Haystack 2.0.1
⬆️ Upgrade Notes
-
The
HuggingFaceTGIGenerator
andHuggingFaceTGIChatGenerator
components have been modified to be compatible withhuggingface_hub>=0.22.0
.If you use these components, you may need to upgrade the
huggingface_hub
library. To do this, run the following command in your environment:pip install "huggingface_hub>=0.22.0"
🚀 New Features
- Adds
streaming_callback
parameter toHuggingFaceLocalGenerator
, allowing users to handle streaming responses. - Introduce a new
SparseEmbedding
class which can be used to store a sparse vector representation of a Document. It will be instrumental to support Sparse Embedding Retrieval with the subsequent introduction of Sparse Embedders and Sparse Embedding Retrievers.
⚡️ Enhancement Notes
-
Set
max_new_tokens
default to 512 in Hugging Face generators. -
In Jupyter notebooks, the image of the Pipeline will no longer be displayed automatically. The textual representation of the Pipeline will be displayed.
To display the Pipeline image, use the
show
method of the Pipeline object.
🐛 Bug Fixes
- The
test_comparison_in
test case in the base document store tests used to always pass, no matter how thein
filtering logic was implemented in document stores. With the fix, thein
logic is actually tested. Some tests might start to fail for document stores that don’t implement thein
filter correctly. - Put
HFTokenStreamingHandler
in a lazy import block inHuggingFaceLocalGenerator
. This fixed some breaking core-integrations. - Fixes
Pipeline.run()
logic so Components that have all their inputs with a default are run in the correct order. This happened we gather a list of Components to run internally when running the Pipeline in the order they are added during creation of the Pipeline. This caused some Components to run before they received all their inputs. - Fixes
HuggingFaceTEITextEmbedder
returning an embedding of incorrect shape when used with a Text-Embedding-Inference endpoint deployed using Docker. - Add the
@component
decorator toHuggingFaceTGIChatGenerator
. The lack of this decorator made it impossible to use theHuggingFaceTGIChatGenerator
in a pipeline.