* test(extractors): Add unit test for LLMMetadataExtractor with no content
Adds a new unit test `test_run_with_document_content_none` to `TestLLMMetadataExtractor`.
This test verifies that `LLMMetadataExtractor` correctly handles documents where `document.content` is None or an empty string.
It ensures that:
- Such documents are added to the `failed_documents` list.
- The correct error message ("Document has no content, skipping LLM call.") is present in their metadata.
- No actual LLM call is attempted for these documents.
This test provides coverage for the fix that prevents an AttributeError when processing documents with no content.
* chore: update comment to reflect new behavior in _run_on_thread method
* docs: Add release note for LLMMetadataExtractor no content fix
* Update releasenotes/notes/fix-llm-metadata-extractor-no-content-910067ea72094f18.yaml
* Update fix-llm-metadata-extractor-no-content-910067ea72094f18.yaml
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Co-authored-by: David S. Batista <dsbatista@gmail.com>
* Start adding support for passing callable to Azure components
* Add to chat version
* Fix test
* Add reno
* Add support to azure doc and text embedder
* Rename
* update llm metadata extractor
* Add tests for text embedder
* Update tests
* Remove unused fixture and import
* Update reno
* Fix from_dict to work if device isn't provided in init params
* Minor refactoring of from_dict for components that load HF models
* Add tests
* Update tests to test loading with all default parameters
* Add more tests
* Add release notes
* Add unit test for whisper local
* Update reno
* Add fix for ExtractiveReader
* Fix NamedEntityExtractor
* fix: Update device deserializtion for SentenceTransformersTextEmbedder
* Add unit test
* Fix unit test
* Make same change to doc embedder
* Add release notes
* Add same change to Diversity Ranker and Named Entity Extractor
* Add unit test
* Add the same for whisper local
* Update release notes
* feat: Add `NamedEntityExtractor`component
This component accepts a list of `Document`s which it annotates with named entities. The annotations are stored in the `meta` dictionary of each `Document` under a specific key.
The component currently support two backends for the annotation models: Hugging Face `transformers` and spaCy.
* Address comments
* Expand release note
* Add the `[torch]` extra package specifier to the lazy import
* Remove dead code
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Co-authored-by: Massimiliano Pippi <mpippi@gmail.com>
