* Add support for tables in SQLDocumentStore, FAISSDocumentStore and MilvuDocumentStore
* Add support for WeaviateDocumentStore
* Make sure that embedded meta fields are strings + add embedding_dim to WeaviateDocStore in test config
* Add latest docstring and tutorial changes
* Represent tables in WeaviateDocumentStore as nested lists
* Fix mypy
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* Make Tutorial10 use print instead of logs and fix a typo in Tutoria15
* Add a type check in 'print_answers'
* Add same checks to print_documents and print_questions
* Make RAGenerator return Answers instead of dictionaries
* Fix RAGenerator tests
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* 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
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* 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
Co-authored-by: fingoldo <fingoldo@gmail.com>
Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
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* 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>
* 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
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* 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.
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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>
