Changelog

Model Improvements:
  • Models Refactor: A complete overhaul of our models implementation to improve on performance and to have better feature parity across models.
    • This improves metrics and visibility on the Agent UI as well.
    • All models now support async-await, with the exception of AwsBedrock.
  • Azure AI Foundry: We now support all models on Azure AI Foundry. Learn more here..
  • AWS Bedrock Support: Our redone AWS Bedrock implementation now supports all Bedrock models. It is important to note which models support which features.
  • Gemini via Google SDK: With the 1.0.0 release of Google’s genai SDK we could improve our previous implementation of Gemini . This will allow for easier integration of Gemini features in future.
  • Model Failure Retries: We added better error handling of third-party errors (e.g. Rate-Limit errors) and the agent will now optionally retry with exponential backoff if exponential_backoff is set to True. <docs>
Other Improvements:
  • Exa Answers Support: Added support for the Exa answers capability.
  • GoogleSearchTools: Updated the name of GoogleSearch to GoogleSearchTools for consistency.
Deprecation:
  • Our Gemini implementation directly on the Vertex API has been replaced by the Google SDK implementation of Gemini.
  • Our Gemini implementation via the OpenAI client has been replaced by the Google SDK implementation of Gemini.
  • Our OllamaHermes has been removed as the implementation of Ollama was improved.
Bug Fixes:
  • Team Members Names: Fixed a bug where teams where team members have non-aphanumeric characters in their names would cause exceptions.

New Features:
  • Perplexity Model: We now support Perplexity as a model provider.
  • Todoist Toolkit: Added a toolkit for managing tasks on Todoist.
  • JSON Reader: Added a JSON file reader for use in knowledge bases.
Improvements:
  • LanceDb: Implemented name_exists function for LanceDb.
Bug Fixes:
  • Storage growth bug: Fixed a bug with duplication of run_messages.messages for every run in storage.

New Features:
  • Google Sheets Toolkit: Added a basic toolkit for reading, creating and updating Google sheets.
  • Weviate Vector Store: Added support for Weviate as a vector store.
Improvements:
  • Mistral Async: Mistral now supports async execution via agent.arun() and agent.aprint_response().
  • Cohere Async: Cohere now supports async execution via agent.arun() and agent.aprint_response().
Bug Fixes:
  • Retriever as knowledge source: Added small fix and examples for using the custom retriever parameter with an agent.

New Features:
  • Google Maps Toolkit: Added a rich toolkit for Google Maps that includes business discovery, directions, navigation, geocode locations, nearby places, etc.
  • URL reader and knowledge base: Added reader and knowledge base that can process any URL and store the text contents in the document store.
Bug Fixes:
  • Zoom tools fix: Zoom tools updated to include the auth step and other misc fixes.
  • Github search_repositories pagination: Pagination did not work correctly and this was fixed.

New Features:
  • Gmail Tools: Add tools for Gmail, including mail search, sending mails, etc.
Improvements:
  • Exa Toolkit Upgrade: Added find_similar to ExaTools.
  • Claude Async: Claude models can now be used with await agent.aprint_response() and await agent.arun().
  • Mistral Vision: Mistral vision models are now supported. Various examples were added to illustrate example.

Bug Fixes:
  • Claude Tool Invocation: Fixed issue where Claude was not working with tools that have no parameters.

Improvements:
  • OpenAI Reasoning Parameter: Added a reasoning parameter to OpenAI.

Improvements:
  • Model Client Caching: Made all models cache the client instantiation, improving Agno agent instantiation time.
  • XTools: Renamed TwitterTools to XTools and updated capabilities to be compatible with Twitter API v2.
Bug Fixes:
  • Agent Dataclass Compatibility: Removed slots=True from the agent dataclass decorator, which was not compatible with Python <3.10.
  • AzureOpenAIEmbedder: Fixed issue where AzureOpenAIEmbedder was not correctly made a dataclass.

Improvements:
  • Mistral Model Caching: Enabled caching for Mistral models.

This is a major refactor to be coupled with the launch of Agno.
Interface Changes:
  • Class Renaming: Renamed certain classes. For example, phi.model.x is now agno.models.x. See Changes
  • Multi-modal interface updates: We have improved the overall multimodal interface to be more intuitive. See Changes
Improvements:
  • Dataclasses: Changed various instances of Pydantic models to dataclasses to improve the speed.
Removals:
  • Removed all references to Assistant.
  • Removed all references to llm.
  • Removed the PhiTools tool.
  • Removed the PythonAgent and DuckDbAgent (this will be brought back in future with more specific agents).
Bug Fixes:
  • Semantic Chunking: Fixed semantic chunking by replacing similarity_threshold param with threshold param.
New Features:
  • Evals for Agents: Introducing Evals to measure the performance, accuracy, and reliability of your Agents.