* 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.
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
* 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
