Agents with Llama 3 and Custom Tools
Can Open LLMs be used to build AI agents that analyze data?
In our previous discussion (opens in a new tab), we've explored the potential of agents to power AI-driven applications. Today, we're delving deeper, leveraging Open Large Language Models—specifically Llama 3—through the Groq API. Our goal? To assemble a team of AI agents tasked with analyzing news trends to predict cryptocurrency prices, and we'll also be developing custom tools to boost these agents' capabilities.
One intriguing question we'll tackle is whether these agents, when coordinated through an Open LLM like Llama 3, can collaborate effectively and deliver reliable predictions, compared to using a more specialized model like GPT-4 Turbo. This comparison will not only shed light on the functionality and efficiency of different AI models in practical applications but also give us insights into the dynamics of AI teamwork in complex tasks.
Will the agents be able to collaborate effectively and produce accurate predictions using an Open LLM instead of GPT-4 Turbo? Let's find out!
Tutorial Goals
In this tutorial you will:
- Use Open LLM (Llama 3) via the Groq API to build agents
- Create custom tools for your agents to use
- Build a hierarchy of tasks to write a cryptocurrency report