Haystack is an end-to-end LLM framework that allows you to build applications
powered by LLMs, Transformer models, vector search and more. Whether you want
to perform retrieval-augmented generation (RAG), document search, question
answering or answer generation, Haystack can orchestrate state-of-the-art
embedding models and LLMs into pipelines to build end-to-end NLP applications
and solve your use case.
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py312-haystack_ai listed in the above command, you can pick from the names under the Packages section.
misc/py-haystack_ai: Update to 2.18.1
- Enhancement Notes:
- Added tools to agent run parameters to enhance the agent's
flexibility. Users can now choose a subset of tools for the agent at
runtime by providing a list of tool names, or supply an entirely new
set by passing Tool objects or a Toolset.
- Bug Fixes
- Fix Agent run_async method to correctly handle async streaming
callbacks. This previously triggered errors due to a bug.
- Prevent duplication of the last assistant message in the chat
history when initializing from an AgentSnapshot.
- We were setting response_format to None in OpenAIChatGenerator by
default which doesn't follow the API spec. We now omit the variable
if response_format is not passed by the user.
Sponsored by: resulta.tech
misc/py-haystack_ai: Add new port
Haystack is an end-to-end LLM framework that allows you to build
applications powered by LLMs, Transformer models, vector search and
more.
Sponsored by: resulta.tech
