From ff49d26db1c1f56b90e406581a0c52cd5a02aa68 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 13:39:28 +0200 Subject: [PATCH 01/13] backend support --- welearn_datastack/modules/embedding_model_helpers.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/welearn_datastack/modules/embedding_model_helpers.py b/welearn_datastack/modules/embedding_model_helpers.py index dc7a32e..5f54fea 100644 --- a/welearn_datastack/modules/embedding_model_helpers.py +++ b/welearn_datastack/modules/embedding_model_helpers.py @@ -84,11 +84,15 @@ def load_embedding_model(str_path: str) -> SentenceTransformer: logger.info("Loading embedding model from %s", str_path) device = os.environ.get("ST_DEVICE", None) + backend = os.environ.get("ST_BACKEND", None) logger.info("ST_DEVICE: %s", device) if device not in ["cpu", "cuda", None]: raise ValueError("ST_DEVICE must be one of 'cpu', 'cuda' or None") + if not isinstance(backend, str) and backend not in ["torch", "onnx", "openvino"]: + raise ValueError("ST_BACKEND must be one of 'torch', 'onnx' or 'openvino'") + model = loaded_models.get(str_path, None) if model is not None: logger.info("%s Model already loaded", str_path) @@ -98,6 +102,7 @@ def load_embedding_model(str_path: str) -> SentenceTransformer: loaded_models[str_path] = SentenceTransformer( model_name_or_path=str_path, device=device, + backend=backend, # type: ignore ) return loaded_models[str_path] From 237b8f3855735392252ed1ac660132c02f353c03 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 13:41:53 +0200 Subject: [PATCH 02/13] backend support --- welearn_datastack/modules/embedding_model_helpers.py | 1 + 1 file changed, 1 insertion(+) diff --git a/welearn_datastack/modules/embedding_model_helpers.py b/welearn_datastack/modules/embedding_model_helpers.py index 5f54fea..3ac38ee 100644 --- a/welearn_datastack/modules/embedding_model_helpers.py +++ b/welearn_datastack/modules/embedding_model_helpers.py @@ -86,6 +86,7 @@ def load_embedding_model(str_path: str) -> SentenceTransformer: device = os.environ.get("ST_DEVICE", None) backend = os.environ.get("ST_BACKEND", None) logger.info("ST_DEVICE: %s", device) + logger.info("ST_BACKEND: %s", device) if device not in ["cpu", "cuda", None]: raise ValueError("ST_DEVICE must be one of 'cpu', 'cuda' or None") From cca15e3fe0504720e36fb8354a0dc96a31c7ad9d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:09:19 +0200 Subject: [PATCH 03/13] backend support --- .../templates/documentVectorizer/cron-workflow.yaml | 5 +++++ .../workflow-template-document-vectorizer.yaml | 5 +++++ 2 files changed, 10 insertions(+) diff --git a/k8s/welearn-datastack/templates/documentVectorizer/cron-workflow.yaml b/k8s/welearn-datastack/templates/documentVectorizer/cron-workflow.yaml index 7e78ea3..32c5f2e 100644 --- a/k8s/welearn-datastack/templates/documentVectorizer/cron-workflow.yaml +++ b/k8s/welearn-datastack/templates/documentVectorizer/cron-workflow.yaml @@ -54,6 +54,8 @@ spec: default: {{ .workflowTemplates.runNode.requests.memory }} - name: size_limit default: 10000000000 # In bytes + - name: st_backend + default: "onnx" steps: - - name: generate-to-vectorize-batch templateRef: @@ -112,6 +114,9 @@ spec: - name: memory value: >- {{ print "{{inputs.parameters.memory_collect_docs}}" }} + - name: st_backend + value: >- + {{ print "{{inputs.parameters.st_backend}}" }} artifacts: - name: batch_ids_csv from: >- diff --git a/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml b/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml index 8c964b5..0855830 100644 --- a/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml +++ b/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml @@ -43,6 +43,8 @@ spec: default: 10000000000 - name: st_device default: "cpu" + - name: st_backend + default: "torch" - name: embedding_model_fr default: {{ $.Values.common.embeddingModelFr }} - name: embedding_model_en @@ -78,6 +80,9 @@ spec: - name: ST_DEVICE value: >- {{ print "{{inputs.parameters.st_device}}" }} + - name: ST_BACKEND + value: >- + {{ print "{{inputs.parameters.st_backend}}" }} - name: MODELS_PATH_ROOT value: {{ $.Values.common.modelsPathRoot }} From 72b880a96ceb0c0e16c596c3d2aff5fdd6d96b9a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:09:36 +0200 Subject: [PATCH 04/13] backend support --- pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/pyproject.toml b/pyproject.toml index 9418a58..15b37b0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -45,6 +45,7 @@ lingua-language-detector = "^2.1.1" psycopg2-binary = "^2.9.10" brotli = "^1.1.0" scikit-learn = "1.6.1" +optimum = {extras = ["onnxruntime"], version = "^1.26.1"} 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welearn_datastack/modules/embedding_model_helpers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/welearn_datastack/modules/embedding_model_helpers.py b/welearn_datastack/modules/embedding_model_helpers.py index 3ac38ee..ab6feee 100644 --- a/welearn_datastack/modules/embedding_model_helpers.py +++ b/welearn_datastack/modules/embedding_model_helpers.py @@ -86,7 +86,7 @@ def load_embedding_model(str_path: str) -> SentenceTransformer: device = os.environ.get("ST_DEVICE", None) backend = os.environ.get("ST_BACKEND", None) logger.info("ST_DEVICE: %s", device) - logger.info("ST_BACKEND: %s", device) + logger.info("ST_BACKEND: %s", backend) if device not in ["cpu", "cuda", None]: raise ValueError("ST_DEVICE must be one of 'cpu', 'cuda' or None") From 7b3e2e990ab3a3ff8874baabfa7a2618e12933df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:39:48 +0200 Subject: [PATCH 07/13] backend support + batch mode --- .../test_embedding_model_helpers.py | 5 ++- .../DocumentVectorizer/document_vectorizer.py | 36 +++++++++++++++---- 2 files changed, 32 insertions(+), 9 deletions(-) diff --git a/tests/document_vectorizer/test_embedding_model_helpers.py b/tests/document_vectorizer/test_embedding_model_helpers.py index 0dfe833..2b6b99c 100644 --- a/tests/document_vectorizer/test_embedding_model_helpers.py +++ b/tests/document_vectorizer/test_embedding_model_helpers.py @@ -18,9 +18,8 @@ class TestEmbeddingHelper(TestCase): def setUp(self) -> None: get_sub_environ_according_prefix.cache_clear() - os.environ["MODELS_NAME_PREFIX"] = "EMBEDDING_MODEL" - os.environ["EMBEDDING_MODEL_FR"] = "test_fr" - os.environ["EMBEDDING_MODEL_EN"] = "test_en" + os.environ["ST_BACKEND"] = "onnx" + def tearDown(self) -> None: os.environ.clear() diff --git a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py index fa312c7..6290c42 100644 --- 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# logger.info("Insert new slices") + # db_session.add_all(slices) + # logger.info("Insert new state") + # db_session.add( + # ProcessState( + # id=uuid.uuid4(), + # document_id=document.id, + # title=Step.DOCUMENT_VECTORIZED.value, + # ) + # ) + # db_session.commit() + # + logger.info("Adding slices to bulk") + bulk_slices.extend(slices) + + logger.info("Adding process state to bulk") + bulk_process_state.append( ProcessState( id=uuid.uuid4(), document_id=document.id, title=Step.DOCUMENT_VECTORIZED.value, ) ) - db_session.commit() - logger.info("'%s' slices were created", len(slices)) + docids_processed += 1 except NoModelFoundError: logger.error("No model found for document %s", document.id) @@ -121,6 +137,14 @@ def main() -> None: logger.info("'%s' documents were processed", docids_processed) logger.info("'%s' documents were not processed", docsids_not_processed) + db_session.bulk_save_objects(bulk_slices) + logger.info("'%s' slices were added to the session", len(bulk_slices)) + db_session.bulk_save_objects(bulk_process_state) + logger.info( + "'%s' process states were added to the session", len(bulk_process_state) + ) + + db_session.commit() db_session.close() logger.info("DocumentVectorizer finished") From 3daade65c3bbee27b149ff3930ddc47503e4b1a7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:40:05 +0200 Subject: [PATCH 08/13] backend support + batch mode --- tests/document_vectorizer/test_embedding_model_helpers.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/document_vectorizer/test_embedding_model_helpers.py b/tests/document_vectorizer/test_embedding_model_helpers.py index 2b6b99c..4011f63 100644 --- a/tests/document_vectorizer/test_embedding_model_helpers.py +++ b/tests/document_vectorizer/test_embedding_model_helpers.py @@ -20,7 +20,6 @@ def setUp(self) -> None: get_sub_environ_according_prefix.cache_clear() os.environ["ST_BACKEND"] = "onnx" - def tearDown(self) -> None: os.environ.clear() From 9d5cb84b07a58417f9d936eb89fccc52bdfa7798 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:41:10 +0200 Subject: [PATCH 09/13] kept for trace in bulk too --- .../nodes_workflow/DocumentVectorizer/document_vectorizer.