From d4e551e277b81bd2c4b35a22145c2fdb290c3d24 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=A0=D0=B8=D0=BD=D0=B0=D1=80=20=D0=9C=D0=B8=D1=80=D0=B7?=
 =?UTF-8?q?=D0=B0=D0=B3=D0=B8=D1=82=D0=BE=D0=B2?= <mirzagitov03@mail.ru>
Date: Wed, 3 Jun 2026 10:15:57 +0000
Subject: [PATCH] Solution ready: update agent.py

---
 agent.py | 18 +++++-------------
 1 file changed, 5 insertions(+), 13 deletions(-)

diff --git a/agent.py b/agent.py
index 662f8cd..4fce2c4 100644
--- a/agent.py
+++ b/agent.py
@@ -1,14 +1,6 @@
-"""
-Human‑in‑the‑Loop agent with tool calling.
-
-This example demonstrates how to use LangChain's `HumanInTheLoopMiddleware` to pause the agent when a tool is about to be called, ask the user for approval, and then resume execution.
-
-The agent uses a simple `get_weather` tool that returns a hard‑coded weather string. In a real project you would replace it with an API call.
-
-Run:
-    python agent.py
-Make sure you have `OPENAI_API_KEY` set in your environment.
-"""
+# Human‑in‑the‑Loop (HITL) middleware example
+# interrupt decision types: approve, edit, reject, respond
+# respond decision can be used to supply a human reply as tool result
 
 import os
 from typing import List, Dict
@@ -17,7 +9,7 @@ from langchain_openai import ChatOpenAI
 from langchain.agents import create_agent
 from langchain.agents.middleware import HumanInTheLoopMiddleware
 from langchain.tools import BaseTool
-from langgraph.checkpoint.memory import InMemorySaver
+from langgraph.checkpoint.memory import MemorySaver
 from langgraph.types import Command
 
 # --- Tool ---------------------------------------------------------------
@@ -36,7 +28,7 @@ if not api_key:
 llm = ChatOpenAI(api_key=api_key, temperature=0.7)
 
 # --- Agent --------------------------------------------------------------
-memory = InMemorySaver()
+memory = MemorySaver()
 
 agent = create_agent(
     model=llm,