"Choose {interrupt_payload.get('options')}: ").strip()
+                if answer in interrupt_payload.get("options"):
+                    break
+                print("Invalid option, try again.")
+            # Add answer to payload
+            interrupt_payload["answer"] = answer
+
+            # Resume graph with the updated payload
+            resume_cmd = Command(resume=interrupt_payload)
+            resume_stream = app.stream(resume_cmd, config)
+
+            async for resume_chunk in resume_stream:
+                if "__interrupt__" in resume_chunk:
+                    # Should not happen in this simple example
+                    continue
+                if "messages" in resume_chunk:
+                    # Final state reached
+                    final_state = resume_chunk
+                    print("\n--- Final state ---")
+                    for msg in final_state["messages"]:
+                        print(msg.content)
+                    return
+
+# ---------- Entry point ----------
+if __name__ == "__main__":
+    asyncio.run(run())