LangGraph Agent with Conversation Memory and User Confirmation

Installation

python -m venv .venv
source .venv/bin/activate   # on Windows use `.venv\Scripts\activate`
pip install -r requirements.txt

Environment Variables

The agent uses the default OpenAI endpoint via langchain. If you want to override, set:

• OPENAI_API_KEY – your OpenAI API key.
• OPENAI_BASE_URL – custom base URL (e.g., for local Ollama).

Running the Agent

python agent.py

The script starts with an empty conversation history. The graph will:

1. Retrieve memory (currently just echoes the existing history).
2. Invoke a placeholder agent that would normally process the conversation.
3. Prompt you to confirm each tool call via Rich console output.
4. Continue execution after confirmation.

Extending

Replace agent_node with real LangChain logic, add tools, and integrate an actual LLM model as needed.