Agno

Agno is an agentic framework for building LLM applications that can be used with Copilotkit. Agno Agents allow developers to combine and coordinate coding tasks efficiently, providing a robust framework for building sophisticated AI automations.

CoAgents and Agno

How do CoAgents extend Agno? Let's read about the concept of Flows to understand.

Flows allow you to create structured, event-driven workflows. They provide a seamless way to connect multiple tasks, manage state, and control the flow of execution in your AI applications.

Let's break down some key terms and understand how they relate to and are implemented by CoAgents.

• ** manage state**: CoAgents have bi-directional state sharing with the agent and UI. This allows for the agent to remember information from previous messages and the UI to update the agent with new information. Read more about how state sharing works here.
• Multi-actor: CoAgents allow for multiple agents to interact with each other. Copilotkit acts as the "ground-truth" when transitioning between agents. Read more about how multi-actor workflows work here and how messages are managed here.
• LLMs: CoAgents use large language models to generate responses. This is useful for building applications that need to generate natural language responses.

Some additional functionality not mentioned here is:

• Human in the loop: CoAgents enabled human review and approval of generated responses. Read more about how this works here.
• Tool calling: Tool calling is a fundamental building block for agentic workflows. They allow for greater control over what the agent can do and can be used to interact with external systems. CoAgents allow you to easily render in-progress tool calls in the UI so your users know what's happening. Read more about streaming tool calls here.

Building with Python

You can build Agno applications using Python. Check out the Agno docs for more information.