Human-in-the-Loop через middleware: README.md

2026-05-27 10:10:24 +00:00
parent 9e5eff37c7
commit 905800cdb2
1 changed files with 160 additions and 0 deletions
@@ -0,0 +1,160 @@
 # Human‑in‑the‑Loop Middleware Demo  
 This repository contains a minimal LangChain/LangGraph example that demonstrates how to pause an agent whenever it wants to call a tool and ask the user for approval (`approve` / `reject`).  
 The pausing logic is handled by **`HumanInTheLoopMiddleware`**, which automatically generates a prompt, receives the user’s decision, and resumes execution via a `Command(resume={…})`.
 > **Why this matters** – In many real‑world scenarios an LLM should not act autonomously. By inserting a human checkpoint you can keep control over every tool call, ensuring safety, compliance or simply giving the user a chance to correct mistakes.
 ---
 ## 📦 Installation
 ```bash
 # 1️⃣ Clone the repo
 git clone https://github.com/your‑org/human‑in‑the‑loop-demo.git
 cd human‑in‑the‑loop-demo
 # 2️⃣ Create a virtual environment (recommended)
 python -m venv .venv
 source .venv/bin/activate   # Windows: .venv\Scripts\activate
 # 3️⃣ Install dependencies
 pip install -r requirements.txt
 ```
 > **Requirements**  
 > * Python ≥ 3.10  
 > * `langchain` (>=0.2)  
 > * `langgraph` (>=0.1)  
 > * `openai` or any LLM provider you prefer  
 The `requirements.txt` file contains the exact versions used for this demo.
 ---
 ## 📁 Project Structure
 ```
 .
 ├── agent.py          # Agent definition with HumanInTheLoopMiddleware
 ├── main.py           # CLI entry point – runs the agent interactively
 ├── tools.py          # Example tool(s) (e.g., get_weather)
 └── README.md         # This file
 ```
 ---
 ## 🚀 Running the Demo
 ### 1️⃣ Start the Agent
 ```bash
 python main.py
 ```
 You will see a prompt like:
 ```
 Assistant: What would you like to do?
 User: Tell me the weather in London.
 Assistant: (Thinking...) 
 ```
 When the agent decides to call `get_weather`, it pauses and prints:
 ```
 Human-in-the-loop checkpoint:
 The assistant wants to execute tool 'get_weather' with arguments {'location': 'London'}.
 Please type one of the following decisions: approve / reject
 ```
 Type **`approve`** to let the tool run, or **`reject`** to cancel it.  
 After your decision, the agent continues:
 ```
 Assistant: The weather in London is 18°C and sunny.
 ```
 ### 2️⃣ Using a Different Tool
 If you want to test another tool (e.g., `get_time`), add it to `tools.py`, import it in `agent.py`, and adjust the middleware configuration accordingly.
 ---
 ## 📚 Example Usage
 ```python
 # main.py
 from agent import agent
 def run():
    print("Welcome! Type 'exit' to quit.")
    while True:
        user_input = input("\nUser: ")
        if user_input.lower() == "exit":
            break
        response = agent.invoke({"input": user_input})
        print(f"Assistant: {response['output']}")
 if __name__ == "__main__":
    run()
 ```
 ```python
 # agent.py
 from langchain.agents import create_agent
 from langchain.agents.middleware import HumanInTheLoopMiddleware
 from langgraph.checkpoint.memory import MemorySaver
 from tools import get_weather  # <-- your tool(s)
 memory = MemorySaver()
 agent = create_agent(
    model="gpt-4o-mini",          # or any LLM you have access to
    tools=[get_weather],
    system_prompt="You are a helpful assistant.",
    middleware=[
        HumanInTheLoopMiddleware(
            interrupt_on={"get_weather": True},
            description_prefix="Please confirm the tool call:",
        ),
    ],
    checkpointer=memory,
 )
 ```
 ```python
 # tools.py
 from langchain.tools import BaseTool
 class GetWeather(BaseTool):
    name = "get_weather"
    description = "Returns current weather for a location."
    args_schema = ...  # define your schema here
    def _run(self, location: str) -> str:
        # Dummy implementation – replace with real API call
        return f"The weather in {location} is 18°C and sunny."
 get_weather = GetWeather()
 ```
 ---
 ## 🔧 Customization Tips
 | Feature | How to change |
 |---------|---------------|
 | **Allowed decisions** | `interrupt_on={"get_weather": {"allowed_decisions": ["approve", "reject"]}}` |
 | **Prompt prefix** | Change `description_prefix` in the middleware. |
 | **Tool list** | Add or remove tools in the `tools=[...]` array. |
 | **LLM model** | Pass a different model name or a custom LLM instance to `create_agent`. |
 ---
 ## 📜 License
 This project is licensed under the MIT License – see the [LICENSE](LICENSE) file for details.
 ---