prakticheskoe-zadanie-3-pamyat-i-podtver/README.md

LangGraph Agent with Memory and Tool Confirmation

This project demonstrates a simple conversational agent built with LangGraph that:

• Remembers the conversation history across turns using an in‑memory checkpoint.
• Pauses before invoking any tool, asking the user for confirmation.
• Uses the Rich library for pretty console output.

Prerequisites

• Python 3.10+
• An OpenAI API key (set as the OPENAI_API_KEY environment variable).

Installation

# Clone the repository (or copy the files)
git clone https://github.com/yourusername/langgraph-agent.git
cd langgraph-agent

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

# Install dependencies
pip install -r requirements.txt

Usage

python src/main.py

You will see a prompt:

Start chat. Type 'exit' to quit.
You:

Type any message. If the agent decides to use a tool (e.g., the echo tool), it will pause and ask:

Agent wants to call tool: echo({"text":"Hello"})
Разрешить? (Y/n):

• Type Y or press Enter to allow the tool to run.
• Type n to cancel the tool call.

The conversation history is preserved across turns, so the agent can refer back to earlier messages.

Customizing

• Tools: Add more tools by defining functions decorated with @tool from langchain.tools.
• Memory: Replace MemorySaver() with a persistent checkpoint (e.g., RedisSaver) for long‑term storage.
• Prompt: Modify the system_prompt in create_agent to change the agent’s behavior.

License

MIT License