I recently had the opportunity to explore Llama Index AI agents and was amazed by their capabilities. Unlike AI chatbots, which are primarily focused on conversation interfaces, AI agents offer task automation. This means that AI agents can interact with their environment using tools, while AI chatbots simply respond to queries.
One of the most impressive features of Llama Index is its ability to turn enterprise data into a production-ready language model application. It can load, index, query, and evaluate data all in one place. By combining this powerful tool with AI agents, we can create a truly autonomous system that can perform complex calculations and tasks.
To demonstrate this, I created a simple example that involves creating custom tools, assigning them to an AI agent, and creating a user interface. The custom tools I created include functions for addition, subtraction, multiplication, and division. These tools are necessary because language models like Llama 3 are not good at multiplication or division, but they excel at completing sentences and other language-based tasks.
Once the tools were created, I defined and initiated the AI agent using the react agent function. I then used the agent.chat function to ask the agent to perform a complex calculation. The agent was able to use the appropriate tools to perform the calculation and provide the correct answer.
Finally, I created a user interface using chain lit. This allowed me to create a chatbot-like interface that users can interact with. Behind the scenes, the AI agent is working to provide the correct answers to user queries.
Overall, I was impressed by the power and flexibility of Llama Index AI agents. By combining this tool with custom tools and a user interface, we can create truly autonomous systems that can perform complex tasks and calculations. I'm excited to continue exploring the possibilities of AI agents and can't wait to see what developers will create with this powerful technology.