Human‑in‑the‑Loop Agent with LangGraph

This repository contains a minimal example of a Human‑in‑the‑Loop (HITL) agent built on top of LangGraph.
The agent pauses whenever it needs to call an external tool, presents the tool output to the user and waits for a decision (approve or reject). After the decision is made the conversation continues automatically.

⚠️ Prerequisites – The example uses OpenAI‑compatible APIs.
Make sure you have an API key set in the environment variable OPENAI_API_KEY.

📦 Installation

# 1️⃣ Clone the repo (or copy solution.py into a new folder)
git clone https://github.com/your-username/hitl-langgraph.git
cd hitl-langgraph

# 2️⃣ Create and activate a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate   # Windows: .\.venv\Scripts\activate

# 3️⃣ Install dependencies
pip install --upgrade pip
pip install langchain-openai langgraph langchain-tools

Tip

– If you want to use a different LLM (e.g., Anthropic, Gemini), replace the ChatOpenAI import with the appropriate wrapper and adjust the model name.

🚀 Running the Agent

The main logic is in solution.py.
Run it directly:

python solution.py

What Happens?

The agent starts a conversation.
When it decides to call the get_weather tool, the execution pauses.
The tool output (e.g., "Погода в Москва на 2024-05-28: солнечно 25°C.") is printed to the console.
You are prompted to type approve or reject:
- approve: the agent resumes with the tool result as normal input.
- reject: the agent receives a ToolMessage indicating rejection and can decide what to do next.

🔧 Example Interaction

$ python solution.py
Agent: Какую погоду вы хотите узнать?
User: Москва на 2024-05-28
Agent (calling tool): get_weather(city='Москва', date='2024-05-28')
Tool output: Погода в Москва на 2024-05-28: солнечно 25°C.
Please type 'approve' or 'reject': approve
Agent: Спасибо! Как ещё могу помочь?

If you type reject, the agent will receive a rejection message and can, for example, ask for clarification.

📁 Project Structure

File	Purpose
`solution.py`	Full implementation of the HITL agent.
`README.md`	This documentation file.

🛠️ Customization

Add more tools – Decorate any function with @tool and add it to the tools=[...] list.
Change prompt – Edit system_prompt in create_react_agent.
Persist memory – Replace MemorySaver() with a file‑based or database checkpoint if you need persistence across runs.

README.md Unescape Escape