- Step1: Clone the repository from GitHub and navigate into the project directory.
- Step2: Install dependencies using pip and configure your Python environment.
- Step3: Define or import custom tools with standardized interfaces for your agent.
- Step4: Configure the agent by specifying LLM provider, memory backend, and toolset.
- Step5: Use the provided AgentExecutor class to initialize and run your AI agent.
- Step6: Test and iterate on prompts, memory settings, and tools to refine agent behavior.
- Step7: Extend the framework by adding new tools, templates, or integrating additional APIs.