* 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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* 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
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Add node names validation
* Add tests
* Improve test and test that params exists before validating
* Fix the REST API
* Use minilm-uncased-squad2 instead of roberta-base-squad2
* Use roberta model for test_pipeline.yaml
* Turn off TOKENIZERS_PARALLELISM in generator tests (#1605)
* Account for non-targeted parameters
* Restore previous parameters handling in the rest api
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Co-authored-by: Julian Risch <julian.risch@deepset.ai>
* 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>
* 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
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Removing probability field from reader and from test cases
* Add switch to FARMReader to choose score/probability
* Remove probability field from doc returned by doc store
* Relax assertion testing joined es and dpr predictions
* Use switch for confidence scores also for no_answer
* Add test that checks switching to old answer scores > 10
* Normalize score in elastic doc store and reset reader.md
* Scale weights of JoinDocuments to sum to 1 and adapt test case
* [pipeline] Allow for batch indexing when using Pipelines fix#1168
* [pipeline] Test case fixed fix#1168
* [file_converter] Path.suffix updated #1168
* [file_converter] meta can be one of these three cases:
A single dict that is applied to all files
One dict for each file being converted
None #1168
* [file_converter] mypy error fixed.
* [file_converter] mypy error fixed.
* [rest_api] batch file upload introduced in indexing API.
* [test_case] Test_api file upload parameter name updated.
* [ui] Streamlit file upload parameter updated.
* Adding translator with many generic input parameter support
* Making dict_key as generic
* Fixing mypy issue
* Adding pipeline and using opus models
* Add latest docstring and tutorial changes
* Adding test cases for end-to-end translation for generator, summerizer etc
* raise error join and merge nodes
* Fix test failure
* add docstrings. add usage documentation. rm skip_special_tokens param
* Add latest docstring and tutorial changes
* fix code snippets in md
* Adding few extra configuration parameters and fixing tests
* Fixingmypy issue and updating usage document
* fix for mypy issue in pipeline.py
* reverting renaming of pytest_collection_modifyitems method
* Addressing review comments
* setting skip_special_tokens to True
* removing model_max_length argument as None type is not supported to many models
* Removing padding parameter. Better to leave it as default otherwise it cause tensor size miss match error. If this option required by used then it can be added later.
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Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
