1.5 KiB
integration-langgraph (LangGraph Integration)
This example demonstrates how to use LangGraph with Promptfoo, including a research agent setup, structured output, and red teaming or evaluation.
You can run this example with:
npx promptfoo@latest init --example integration-langgraph
cd integration-langgraph
Environment Variables
This example requires the following environment variables:
OPENAI_API_KEY– Your OpenAI API key (required by LangGraph to use ChatOpenAI)
You can set this in a .env file or directly in your environment.
Prerequisites
- Python 3.9-3.12 tested
- Node.js v22 LTS or newer
- OpenAI API access (for GPT-4o, GPT-4o-mini, and OpenAI's forthcoming o3 mini once released)
- An OpenAI API key
Install Python packages:
pip install -r requirements.txt
Or install individually:
pip install langgraph langchain langchain-openai python-dotenv
Install promptfoo CLI:
npm install -g promptfoo
Files
-
agent.py: Defines the LangGraph Research Agent, using a StateGraph that processes user queries and summarizes AI research trends. -
provider.py: Wraps the agent logic into a callable function for Promptfoo, exposing a call_api() handler. -
promptfooconfig.yaml: Configures Promptfoo to: -
Provide test prompts
-
Call the LangGraph provider
-
Check outputs using assertions
Run the evaluation:
npx promptfoo eval
Explore results in browser:
npx promptfoo view