1.2.7

New Features:

Gemini Image Generation: Added support for generating images straight from Gemini using the gemini-2.0-flash-exp-image-generation model.

Improvements:

Vertex AI: Improved use of Vertex AI with Gemini Model class to closely follow the official Google specification
Function Result Caching Improvement: We now have result caching on all Agno Toolkits and any custom functions using the @tool decorator. See the docs here.
Async Vector DB and Knowledge Base Improvements: Various knowledge bases, readers and vector DBs now have async-await support, so it will be used in agent.arun and agent.aprint_response. This also means that knowledge_base.aload() is possible which should greatly increase loading speed in some cases. The following have been converted:
- Vector DBs:
  - LanceDb → Here is a cookbook to illustrate how to use it.
  - Milvus → Here is a cookbook to illustrate how to use it.
  - Weaviate → Here is a cookbook to illustrate how to use it.
- Knowledge Bases:
  - JSONKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - PDFKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - PDFUrlKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - CSVKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - CSVUrlKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - ArxivKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - WebsiteKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - YoutubeKnowledgeBase → Here is a cookbook to illustrate how to use it.
  - TextKnowledgeBase → Here is a cookbook to illustrate how to use it.

Bug Fixes:

Recursive Chunking Infinite Loop: Fixes an issue with RecursiveChunking getting stuck in an infinite loop for large documents.