Agno

AgnoSince 2025-10

Agno (formerly Phidata) is a lightweight, ultra-fast Python framework engineered for building production-grade autonomous multi-agent systems with native memory, knowledge retrieval, and multimodal reasoning capabilities. It is designed to replace bloated agent frameworks with a pure, pythonic developer experience. Agno agents operate up to 10x faster than legacy orchestration libraries by eliminating unnecessary abstractions. With built-in support for vector databases (PgVector, Qdrant, Pinecone), structured output schemas, and agent-to-agent delegating protocols, developers can build complex autonomous assistants with under 20 lines of clean code.

The framework includes first-class multimodal tools allowing agents to analyze images, process video streams, execute code in secure sandboxes, and query SQL databases. Agno agents natively persist session state and user memory in PostgreSQL, making stateful conversations effortless across web sessions. Agno is fully open-source with extensive documentation, offering enterprise-ready middleware for authentication, telemetry, and rate limiting.

CopilotKitSince 2024-03

CopilotKit is an open-source framework designed to help frontend developers build and embed contextual AI copilots and autonomous agents directly inside React and Next.js applications. Instead of building isolated chatbot sidebars that have no awareness of your application's state, CopilotKit connects the LLM directly to your frontend components, state stores, and backend APIs. With CopilotKit, applications gain two-way interaction with AI: users can ask questions in natural language, and the AI agent can read current component state, trigger actions across the UI (such as updating tables, filtering views, or submitting forms), and stream live generative UI widgets directly into the workspace. It natively supports popular LLMs, LangChain, and LangGraph multi-agent backends.

CopilotKit architecture consists of frontend React hooks and UI components (`useCopilotAction`, `useCopilotReadable`, `<CopilotSidebar />`) paired with an extensible runtime backend. The frontend hooks serialize active component state into dynamic LLM prompts and register client-side actions that can be triggered deterministically via function calling. The backend runtime acts as an orchestration proxy that can route execution to OpenAI, Anthropic, Ollama, or self-hosted LangGraph agent workflows. It handles streaming responses, structured schema validation, error recovery, and permission boundaries so that user-authorized actions cannot inadvertently alter unintended data. CopilotKit also provides built-in text-editing copilots and auto-suggest inputs for rich document manipulation.