- Step1: Clone the GPA-LM repository from GitHub.
- Step2: Install dependencies using pip and configure the Python environment.
- Step3: Set up API keys and model parameters in the configuration file.
- Step4: Choose or define custom plugins and tools.
- Step5: Run example scripts to test agent workflows.
- Step6: Customize planner and executor strategies for specific tasks.
- Step7: Deploy the agent pipeline and monitor execution logs.