From d7ffa797c46388828e23fe52c18d4cb4ccad25be Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=9A=D0=B8=D1=80=D0=B8=D0=BB=D0=BB=20=D0=9A=D1=83=D1=82?=
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 <kirillkutlahmetov10@gmail.com>
Date: Tue, 26 May 2026 13:46:58 +0000
Subject: [PATCH] add agent.py

---
 agent.py | 78 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 78 insertions(+)
 create mode 100644 agent.py

diff --git a/agent.py b/agent.py
new file mode 100644
index 0000000..947586a
--- /dev/null
+++ b/agent.py
@@ -0,0 +1,78 @@
+"""
+Agent configuration for the Human‑in‑the‑Loop example.
+
+The agent uses :class:`langchain.agents.middleware.HumanInTheLoopMiddleware` to pause whenever a tool is called.  The middleware automatically builds an interrupt payload that contains the name of the tool, its arguments and the allowed decisions (approve / reject / edit).  The caller can then resume execution by sending a ``Command`` with the chosen decisions.
+"""
+import os
+from langchain_openai import ChatOpenAI
+from langchain.agents import create_agent
+from langchain.agents.middleware import HumanInTheLoopMiddleware
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.types import Command
+
+# LLM – BroJS
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
+    api_key=os.getenv("JOURNAL_MCP_PAT"),
+    temperature=0.5,
+)
+
+# Tool import – defined in tools.py
+from tools import get_weather
+
+memory = MemorySaver()
+agent = create_agent(
+    llm=llm,
+    tools=[get_weather],
+    system_prompt="Ты полезный ассистент.",
+    middleware=[
+        HumanInTheLoopMiddleware(
+            interrupt_on={"get_weather": True},
+            description_prefix="Подтвердите вызов инструмента",
+        ),
+    ],
+    checkpointer=memory,
+)
+
+# Helper to run a single user query with HIL loop
+
+def run_query(user_msg: str, thread_id: str = "session-1"):
+    config = {"configurable": {"thread_id": thread_id}}
+    result = agent.invoke({"messages": [{"role": "human", "content": user_msg}]}, config)
+
+    # Loop while the agent is paused for a decision
+    while "__interrupt__" in result:
+        interrupt_value = result["__interrupt__"][0].value
+        action_requests = interrupt_value.get("action_requests", [])
+        decisions = []
+        print("\n--- Подтверждение вызова инструмента ---")
+        for idx, act in enumerate(action_requests):
+            name = act["name"]
+            args = act.get("args", {})
+            desc = act.get("description", "")
+            print(f"{idx+1}. Инструмент: {name}")
+            print(f"   Аргументы: {args}")
+            if desc:
+                print(f"   Описание: {desc}")
+        # Simple approve/reject per action
+        for idx, act in enumerate(action_requests):
+            while True:
+                choice = input("a=approve, r=reject (e=edit не поддерживается): ").strip().lower()
+                if choice == "a":
+                    decisions.append({"type": "approve"})
+                    break
+                elif choice == "r":
+                    msg = input("Причина отказа: ")
+                    decisions.append({"type": "reject", "message": msg})
+                    break
+        # Resume execution with collected decisions
+        result = agent.invoke(Command(resume={"decisions": decisions}), config)
+    # Final answer
+    final_msg = result["messages"][-1].content
+    print("\nОтвет агента:")
+    print(final_msg)
+    return final_msg
+
+if __name__ == "__main__":
+    run_query("Какая погода в Казани сегодня?")