This is a major release that introduces a completely new approach to building multi-agent systems. It also introduces the AgentOS, a runtime for agents. This is a major rewrite of the Agno library and introduces various new concepts and updates to the existing ones. Some of the major changes are:
  • Agents, Teams and Workflows are now fully stateless.
  • Knowledge is now a single solution that supports many forms of content.
  • Storage of sessions, memories, evals, etc. has been simplified

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General Changes

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Session & Run State

  • We have made significant changes to the innerworkings of Agent, Team and Workflow to make them completely stateless.
  • This means that agent_session, session_metrics, session_state, etc. should not be seen as stateful variables that would be updated during the course of a run, but rather as “defaults” for the agent if they can be set on initialisation.
  • CustomEvent is now supported and you can inherit from it to create your own custom events that can be yielded from your own tools. See the documentation for more details.

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Storage

  • Agent, Team, Workflow and the various evals now all support a single db parameter. This is to enable storage for the instance of that class. This is required for persistence of sessions, memories, metrics, etc.
  • storage and memory have been removed from Agent, Team and Workflow.

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Memory

  • With the above changes to storage, memory has been simplified.
  • memory has been removed from Agent and Team. Instead memory is enabled with enable_user_memories: bool (like before) and persisted in the db instance.
  • Changes to how memories are created can still be done by overriding the MemoryManager class on Agent or Team. E.g. Agent(memory_manager=MyMemoryManager()).
  • AgentMemory and TeamMemory have been removed.

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Knowledge

  • Knowledge has been completely reworked. See full details in the Knowledge section.
  • You now define a single Knowledge instance for all types of content. Files (PDF, CSV, etc.), URLs, and other.
  • The agent can still use your knowledge base to search for information at runtime. All existing RAG implementations are still supported.
  • Added full async support for embedding models and vector DBs. This has a significant impact on performance and is a major speed improvement when adding content to the knowledge base using knowledge.add_content_async(...).
  • AgentKnowledge and all other knowledge base classes have been removed.
  • Import locations for embedder, document, chunking, reranker and reader have been moved to agno.knowledge. See examples for more details.

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Tools updates

  • General:
    • Since Agents and Teams are now stateless, using attributes from the agent/team object inside a function will give you access to the attributes set on initialisation of that agent/team. E.g. agent.session_state should not be used, instead session_state can now be directly accessed and would have the “current” state of the session.
    • A new flow allows images, audio and video files generated during tool execution to be passed back in a FunctionExecutionResult object and this will ensure these artifacts are made available to the model and agent as needed.
  • All tools that handle media (e.g. image generation tools) now correctly add this generated media to the RunOutput, but also make it available for subsequent model calls.
  • The interface of almost all the toolkits have been updated for a more consistent experience around switching specific tools on and off. The list of changes is too long to list here. We suggest you take a look at the toolkits you use specifically and how they have been updated.
  • show_results is now True by default for all tools. If you just set stop_after_tool_call=True then show_results will be automatically set to True.
  • images, videos, audio and files are now available as parameters to tools. See the documentation for more details.

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Media

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Removals

  • Removed legacy artifact classes: ImageArtifact, VideoArtifact, AudioArtifact, and AudioResponse classes have been completely removed in favor of unified media classes.

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New Unified Media Architecture

  • Unified Image class: Now serves all use cases (input, output, artifacts) with standardized content: Optional[bytes] field for raw image data
  • Unified Audio class: Replaces both AudioArtifact and AudioResponse with consistent byte-based content storage and additional fields like transcript, expires_at, sample_rate, and channels
  • Unified Video class: Updated to handle all video use cases with standardized content handling and metadata fields
  • Enhanced File class: Updated to work seamlessly across agent, team, workflow, and toolkit contexts

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New Methods and Features

  • from_base64() class method: Added to Image, Audio, and Video classes for creating instances from base64-encoded content (automatically converts to raw bytes)
  • get_content_bytes() method: Retrieves content as raw bytes, handling loading from URLs or file paths
  • to_base64() method: Converts content to base64 string for transmission/storage
  • to_dict() method: Enhanced serialization with optional base64 content inclusion

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Content Standardization

  • Byte-based storage: All media content is now stored as raw bytes (Optional[bytes]) instead of mixed string/bytes formats
  • Automatic validation: Model validators ensure exactly one content source (url, filepath, or content) is provided
  • Auto-generated IDs: Media objects automatically generate UUIDs when not provided

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Logging

  • Added support for custom loggers. See the documentation for more details.

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Agent updates

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Team updates

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Workflow updates