README.md

LangGraph Multi-Agent Example (Multiple Agents)

This example demonstrates how to use LaunchDarkly's AI Config with LangGraph to orchestrate multiple agents in a code review workflow.

Prerequisites

• Python 3.10 or higher
• Poetry installed
• A LaunchDarkly account and SDK key
• API keys for the providers you want to use

Setup

1. Create the following configs in your LaunchDarkly project. You can use different keys by setting the environment variables in your .env.

   • Create an AI Agent Config for code analysis. Default key: code-review-analyzer.
   • Create an AI Agent Config for documentation generation. Default key: code-review-documentation.

2. Create a .env file in this directory with the following variables:

   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
   LAUNCHDARKLY_ANALYZER_CONFIG_KEY=code-review-analyzer
   LAUNCHDARKLY_DOCUMENTATION_CONFIG_KEY=code-review-documentation
   

   Add the API keys for the providers you want to use:

   OPENAI_API_KEY=your-openai-api-key
   GOOGLE_API_KEY=your-google-api-key
   AWS_ACCESS_KEY_ID=your-access-key-id
   AWS_SECRET_ACCESS_KEY=your-secret-access-key
   

3. Install the required dependencies:

   poetry install

Run

poetry run agent-graph