December 2024 Summaries

The text explores the concept of AI agents that autonomously create and execute their own tools by writing code, rather than relying on predefined actions or LLM-specific tooling. Using a demo agent built on Anthropic's Claude 3.5 Sonnet model, the article illustrates how an agent can interact with a known API, such as Stripe, to perform tasks like listing customers by email, updating customer details, adding payment cards, and charging customers. The agent starts with a basic toolset to request user input, show options, and create new tools, and it progressively develops more sophisticated capabilities by generating code in response to user requests. The demonstration emphasizes the potential for agents to bootstrap their skills dynamically and highlights the possibility of enabling agents to modify their tools for continuous improvement, akin to the Skill Library in the Voyager agent. The discussion concludes by inviting readers to engage further on the topic through a Discord community for ongoing exploration and development.

The Riza Tools API has been launched, extending the capabilities of the existing Code Interpreter API by allowing users to save and execute functions on demand, with added support for structured inputs. This API is useful for developers building AI agents, enabling them to deploy and invoke user-defined tools or even allowing AI agents to create their own tools. A step-by-step guide is provided for creating, executing, and managing tools through the Riza Dashboard, which supports Python, JavaScript, or TypeScript functions. The API's integration with popular LLMs, such as OpenAI's Function Calling API, is highlighted, showcasing seamless tool execution and interaction. The API also includes a Secrets API for secure management of secrets during tool execution. Users are encouraged to explore the API for free and engage with the community to share their creations.