* Conversion to df does not need initialization
* Apply Black
* fix test case
* Apply Black
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Testing black on ui/
* Applying black on docstores
* Add latest docstring and tutorial changes
* Create a single GH action for Black and docs to reduce commit noise to the minimum, slightly refactor the OpenAPI action too
* Remove comments
* Relax constraints on pydoc-markdown
* Split temporary black from the docs. Pydoc-markdown was obsolete and needs a separate PR to upgrade
* Fix a couple of bugs
* Add a type: ignore that was missing somehow
* Give path to black
* Apply Black
* Apply Black
* Relocate a couple of type: ignore
* Update documentation
* Make Linux CI run after applying Black
* Triggering Black
* Apply Black
* Remove dependency, does not work well
* Remove manually double trailing commas
* Update documentation
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Fist attempt at using setup.cfg for dependency management
* Trying the new package on the CI and in Docker too
* Add composite extras_require
* Add the safe_import function for document store imports and add some try-catch statements on rest_api and ui imports
* Fix bug on class import and rephrase error message
* Introduce typing for optional modules and add type: ignore in sparse.py
* Include importlib_metadata backport for py3.7
* Add colab group to extra_requires
* Fix pillow version
* Fix grpcio
* Separate out the crawler as another extra
* Make paths relative in rest_api and ui
* Update the test matrix in the CI
* Add try catch statements around the optional imports too to account for direct imports
* Never mix direct deps with self-references and add ES deps to the base install
* Refactor several paths in tests to make them insensitive to the execution path
* Include tstadel review and re-introduce Milvus1 in the tests suite, to fix
* Wrap pdf conversion utils into safe_import
* Update some tutorials and rever Milvus1 as default for now, see #2067
* Fix mypy config
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* add tinybert data augmentation
* don't reload glove in tinybert data augmentation
* fix unnecessary load_glove call
* fix type hints
* add comments and type hints
* add batch_size argument
* don't predict subwords as alternative for words
* fix subword predictions
* limit sequence length
* actually limit sequence length
* improve performance by calculating nearest glove vector on gpu
* add model and tokenizer parameter
* fix type hints
* improve data augmentation performance
* explained limits of script
* corrected comment
* added data augmentation test
* don't label every question in augmented dataset as impossible
* add sample glove
* better handling of downloading of glove
* fix typo of last commit
* Feat: Removing use of temp file while downloading archive from url along with adding CI for windows and mac platform
* Windows CI by default installing pytorch gpu hence updating CI to pick cpu version
* fixing mac cache build issue
* updating windows pip install command for torch
* another attempt
* updating ci
* Adding sudo
* fixing ls failure on windows
* another attempt to fix build issue
* Saving env variable of test files
* Adding debug log
* Github action differ on windows
* adding debug
* anohter attempt
* Windows have different ways to receive env
* fixing template
* minor fx
* Adding debug
* Removing use of json
* Adding back fromJson
* addin toJson
* removing print
* anohter attempt
* disabling parallel run at least for testing
* installing docker for mac runner
* correcting docker install command
* Linux dockers are not suported in windows
* Removing mac changes
* Upgrading pytorch
* using lts pytorch
* Separating win and ubuntu
* Install java 11
* enabling linux container env
* docker cli command
* docker cli command
* start elastic service
* List all service
* correcting service name
* Attempt to fix multiple test run
* convert to json
* another attempt to check
* Updating build cache step
* attempt
* Add tika
* Separating windows CI
* Changing CI name
* Skipping test which does not work in windows
* Skipping tests for windows
* create cleanup function in conftest
* adding skipif marker on tests
* Run windows PR on only push to master
* Addressing review comments
* Enabling windows ci for this PR
* Tika init is being called when importing tika function
* handling tika import issue
* handling tika import issue in test
* Fixing import issue
* removing tika fixure
* Removing fixture from tests
* Disable windows ci on pull request
* Add back extra pytorch install step
Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
* 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>
* Adding dummy generator implementation
* Adding tutorial to try the model
* Committing current non working code
* Committing current update where we need to call generate function directly and need to convert embedding to tensor way
* Addressing review comments.
* Refactoring finder, and implementing rag_generator class.
* Refined the implementation of RAGGenerator and now it is in clean shape
* Renaming RAGGenerator to RAGenerator
* Reverting change from finder.py and addressing review comments
* Remove support for RagSequenceForGeneration
* Utilizing embed_passage function from DensePassageRetriever
* Adding sample test data to verify generator output
* Updating testing script
* Updating testing script
* Fixing bug related to top_k
* Updating latest farm dependency
* Comment out farm dependency
* Reverting changes from TransformersReader
* Adding transformers dataset to compare transformers and haystack generator implementation
* Using generator_encoder instead of question_encoder to generate context_input_ids
* Adding workaround to install FARM dependency from master branch
* Removing unnecessary changes
* Fixing generator test
* Removing transformers datasets
* Fixing generator test
* Some cleanup and updating TODO comments
* Adding tutorial notebook
* Updating tutorials with comments
* Explicitly passing token model in RAG test
* Addressing review comments
* Fixing notebook
* Refactoring tests to reduce memory footprint
* Split generator tests in separate ci step and before running it reclaim memory by terminating containers
* Moving tika dependent test to separate dir
* Remove unwanted code
* Brining reader under session scope
* Farm is now session object hence restoring changes from default value
* Updating assert for pdf converter
* Dummy commit to trigger CI flow
* REducing memory footprint required for generator tests
* Fixing mypy issues
* Marking test with tika and elasticsearch markers. Reverting changes in CI and pytest splits
* reducing changes
* Fixing CI
* changing elastic search ci
* Fixing test error
* Disabling return of embedding
* Marking generator test as well
* Refactoring tutorials
* Increasing ES memory to 750M
* Trying another fix for ES CI
* Reverting CI changes
* Splitting tests in CI
* Generator and non-generator markers split
* Adding pytest.ini to add markers and enable strict-markers option
* Reducing elastic search container memory
* Simplifying generator test by using documents with embedding directly
* Bump up farm to 0.5.0
