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Pydantic AI vs Agno

Agno is a Python agent framework that optimizes for breadth: a very large tool catalogue, teams, step workflows, and AgentOS to run and watch them. Pydantic AI gives you that breadth on a typed core with strict Pydantic validation: capabilities and the Harness SDK for the batteries, sub-agents for teams, pydantic-graph for workflows, and Pydantic Logfire to run and watch them.

Pydantic AI is one part of a stack: the Harness SDK for capabilities and complete agents, Pydantic Evals, Pydantic Graph, Pydantic Logfire for observability, and Pydantic itself for validation. The tables below cover the whole of it.

Framework

AgnoPydantic AI and Harness SDK
LanguagePythonPython
LicenseApache-2.0MIT
Model providersManyMany
ExtensibilityTools, toolkitsCapabilities and toolsets; 50+ with the Harness SDK
HarnessesBuild your ownBuilt-in Coder and Researcher, or compose your own
ObservabilityOpenTelemetryOpenTelemetry, including Pydantic Logfire
Durable executionYes5+ integrations
InterfacesAG-UI, A2A, chat platformsCLI, web chat, AG-UI, Vercel AI, ACP (experimental)
Realtime voiceNoRealtime
EvalsYesPydantic Evals
Image generationYesImage Generation

Features

AgnoPydantic AI and Harness SDK
Multi-agentYesSubagents, delegation, or pydantic-graph
PlanningTeams onlyPlanning
SkillsYesSkills
MemoryYesMemory
CompactionHistory window, session summariesCompaction
GuardrailsYesGuardrails
Code sandboxesYesExecution environments
Browser useYesWeb & research