Initial implementation of Human-in-the-Loop agent

main.py

@@ -1,105 +1,84 @@
-import os
+import json
-import asyncio
+from langchain.agents import create_agent
-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
 from langchain.agents.middleware import HumanInTheLoopMiddleware
 from langgraph.checkpoint.memory import MemorySaver
-from langgraph.types import Command
+from langchain_openai import ChatOpenAI
+from langchain.tools import tool
 
-# --- LLM initialization (OpenRouter) -------------------------------------------------
+# Define a simple get_weather tool
-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 setup -------------------------------------------------
-backend = CompositeBackend([
-    LocalShellBackend(workspace_dir="./workspace"),
-    FilesystemBackend(),
-])
-
-# --- Tool definition -------------------------------------------------
 @tool
-def get_weather(city: str, date: str) -> str:
+def get_weather(city: str, date: str = "today") -> str:
-    """Return a mock weather report for the given city and date."""
+    """Return a mock weather for the given city and date."""
-    # In a real scenario this would call an external API.
     return f"The weather in {city} on {date} is sunny with a high of 25°C."
 
-# --- Agent creation -------------------------------------------------
+# Initialize LLM (replace with your OpenRouter key if needed)
-agent = create_deep_agent(
+llm = ChatOpenAI(model="gpt-4o", temperature=0)
+
+memory = MemorySaver()
+
+agent = create_agent(
     model=llm,
     tools=[get_weather],
-    backend=backend,
+    system_prompt="Ты полезный ассистент",
-    system_prompt="You are a helpful assistant.",
     middleware=[
         HumanInTheLoopMiddleware(
-            interrupt_on={"get_weather": True},
+            interrupt_on={
+                "get_weather": True,
+            },
             description_prefix="Подтвердите вызов инструмента",
         ),
     ],
-    checkpointer=MemorySaver(),
+    checkpointer=memory,
 )
 
-# --- Helper functions -------------------------------------------------
+if __name__ == "__main__":
-async def prompt_user_for_decisions(action_requests, review_configs):
+    import sys
+    from langgraph.types import Command
+
+    # Simple CLI loop
+    thread_id = "session-1"
+    config = {"configurable": {"thread_id": thread_id}}
+
+    # Initial user message
+    user_msg = " ".join(sys.argv[1:]) or "Какая погода в Казани сегодня?"
+    result = agent.invoke({"messages": [{"role": "human", "content": user_msg}]}, config=config)
+
+    while "__interrupt__" in result:
+        interrupt = result["__interrupt__"][0].value
+        action_requests = interrupt["action_requests"]
+        review_configs = interrupt["review_configs"]
         decisions = []
         for idx, action in enumerate(action_requests):
             print(f"\n--- Подтверждение ---")
-        print(f"Инструмент: {action.get('name')}\n")
+            print(f"Инструмент: {action['name']}")
-        print(f"Аргументы: {action.get('args')}\n")
+            print(f"Аргументы: {action['args']}")
             if "description" in action:
-            print(f"Описание: {action['description']}\n")
+                print(f"Описание: {action['description']}")
-        allowed = review_configs[idx].get("allowed_decisions", ["approve", "reject", "edit"])
+            # Determine allowed decisions
-        prompt = f"a = approve, r = reject{', e = edit' if 'edit' in allowed else ''}: "
+            allowed = review_configs.get(action['name'], {}).get("allowed_decisions", ["approve", "reject", "edit"]) if isinstance(review_configs.get(action['name']), dict) else ["approve", "reject", "edit"]
+            # Simple input handling
             while True:
-            choice = input(prompt).strip().lower()
+                inp = input("a = approve, r = reject, e = edit: ").strip().lower()
-            if choice == "a" and "approve" in allowed:
+                if inp == "a" and "approve" in allowed:
                     decisions.append({"type": "approve"})
                     break
-            elif choice == "r" and "reject" in allowed:
+                if inp == "r" and "reject" in allowed:
-                msg = input("Сообщение для агента (причина отказа): ")
+                    msg = input("Введите причину отказа: ")
                     decisions.append({"type": "reject", "message": msg})
                     break
-            elif choice == "e" and "edit" in allowed:
+                if inp == "e" and "edit" in allowed:
-                # Simple edit: ask for new JSON args
+                    # For simplicity, ask for new args as JSON
-                new_args = input("Введите отредактированные аргументы в формате JSON: ")
+                    new_args = input("Введите новые аргументы в формате JSON: ")
                     try:
-                    import json
+                        new_args_dict = json.loads(new_args)
-                    edited = json.loads(new_args)
+                        decisions.append({"type": "edit", "edited_action": {"name": action['name'], "args": new_args_dict}})
-                    decisions.append({"type": "edit", "edited_action": {"name": action['name'], "args": edited}})
                         break
-                except json.JSONDecodeError:
+                    except Exception as exc:
-                    print("Неверный JSON. Попробуйте снова.")
+                        print("Неверный JSON, попробуйте снова.")
-            else:
+                print("Недопустимый ввод. Попробуйте снова.")
-                print("Неверный выбор. Попробуйте снова.")
+        # Resume
-    return decisions
+        result = agent.invoke(Command(resume={"decisions": decisions}), config=config)
-
-# --- Main interaction loop -------------------------------------------------
-async def main():
-    config = {"configurable": {"thread_id": "session-1"}}
-    # Initial user message
-    user_input = input("Вы: ")
-    result = await agent.ainvoke(
-        {"messages": [HumanMessage(content=user_input)]},
-        config,
-    )
-
-    # Process possible interrupts
-    while "__interrupt__" in result:
-        interrupt = result["__interrupt__"][0].value
-        action_requests = interrupt.get("action_requests", [])
-        review_configs = interrupt.get("review_configs", [])
-        decisions = await prompt_user_for_decisions(action_requests, review_configs)
-        result = await agent.ainvoke(Command(resume={"decisions": decisions}), config)
 
     # Final answer
-    final_message = result["messages"][-1].content
+    final_msg = result["messages"][-1]["content"]
-    print(f"\nАгент: {final_message}")
+    print("\nАгент: " + final_msg)
-
-if __name__ == "__main__":
-    asyncio.run(main())