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v2.30.2 Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 1mo LLM Frameworks
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

agent agents ai gemini generative-ai gpt-4
+13 more
information-retrieval large-language-models llm machine-learning nlp orchestration python pytorch question-answering retrieval-augmented-generation semantic-search summarization transformers

Summary

AI summary

Fixed premature Agent termination when encountering empty assistant messages.

Full changelog

Release Notes

v2.30.2

Bug Fixes

  • Fixed the Agent exiting prematurely under the default exit_conditions=["text"]. The agent now only stops when the last message is an assistant message with non-empty text (or when no tool invoker is configured). Previously, if the LLM produced an invalid tool call that was discarded, the resulting assistant message with empty text and no tool calls would trigger an exit, preventing the agent from recovering. The agent now continues looping so the model can recover on the next iteration.

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About haystack

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

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Related context

Earlier breaking changes

  • v2.30.0 LLM.run and LLM.run_async no longer accept positional messages or streaming_callback arguments.
  • v2.29.0 `LLM.run` and `LLM.run_async` now require keyword arguments for `messages` and `streaming_callback`.

Beta — feedback welcome: [email protected]