Agno is an agent platform designed to build, deploy, and manage AI agents in production environments. It supports agents built using any framework or no-code UI, providing production-grade features like tracing, scheduling, and RBAC. Agno allows teams to automate diverse tasks from data labeling and document extraction to product copilots while maintaining data ownership.

The OpenAI Agents SDK provides a lightweight, Python-first framework for building agentic AI applications with built-in primitives for agents, tools, guardrails, and multi-agent coordination. It abstracts away common complexities like tool invocation, turn management, and state persistence, while offering customization. The SDK is designed for production-ready agent workflows that go beyond single LLM calls.

• +Productionizes agents built with any framework, offering flexibility in agent creation.
• +Provides robust production features for agents, including tracing, scheduling, role-based access control (RBAC), and audit trails.
• +Supports management of the entire agent development lifecycle using coding agents.
• +Offers native typesafety and multi-modal capabilities for various input/output modalities, including structured output.
• +Ensures data ownership by storing all session, memory, and trace data in the user's own database and cloud.
• +Enables auto-improvement of agents using production usage data via provided code mechanisms.

• +Provides a built-in agent loop handling tool invocation and result processing until task completion.
• +Offers a Python-first approach, using language features for orchestration without new abstractions.
• +Supports multi-agent coordination through 'Agents as tools' (Handoffs) for task delegation.
• +Includes 'Sandbox agents' for running specialists in isolated workspaces with resumable sessions.
• +Implements 'Guardrails' for parallel input validation and safety checks, enabling fail-fast behavior.
• +Generates automatic schemas for Python functions, enabling them as Pydantic-validated tools.
• +Features built-in tracing for visualizing, debugging, and monitoring workflows, with support for OpenAI evaluation and fine-tuning.
• +Enables building low-latency voice agents with `gpt-realtime-2` for real-time interactions and context management.

• −Introduces a higher-level runtime that adds overhead for simple, short-lived API calls where direct model response is the only goal.
• −Less control over core model loop, tool dispatch, and state handling when compared to direct use of the OpenAI Responses API.

Agno stores all session, memory, and trace data in the user's own database within their cloud environment.

The SDK provides 'Sessions' as a persistent memory layer to maintain working context within an agent loop and across turns.