README.md

LangGraph A2A Conversational Agent

This project demonstrates an Agent-to-Agent (A2A) conversation using LangGraph with the A2A protocol.

Setup

1. Create a virtual environment:

   python -m venv venv

2. Activate the virtual environment:

   source venv/bin/activate  # On macOS/Linux
   # or
   venv\Scripts\activate  # On Windows

3. Copy the environment example file and configure:

   cp .env.example .env

   Edit .env and add your required variables (e.g., OPENAI_API_KEY).

4. Install dependencies:

   pip install -r python/requirements.txt

Running the Agents

1. Start the first agent server:

   cd python
   langgraph dev --port 2024

   Copy the assistant_id from the output.

2. In another terminal, start the second agent server:

   cd python
   langgraph dev --port 2025

   Copy the assistant_id from this output as well.

3. Configure the assistant IDs: Add the following to your .env file:

   AGENT_A_ID=<assistant_id_from_port_2024>
   AGENT_B_ID=<assistant_id_from_port_2025>
   

4. Run the conversation simulation:

   python a2a_conversation.py

This will simulate a conversation between the two agents, with each agent responding to the other's messages.