* 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
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.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
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Add inferencer for QA only
* Add latest docstring and tutorial changes
* Add QA inferencer tests
* Add type annotations for inferencer
* Fix type annotations, move util functions
* Fix type annotations
* Move fixtures to the top of the file
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* [UPDT] delete_all_documents() replaced by delete_documents()
* [UPDT] warning logs to be fixed
* [UPDT] delete_all_documents() renamed and the same method added
Co-authored-by: Ram Garg <ramgarg102@gmai.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
* Add FARM classification node
* Add classification output to meta field of document
* Update usage example
* Add test case for FARMClassifier
* Replace FARMRanker with FARMClassifier in documentation strings
* Remove base method not implemented by any child class, etc.
* Annotation Tool: data is not persisted when using local version #853
* First version of weaviate
* First version of weaviate
* First version of weaviate
* Updated comments
* Updated comments
* ran query, get and write tests
* update embeddings, dynamic schema and filters implemented
* Initial set of tests and fixes
* Tests added for update_embeddings and delete documents
* introduced duplicate documents fix
* fixed mypy errors
* Added Weaviate to requirements
* Fix the weaviate docker env variables
* Fixing test dependencies for now
* Created weaviate test marker and fixed query
* Update docstring
* Add documentation
* Bump up weaviate version
* Bump up weaviate version in documentation
* Bump up weaviate version in documentation
* Updgrade weaviate version
Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
* Add knowledge graph module
* Fix type hint
* Add graph retriver module
* Change type annotations, change return format
* Add graph retriever that executes questions as sparql queries
* Linking only those entities that are in the knowledge graph
* Added logging and using relations extracted from Knowledge graph for linking
* Preventing entity linking from linking the same token to multiple entities
* Pruning triples that have no variables for select and count queries
* Support knowledge graphs with Pipelines
* Add text2sparql
* Entity linking and relation linking consider more special cases now based on evaluation on labelled data
* Separating example code from KGQA implementation
* Add eval on combined extarctive and kg questions
* Remove references to hp-test
* Add fields sparql_query and long_answer_list to metadata
* Removing modular Question2SPARQL approach
* Removing additional classes used for modular kgqa approach
* preparing lcquad data
* change graph db
* Translating namespaces in knowledge graph queries
* Creating graphdb index and loading triples from .ttl file
* Fetching graph config files, triples and model from S3
* Fix incompatibility issues with BaseGraphRetriever and BaseComponent
* Removing unused utility functions
* Adding doc strings and tutorial header
* Adding sparqlwrapper dependency
* Moving tutorial header
* Sorting tutorials by number within name of notebook
* Add latest docstring and tutorial changes
* Creating test cases for knowledge graph
* Changing knowledge graph example to harry potter
* Add latest docstring and tutorial changes
* Adapting the tutorial notebook to harry potter example
* Add GraphDB fixture for tests
* Add latest docstring and tutorial changes
* Added GraphDB docker launch to CI
* Use correct GraphDB fixture
* Check if GraphDB instance is already running
* Renaming question/query and incorporating other feedback from Timo and Tanay
* Removed type annotation
* Add latest docstring and tutorial changes
Co-authored-by: oryx1729 <oryx1729@protonmail.com>
Co-authored-by: Timo Moeller <timo.moeller@deepset.ai>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* 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>
* Integration of SummarizationQAPipeline with Haystack.
* Moving summarizer tests because of OOM issue
* Fixing typo
* Splitting summarizer test in separate ci step
* Removing sysctl configuration as we already running elastic search in docker container
* fixing mypy issue
* update parameter names and docstrings
* update parameter names in BaseSummarizer
* rename pipeline
* change return type of summarizer from answer to document
* change scope of doc store fixture
* revert scope
* temp. disable test_faiss_index_save_and_load()
* fix mypy. change order for mypy in CI
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
* Adding support to return embedding along with other result via query_by_embedding function
* Adding test case to check return embedding
* By default for all tests but DPR tests: disable return_embedding flag
* Reducing None test case and fixing query_by_embedding of ElasticsearchDocumentStore when it updating self.excluded_meta_data directly
* Fixing mypy reported issue
* 1. Prevent update_embeddings function in FAISSDocumentStore to set faiss_index as None when document store does not have any docs.
2. cleaning up tests by adding fixture for retriever.
* TfidfRetriever need document store with documents during initialization as it call fit() function in constructor so fixing it by checking self.paragraphs of None
* Fix naming of retriever's fixture (embedded to embedding and tfid to tfidf)
* remove phi normalization
* add special case for hnsw
* rename vector_size to vector_dim
* fix loading. fix extra dim in tests
* switch to new ES syntax for vector similarity
* 3x sql speed up. cascade deletes. add train_index()
* add docstrings. remove vector_dim from load()
* delete docs from faiss and sql
* fix delete of docs in test
* relax type hint for faiss index
* rename metric to metric_type
Co-authored-by: lalitpagaria <19303690+lalitpagaria@users.noreply.github.com>
