haystack/test/pytest.ini

[pytest]
addopts = --strict-markers
markers =
    slow: marks tests as slow (deselect with '-m "not slow"')
    tika: marks tests which require tika container (deselect with '-m "not tika"')
    elasticsearch: marks tests which require elasticsearch container (deselect with '-m "not elasticsearch"')
    graphdb: marks tests which require graphdb container (deselect with '-m "not graphdb"')
    generator: marks generator tests (deselect with '-m "not generator"')
    pipeline: marks tests with pipeline
    summarizer: marks summarizer tests
    weaviate: marks tests that require weaviate container
    vector_dim: marks usage of document store with non-default embedding dimension (e.g @pytest.mark.vector_dim(128))
[RAG] Integrate "Retrieval-Augmented Generation" with Haystack (#484) * 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 2020-10-30 18:06:02 +01:00			`[pytest]`
			`addopts = --strict-markers`
			`markers =`
			`slow: marks tests as slow (deselect with '-m "not slow"')`
			`tika: marks tests which require tika container (deselect with '-m "not tika"')`
			`elasticsearch: marks tests which require elasticsearch container (deselect with '-m "not elasticsearch"')`
knowledge graph example (#934) * 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> 2021-04-08 14:05:33 +02:00			`graphdb: marks tests which require graphdb container (deselect with '-m "not graphdb"')`
[RAG] Integrate "Retrieval-Augmented Generation" with Haystack (#484) * 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 2020-10-30 18:06:02 +01:00			`generator: marks generator tests (deselect with '-m "not generator"')`
Add pipelines for GenerativeQA & FAQs (#645) 2020-12-03 10:27:06 +01:00			`pipeline: marks tests with pipeline`
Add Summarizer (standalone + node in custom pipelines + SearchSummarizationPipeline) (#698) * 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> 2021-01-08 14:29:46 +01:00			`summarizer: marks summarizer tests`
Integrate Weaviate as another DocumentStore (#1064) * 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> 2021-06-10 13:13:53 +05:30			`weaviate: marks tests that require weaviate container`
Add Longform-QA (LFQA), Seq2SeqGenerator for generative QA and Retribert Retriever (#1086) * Integrate LFQA with Haystack * Integrate LFQA with Haystack - unit tests * Properly initialize conftest default value for vector_dim * Update PR after inital feedback * Fix conftest.py import * Seq2SeqGenerator uses Callables instead of subclasses for custom model input * Update docstring * Fix Callable use * Add LFQA tutorials * Improve type error reporting for invalid input converter Callable * Generate docstrings * Format comments in tutorial script * Generate tutorial md * Add usage page Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai> Co-authored-by: brandenchan <brandenchan@icloud.com> 2021-06-14 17:53:43 +02:00			`vector_dim: marks usage of document store with non-default embedding dimension (e.g @pytest.mark.vector_dim(128))`