v1.7.6
July 25, 2025
1.7.6
New Features:
- Portkey Model Support: Added support for Portkey hosted models.
- Bitbucket Tool: Added
BitbucketToolswith a variety of Bitbucket repository actions. - Jina Embedder: Added
JinaEmbedderfor using embedding models via Jina. - Row Chunking: Added
RowChunkingas a CSV chunking strategy. - EVM Toolkit: Added
EvmToolsto do transactions on EVM compatible blockchains usingweb3. - LinkUp Toolkit: Added
LinkupToolsfor powerful search. - Background Execution Support for Workflows 2.0: Introduced background execution capabilities for Workflows 2.0, enabling non-blocking workflow execution with polling support. See docs here.
Improvements:
- Async Bedrock Support: Added async execution support for the AWS bedrock implementation. See docs here
- PostgreSQL Tools Updates: Various security and stability overhauls made to the
PostgresToolstoolkit. - Daytona Toolkit Updates: Added new tools for
Daytonaagent Toolkit
Bug Fixes:
- LiteLLM Metrics: Fixed issue with metrics on streaming responses from LiteLLM.
- Team Expected Output: Fixed issue where expected_output of members were overwritten by the team leader agent.
- Workflows Async Generators: Fixed how async generator
arunfunctions are treated. It now correctly keeps async generators as async generators and doesn’t convert it to a coroutine.- Before: Workflows with Async generator
arunfunctions were incorrectly awaited as coroutines, which could cause runtime errors or prevent proper iteration through the yielded asynchronous values. - After: Async generator workflows are now properly recognised and handled as async generators, allowing for correct iteration over their yielded values using
async for. This ensures all yielded results are processed as intended within asynchronous workflows.
- Before: Workflows with Async generator
- LiteLLM Multiple Streaming Tool Calls: When Agno is run through LiteLLM against OpenAI chat models (eg. GPT4.1), multiple streamed
tool_callslost their individual argument streams. This has been resolved.
