* create uuid and dummy embeddding in weaviate doc store
* handle and test for duplicate non-uuid-formatted ids in weaviate
* add uuid and dummy embedding to doc strings
* Add latest docstring and tutorial changes
* Upgrade weaviate
* Include weaviate in common doc store test cases
* Add latest docstring and tutorial changes
* Exclude weaviate doc store from eval tests
* Incorporate index name in uuid generation
* Ignore mypy error
* Fix typo
* Restore DOCS without uuid and embeddings generated by weaviate
* Supply docs for retriever tests as fixture
* Limit scope of fixture to function instead of session
* Add comments
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* Added uniform normalization method to each of the DocStores (implemented), so that now Milvus and Weaviate doc stores can use cosine similarity, plus future method for making existing embeddings normaziled (empty for now).
* Fixed a typo.
* Fixed lots of stuff. Performed local tests.
* Fixed scores representation for cosine. Assuming Weavieate's rep needs no change.
* fixes as per discussion
* Trigger CI
* resolving conflicts
* small typo
* fixed a param type
* cleaned some conflicts resolving left overs
* commented out fastmath for a moment
* fixing tests
* added docstore for small vectors
* test
* fixed document_store_cosine_small
* cosine tests fixes
* fixed document_store_cosine_small
* fixed weaviate index name and lowered rtol for ES
* increased rtol
* added explicit doc_ids for weaviate, excluded ES, included Inmemory
* resolving mismatch
* fixing a typo
* flatten normalize_embedding()
* fix import for test
* standardize normalize_embeddings across doc stores
* Add latest docstring and tutorial changes
* going for the faster plain dot prod
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Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
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* ensure tf-idf matrix calculation before retrieval
* Run fit() automatically if new documents have been added
* Add latest docstring and tutorial changes
* Fix type error
* Add test case for tfidf retriever yaml pipeline
* Use InMemoryDocStore and add 2nd test case
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* Truncate too large tables for TableReader
* Add documentation
* Add latest docstring and tutorial changes
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* Files moved, imports all broken
* Fix most imports and docstrings into
* Fix the paths to the modules in the API docs
* Add latest docstring and tutorial changes
* Add a few pipelines that were lost in the inports
* Fix a bunch of mypy warnings
* Add latest docstring and tutorial changes
* Create a file_classifier module
* Add docs for file_classifier
* Fixed most circular imports, now the REST API can start
* Add latest docstring and tutorial changes
* Tackling more mypy issues
* Reintroduce from FARM and fix last mypy issues hopefully
* Re-enable old-style imports
* Fix some more import from the top-level package in an attempt to sort out circular imports
* Fix some imports in tests to new-style to prevent failed class equalities from breaking tests
* Change document_store into document_stores
* Update imports in tutorials
* Add latest docstring and tutorial changes
* Probably fixes summarizer tests
* Improve the old-style import allowing module imports (should work)
* Try to fix the docs
* Remove dedicated KnowledgeGraph page from autodocs
* Remove dedicated GraphRetriever page from autodocs
* Fix generate_docstrings.sh with an updated list of yaml files to look for
* Fix some more modules in the docs
* Fix the document stores docs too
* Fix a small issue on Tutorial14
* Add latest docstring and tutorial changes
* Add deprecation warning to old-style imports
* Remove stray folder and import Dict into dense.py
* Change import path for MLFlowLogger
* Add old loggers path to the import path aliases
* Fix debug output of convert_ipynb.py
* Fix circular import on BaseRetriever
* Missed one merge block
* re-run tutorial 5
* Fix imports in tutorial 5
* Re-enable squad_to_dpr CLI from the root package and move get_batches_from_generator into document_stores.base
* Add latest docstring and tutorial changes
* Fix typo in utils __init__
* Fix a few more imports
* Fix benchmarks too
* New-style imports in test_knowledge_graph
* Rollback setup.py
* Rollback squad_to_dpr too
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* Update jobs link to personio
* Add latest docstring and tutorial changes
* Change jobs link to main website
* Add latest docstring and tutorial changes
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* Add delete_labels() except for weaviate doc store
* Add latest docstring and tutorial changes
