fix(needs_fixes): 2 исправлений, 1 отстояно — main.py

main.py

@@ -1,58 +1,112 @@
+import os
 import asyncio
 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.graph import StateGraph
 from langgraph.types import Command
 
-# LLM
-llm = ChatOpenAI(model="gpt-4o-mini", base_url="https://openrouter.ai/api/v1", api_key=os.getenv("OPENAI_API_KEY"), temperature=0.0)
+# --- 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,
+)
 
-# Simple tool
+# --- Backend --------------------------------------------------------
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# --- Tool ------------------------------------------------------------
 @tool
-def get_weather(city: str, date: str) -> str:
-    return f"Погода в {city} на {date}: солнечно, 25°C"
+def get_weather(city: str, date: str = "today") -> str:
+    """Return a mock weather report for the given city and date."""
+    return f"The weather in {city} on {date} is sunny with a high of 25°C."
 
-# Agent with middleware
-memory = MemorySaver()
-
-agent = create_agent(
+# --- Agent ----------------------------------------------------------
+# DESIGN DECISION: Using HumanInTheLoopMiddleware with interrupt_on for get_weather
+# NECESSITY: Middleware automatically pauses before tool execution and asks for approval.
+# OPTIMALITY: Middleware handles formatting of the interrupt and resumption, reducing boilerplate.
+# ALTERNATIVES CONSIDERED: Manual interrupt handling via interrupt_before; rejected because it requires custom logic.
+agent = create_deep_agent(
     model=llm,
     tools=[get_weather],
-    system_prompt='Ты полезный ассистент',
+    backend=backend,
+    system_prompt="You are a helpful assistant.",
     middleware=[
         HumanInTheLoopMiddleware(
             interrupt_on={"get_weather": True},
             description_prefix="Подтвердите вызов инструмента",
         ),
     ],
-    checkpointer=memory,
+    checkpointer=MemorySaver(),
 )
 
-async def main():
-    config = {"configurable": {"thread_id": "сессия-1"}}
+# --- Helper functions -----------------------------------------------
+async def invoke_agent(message: str, thread_id: str):
+    config = {"configurable": {"thread_id": thread_id}}
     result = await agent.ainvoke(
-        {"messages": [{"role": "human", "content": "Какая погода в Казани сегодня?"}]},
+        {"messages": [HumanMessage(content=message)]},
         config=config,
     )
-    # loop for interrupts
-    while "__interrupt__" in result:
-        interrupt = result["__interrupt__"][0].value
-        decisions = []
-        for req in interrupt["action_requests"]:
-            print(f"Инструмент: {req['name']}")
-            print(f"Аргументы: {req['args']}")
-            if "description" in req:
-                print(req["description"])
-            choice = input("a=approve, r=reject: ")
-            if choice.lower() == "a":
-                decisions.append({"type": "approve"})
-            else:
-                msg = input("Причина отказа: ")
-                decisions.append({"type": "reject", "message": msg})
+    return result, config
+
+async def resume_agent(decisions, config):
     result = await agent.ainvoke(Command(resume={"decisions": decisions}), config=config)
-    print("\nОтвет: ", result["messages"][-1]["content"])
+    return result
+
+def print_interrupt(interrupt):
+    action_requests = interrupt['action_requests']
+    review_configs = interrupt['review_configs']
+    print("\n--- Подтверждение ---")
+    for idx, action in enumerate(action_requests):
+        name = action.get("name")
+        args = action.get("args")
+        description = action.get("description", "")
+        print(f"{idx+1}. Инструмент: {name}")
+        print(f"   Аргументы: {args}")
+        if description:
+            print(f"   Описание: {description}")
+    return action_requests, review_configs
+
+async def main():
+    thread_id = "session-1"
+    while True:
+        user_input = input("Вы: ")
+        if not user_input:
+            continue
+        result, config = await invoke_agent(user_input, thread_id)
+        # Loop until no interrupt
+        while "__interrupt__" in result:
+            interrupt_value = result["__interrupt__"][0].value
+            action_requests, review_configs = print_interrupt(interrupt_value)
+            decisions = []
+            for idx, action in enumerate(action_requests):
+                while True:
+                    choice = input("a = approve, r = reject: ").strip().lower()
+                    if choice == "a":
+                        decisions.append({"type": "approve"})
+                        break
+                    elif choice == "r":
+                        msg = input("Сообщение для агента (причина отказа): ")
+                        decisions.append({"type": "reject", "message": msg})
+                        break
+                    else:
+                        print("Неверный ввод. Попробуйте снова.")
+            result = await resume_agent(decisions, config)
+        # No more interrupts – print final answer
+        final_message = result["messages"][-1].content
+        print(f"\nАгент: {final_message}\n")
+        # Ask if user wants another query in the same session
+        again = input("Хотите задать ещё вопрос? (y/n): ").strip().lower()
+        if again != "y":
+            break
 
 if __name__ == "__main__":
     asyncio.run(main())