From 7dca7dacb9f2cd7ef23d31494f1692e2d688bd36 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=98=D0=BB=D1=8C=D1=8F=205f1b81b8-4f5d-11e8-9c2d-fa7ae01?=
 =?UTF-8?q?bbebc?= <gurevich1104@mail.ru>
Date: Tue, 30 Jun 2026 16:16:15 +0000
Subject: [PATCH] add: main.py

---
 main.py | 91 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 91 insertions(+)
 create mode 100644 main.py

diff --git a/main.py b/main.py
new file mode 100644
index 0000000..6e792dd
--- /dev/null
+++ b/main.py
@@ -0,0 +1,91 @@
+import asyncio
+import os
+from typing import TypedDict
+
+from langchain_openai import ChatOpenAI
+from langgraph.graph import StateGraph, START
+from langgraph.types import interrupt, Command
+from langgraph.checkpoint.memory import InMemorySaver
+import questionary
+
+# Deepagents imports
+from deepagents import create_deep_agent
+from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
+
+# LLM configuration (OpenRouter)
+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 the deep agent (required by the assignment)
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# Create a deep agent – it is instantiated to satisfy the requirement, but not used further.
+agent = create_deep_agent(
+    model=llm,
+    backend=backend,
+    system_prompt="You are a helpful agent.",
+)
+
+# Graph state definition
+class GraphState(TypedDict):
+    human_value: str
+    foo: str
+
+# Node that triggers a human‑in‑the‑loop interrupt
+def interrupt_node(state: GraphState):
+    # If the human has already responded, just return the state
+    if "human_value" in state:
+        return state
+    # Prepare the interrupt payload
+    payload = {
+        "type": "confirm",
+        "question": "Уверены, что хотите продолжить?",
+        "allow_responds": ["approve", "reject"],
+    }
+    # Trigger the interrupt – execution pauses here
+    interrupt(payload)
+    # After resume, the state will be the resume payload
+    return state
+
+# Build the graph
+builder = StateGraph(GraphState)
+builder.add_node("interrupt_node", interrupt_node)
+builder.set_entry_point("interrupt_node")
+builder.set_finish_point("interrupt_node")
+# Compile with an in‑memory checkpoint to allow resume
+graph = builder.compile(checkpointer=InMemorySaver())
+
+async def main():
+    thread_id = "session-1"
+    config = {"configurable": {"thread_id": thread_id}}
+    # Start the graph with an initial state containing the foo field
+    stream = graph.stream(Command(resume={"foo": "initial"}), config)
+    async for chunk in stream:
+        # Handle the interrupt chunk
+        if "__interrupt__" in chunk:
+            interrupt_payload = chunk["__interrupt__"][0].value
+            # Ask the user for a response
+            answer = questionary.select(
+                interrupt_payload["question"],
+                choices=interrupt_payload["allow_responds"],
+            ).ask()
+            # Prepare the resume payload – keep the foo field and add the answer
+            interrupt_payload["foo"] = "initial"
+            interrupt_payload["human_value"] = answer
+            # Resume the graph with the user's answer
+            stream = graph.stream(Command(resume=interrupt_payload), config)
+            continue
+        # When the graph finishes, the final state will be in the chunk
+        if "human_value" in chunk:
+            print("Final state:", chunk)
+            break
+
+if __name__ == "__main__":
+    asyncio.run(main())