* Add test for delete_labels()
* Adapt filter for label deletion to different doc stores in test
* Allow delete labels by _id in elasticsearch
* Add latest docstring and tutorial changes
* Add latest docstring and tutorial changes
* re-add bugfix after merge
* Add ids as optional parameter
* Add latest docstring and tutorial changes
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* Rename TransformersAdamW into simply AdamW (probably changed in transformers at some point)
* Add latest docstring and tutorial changes
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* Add endpoint to get documents by filter
* Add test for /documents/get_by_filter and extend the delete documents test
* Add rest_api/file-upload to .gitignore
* Make sure the document store is empty for each test
* Improve docstrings of delete_documents_by_filters and get_documents_by_filters
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* First rough implementation
* Add a flag to dump the debug logs to the console as well
* Typing run() and _dispatch_run()
* Allow debug and debug_logs to be passed as arguments of run()
* Avoid overwriting _debug, later we might want to store other objects in it
* Put logs under a separate key of the _debug dictionary and add input and output of the node alongside it
* Introduce global arguments for pipeline.run() that get applied to every node when defined
* Change default values of debug variables to None, otherwise their default would override the params values
* Remove a potential infinite recursion on the overridden __getattr__
* Do not append the output of the last node in the _debug key, it causes infinite recursion
* Add tests
* Move the input/output collection into _dispatch_run to gather only relevant info
* Add partial Pipeline.run() docstring
* Add latest docstring and tutorial changes
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Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
* Initial draft of TransformersClassifier
* Add transformers classifier implementation
* Add test for SentenceTransformersClassifier
* Add truncation and corresponding test case to Classifier
* Add zero-shot classification and test
* Add document classifier documentation
* Add latest docstring and tutorial changes
* print meta data with print_documents()
* Add latest docstring and tutorial changes
* Remove top_k param from Classifier usage example
* Add latest docstring and tutorial changes
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* Make InMemoryDocumentStore accept and apply filters in delete_documents()
* Modify test_document_store.py to test the filtered deletion in memory, sql and milvus too
* Make FAISSDocumentStore accept and properly apply filters in delete_documents()
* Add latest docstring and tutorial changes
* Remove accidentally duplicated test
* Remove unnecessary decorators from test/test_document_store.py::test_delete_documents_with_filters
* Add embeddings count test for FAISS and Milvus; Milvus fails it.
* Fixed a bug that made Milvus not deleting embeddings
* Remove batch size parametrization in tests & update all documentstore's docstrings with a filter example
* Add latest docstring and tutorial changes
Co-authored-by: prafgup <prafulgupta6@gmail.com>
* simplify tests for individual doc stores
* WIP refactoring markers of tests
* test alternative approach for tests with existing parametrization
* fix skip logic of already parametrized tests
* fix weaviate behaviour in tests - not parametrizing it in our general test cases.
* Add latest docstring and tutorial changes
* fix some tests
* remove sql from document_store_types
* fix markers for generator and pipeline test
* remove inmemory marker
* remove unneeded elasticsearch markers
* update readme and contributing.md
* update contributing
* adjust example
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* Define SAS model in notebook
* Add latest docstring and tutorial changes
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* remove not needed githab actions and reactivate docstrings and tutorial generation
* test workflow
* update pydoc version
* update python version
* update watchdog
* move to latest version pydoc-markdown
* remove version check
* Add latest docstring and tutorial changes
* remove test workflow
* test for param docstrings
* pin pydoc-markdown version
* add test workflow
* pin watchdog version
* Add latest docstring and tutorial changes
* update original workflow and delete test
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* Bump Weaviate
* Bump Weaviate
* Bump Weaviate client
* Bump Weaviate
* Revert client version
There is a change in the client API that needs to be addressed before bumping its version
