dz/solutions/69a86305c46fd26feae6bcaa_Human-in-the-Loop_через_middleware

Human‑in‑the‑Loop Agent via Middleware

This repository contains a minimal example of an LLM agent that pauses every time it wants to call an external tool and asks the user for confirmation (approve or reject).
The pause is implemented with LangChain’s built‑in HumanInTheLoopMiddleware, which automatically generates the prompt, captures the user input, and resumes execution via a Command.

Why use middleware?
Unlike the interrupt_before=['tools'] approach that requires manual handling of interruptions, the middleware handles everything internally: it creates the confirmation request, processes the response, and resumes the agent with the chosen decision.

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📦 Installation

# Create a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate

# Install required packages
pip install langchain langgraph openai rich

OpenAI API key
The example uses an OpenAI model. Set your key in the environment:

export OPENAI_API_KEY="sk-…"

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📁 Project Structure

File	Purpose
solution.py	Main script that creates the agent, defines a simple tool (get_weather), and runs an interactive loop.

The repository contains only one Python file for clarity.

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🚀 Running the Example

python solution.py

You will see something like:

User: What's the weather in London?
Agent: (pauses) Подтвердите вызов инструмента get_weather
  - approve
  - reject
Your choice: 

Type approve to let the agent call the tool, or reject to skip it.
After your decision, the agent continues its reasoning and eventually returns a final answer.

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🛠️ Customizing

Changing the Tool

Replace the get_weather function with any other LangChain tool:

@tool
def get_time() -> str:
    """Return current UTC time."""
    return datetime.utcnow().isoformat()

Add it to the tools list when creating the agent.

Adjusting Middleware Settings

• Interrupt on specific decisions

  interrupt_on={
      "get_weather": {"allowed_decisions": ["approve", "reject"]}  # no edit option
  }
  

• Custom prompt prefix

  description_prefix="Please confirm the tool call:"
  

Using a Different LLM

Swap llm for any LangChain-compatible model (e.g., GPT‑4o, Claude, etc.):

from langchain_openai import ChatOpenAI
llm = ChatOpenAI(model_name="gpt-4o-mini")

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📖 Example Interaction

User: Tell me the weather in Paris.
Agent: (pauses) Подтвердите вызов инструмента get_weather
  - approve
  - reject
Your choice: approve
Agent: The current temperature in Paris is 18°C with clear skies.
Final answer: It’s sunny and mild in Paris today.

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📜 License

This project is provided under the MIT license. Feel free to adapt it for your own experiments.

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