add main.py

main.py

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+"""
+Human‑in‑the‑Loop example using LangChain `HumanInTheLoopMiddleware`.
+
+This repository demonstrates how to pause an agent when a tool is about to be called, ask the user for approval (or rejection), and then resume execution.
+
+The script contains three independent examples:
+1. Simple weather query – single tool call.
+2. Multiple tool calls in one conversation – shows that the loop continues until all tools are approved.
+3. Rejection path – demonstrates how a rejected action is handled by the agent.
+
+Run with:
+    python -m venv .venv && source .venv/bin/activate
+    pip install -r requirements.txt
+    export JOURNAL_MCP_PAT=YOUR_BROJS_TOKEN
+    python main.py
+"""
+
+import os
+import json
+from typing import List, Dict
+
+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
+
+# ---------------------------------------------------------------------------
+# 1. LLM configuration – BroJS only
+# ---------------------------------------------------------------------------
+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=0.0,
+)
+
+# ---------------------------------------------------------------------------
+# 2. Simple tool – get_weather (mocked for demo purposes)
+# ---------------------------------------------------------------------------
+def get_weather(city: str, date: str = "today") -> str:
+    """Return a fabricated weather report.
+
+    Parameters
+    ----------
+    city: str
+        Name of the city.
+    date: str, optional
+        Date for which to fetch the forecast. Defaults to ``today``.
+    """
+    return f"The weather in {city} on {date} is sunny with a high of 25°C."
+
+# ---------------------------------------------------------------------------
+# 3. Agent construction – middleware pauses before calling get_weather
+# ---------------------------------------------------------------------------
+memory = MemorySaver()
+agent = create_agent(
+    model=llm,
+    tools=[get_weather],
+    system_prompt="You are a helpful assistant that can provide weather information.",
+    middleware=[
+        HumanInTheLoopMiddleware(
+            interrupt_on={"get_weather": True},  # allow approve / reject / edit
+            description_prefix="Please confirm the tool call:",
+        ),
+    ],
+    checkpointer=memory,
+)
+
+# ---------------------------------------------------------------------------
+# Helper: run a single turn with HIL loop
+# ---------------------------------------------------------------------------
+def run_turn(user_msg: str, thread_id: str) -> str:
+    """Run one user message through the agent.
+
+    The function handles all pauses caused by the middleware and asks the
+    user for approval or rejection.  It returns the final assistant reply.
+    """
+    config = {"configurable": {"thread_id": thread_id}}
+    result: Dict = agent.invoke({"messages": [{"role": "human", "content": user_msg}]}, config=config)
+
+    while "__interrupt__" in result:
+        interrupt_value = result["__interrupt__"][0].value
+        action_requests = interrupt_value.get("action_requests", [])
+        review_configs = interrupt_value.get("review_configs", {})
+
+        decisions: List[Dict] = []
+        for idx, act in enumerate(action_requests):
+            name = act.get("name")
+            args = act.get("args", {})
+            description = act.get("description", "")
+            allowed = review_configs.get(name, {}).get("allowed_decisions", ["approve", "reject", "edit"])
+
+            print(f"\n--- Tool call {idx + 1} ---")
+            print(f"Name: {name}")
+            print(f"Arguments: {json.dumps(args)}")
+            if description:
+                print(f"Description: {description}")
+            opts = ["a" for _ in allowed if "approve" in _]
+            opts += ["r" for _ in allowed if "reject" in _]
+            opts += ["e" for _ in allowed if "edit" in _]
+            opt_str = "/".join(opts)
+            choice = input(f"Choose {opt_str}: ").strip().lower()
+
+            if choice == "a":
+                decisions.append({"type": "approve"})
+            elif choice == "r":
+                msg = input("Reason for rejection: ")
+                decisions.append({"type": "reject", "message": msg})
+            elif choice == "e":
+                new_args_raw = input("Enter edited arguments as JSON: ")
+                try:
+                    new_args = json.loads(new_args_raw)
+                except Exception:
+                    print("Invalid JSON – falling back to original.")
+                    new_args = args
+                decisions.append({"type": "edit", "edited_action": {"name": name, "args": new_args}})
+            else:
+                print("Unrecognised choice – defaulting to reject.")
+                decisions.append({"type": "reject", "message": "User did not provide valid input."})
+
+        result = agent.invoke(Command(resume={"decisions": decisions}), config=config)
+
+    final_msg = result["messages"][-1].content
+    return final_msg
+
+# ---------------------------------------------------------------------------
+# Demo – three independent examples
+# ---------------------------------------------------------------------------
+if __name__ == "__main__":
+    print("=== Example 1: Simple weather query ===")
+    reply = run_turn("Какая погода в Казани сегодня?", thread_id="session-1")
+    print(f"Assistant: {reply}\n")
+
+    print("=== Example 2: Multiple tool calls in one conversation ===")
+    reply = run_turn(
+        "Сколько будет в Казани завтра и как погода в Москве сегодня?", thread_id="session-2"
+    )
+    print(f"Assistant: {reply}\n")
+
+    print("=== Example 3: Rejection path ===")
+    reply = run_turn("Погода в Лондоне на завтра, пожалуйста.", thread_id="session-3")
+    print(f"Assistant: {reply}\n")
+
+    print("All examples finished.\n")