Agno
Build multi-modal agents in plain Python — text, image, audio, and video inputs handled natively. Agno's tool library and memory system handle the infrastructure.
Agno — the verdict: Python developers building agents that need to reason over images, audio, and video, not just text Agno's real differentiator is multi-modal by default. Pricing: Open source / Free (Agno Cloud in beta). Last reviewed: August 2026.
Best For
Python developers building agents that need to reason over images, audio, and video, not just text
Standout Feature
Multi-modal by default, no special handling required for non-text inputs, unlike most agent frameworks
Verdict
A genuinely readable, Pythonic way to build multi-modal agents, there's no TypeScript SDK if that's your stack.
Alternatives
Overview
Agno (formerly phidata) is a Python framework for building multi-modal AI agents that can reason over text, images, audio, and video with native tool use and memory. Agents are defined in plain Python classes — no DSL, no YAML — and Agno handles the inference routing, tool execution loop, and session state. Ships with 30+ built-in tools (web search, database queries, file operations) and pluggable memory backends.
Our Take
Agno's real differentiator is multi-modal by default. Most agent frameworks treat image, audio, and video inputs as bolt-ons requiring special handling. Agno routes them natively through the same Python class structure you'd use for text, which matters for developers building agents that need to reason over mixed input types without writing custom middleware. The Pythonic API is genuinely readable, and the open-source core gives full control over deployment. The constraint is clear: Python only. If your team works in TypeScript, there's no SDK here, and no workaround that changes that.
Key Features
- Multi-modal agents with native text, image, audio, and video reasoning
- Plain Python class definitions — no framework-specific DSL
- 30+ built-in tools: web search, SQL, file ops, APIs
- Pluggable memory backends including PostgreSQL, MongoDB, and SQLite
- Agent Teams for orchestrating multiple specialized sub-agents
- Structured output support via Pydantic models
- • Multi-modal by default — no special handling for image or audio inputs
- • Pythonic API makes agents readable to anyone who knows Python
- • Built-in tool library means less boilerplate for common tasks
- • Python-only — no TypeScript SDK unlike some competitors
- • Cloud observability platform is still early-stage
- • Less community content than LangChain or CrewAI at the same maturity
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