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py index 6290c42..e52074b 100644 --- a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py +++ b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py @@ -123,14 +123,13 @@ def main() -> None: docids_processed += 1 except NoModelFoundError: logger.error("No model found for document %s", document.id) - db_session.add( + bulk_process_state.append( ProcessState( id=uuid.uuid4(), document_id=document.id, title=Step.KEPT_FOR_TRACE.value, ) ) - db_session.commit() docsids_not_processed += 1 continue From e520d2b8df20715252a0830bfe5f91389198b6c1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:42:50 +0200 Subject: [PATCH 10/13] onnx --- .../workflow-template-document-vectorizer.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml b/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml index 0855830..028c9cc 100644 --- a/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml +++ b/k8s/welearn-datastack/templates/documentVectorizer/workflow-template-document-vectorizer.yaml @@ -44,7 +44,7 @@ spec: - name: st_device default: "cpu" - name: st_backend - default: "torch" + default: "onnx" - name: embedding_model_fr default: {{ $.Values.common.embeddingModelFr }} - name: embedding_model_en From 7d9a63763f3079d2f4197ee5dde71899241abcf6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:47:52 +0200 Subject: [PATCH 11/13] rm comments --- .../DocumentVectorizer/document_vectorizer.py | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py index e52074b..69d5fb4 100644 --- a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py +++ b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py @@ -96,18 +96,6 @@ def main() -> None: ).delete() db_session.commit() - # logger.info("Insert new slices") - # db_session.add_all(slices) - # logger.info("Insert new state") - # db_session.add( - # ProcessState( - # id=uuid.uuid4(), - # document_id=document.id, - # title=Step.DOCUMENT_VECTORIZED.value, - # ) - # ) - # db_session.commit() - # logger.info("Adding slices to bulk") bulk_slices.extend(slices) From ae47cb9a149c321854378649e50b2e55d8c4ff27 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:47:57 +0200 Subject: [PATCH 12/13] rm useless test --- welearn_datastack/modules/embedding_model_helpers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/welearn_datastack/modules/embedding_model_helpers.py b/welearn_datastack/modules/embedding_model_helpers.py index ab6feee..b6093f3 100644 --- a/welearn_datastack/modules/embedding_model_helpers.py +++ b/welearn_datastack/modules/embedding_model_helpers.py @@ -91,7 +91,7 @@ def load_embedding_model(str_path: str) -> SentenceTransformer: if device not in ["cpu", "cuda", None]: raise ValueError("ST_DEVICE must be one of 'cpu', 'cuda' or None") - if not isinstance(backend, str) and backend not in ["torch", "onnx", "openvino"]: + if backend not in ["torch", "onnx", "openvino"]: raise ValueError("ST_BACKEND must be one of 'torch', 'onnx' or 'openvino'") model = loaded_models.get(str_path, None) From a67583cec39fe56c90a6afb0eb705e4e4c5c07a2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Th=C3=A9o?= Date: Tue, 8 Jul 2025 15:54:41 +0200 Subject: [PATCH 13/13] type hint --- .../nodes_workflow/DocumentVectorizer/document_vectorizer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py index 69d5fb4..7cfa19c 100644 --- a/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py +++ b/welearn_datastack/nodes_workflow/DocumentVectorizer/document_vectorizer.py @@ -73,8 +73,8 @@ def main() -> None: # Create content slices docids_processed = 0 docsids_not_processed = 0 - bulk_slices: list = [] - bulk_process_state: list = [] + bulk_slices: list[DocumentSlice] = [] + bulk_process_state: list[ProcessState] = [] for i, document in enumerate(welearn_documents): logger.info("Processing document %s/%s", i, len(welearn_documents)) try: