diff --git a/llm-semantic-annotator.ipynb b/llm-semantic-annotator.ipynb index f42f58f..aa8668c 100644 --- a/llm-semantic-annotator.ipynb +++ b/llm-semantic-annotator.ipynb @@ -6,9 +6,9 @@ "id": "dKquLaEdEeVv" }, "source": [ - "On utilise :\n", - "- RDFLIB pour construire le dataset des labels // vecteur d'embeddings\n", - "- Torch, Transformer pour utiliser le model encodeur de type BERT." + "# LLMSemanticAnnotator: Advanced Semantic Annotation for Plant Biology Research\n", + "\n", + "Installation de la lib" ] }, { @@ -21,94 +21,7 @@ "id": "tKZS68aVEQbW", "outputId": "d8713e6c-a469-477c-b29b-99368362cf17" }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Collecting git+https://github.com/p2m2/encoder-ontology-match-abstract\n", - " Cloning https://github.com/p2m2/encoder-ontology-match-abstract to /tmp/pip-req-build-7_9_4veb\n", - " Running command git clone --filter=blob:none --quiet https://github.com/p2m2/encoder-ontology-match-abstract /tmp/pip-req-build-7_9_4veb\n", - 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" Created wheel for llm-semantic-annotator: filename=llm_semantic_annotator-0.1-py3-none-any.whl size=20456 sha256=087ec81ccdc0ed77b06b57a5ddf3e6ecee9ec86ed809ed6929c16b2166b93430\n", - " Stored in directory: /tmp/pip-ephem-wheel-cache-y77ogfsw/wheels/af/c0/2b/0168497674b20472d0c1ad6543b218259553ac96fb3d1277fb\n", - " Building wheel for np (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - " Created wheel for np: filename=np-1.0.2-py3-none-any.whl size=13657 sha256=b4ba2608a40751112b7b7037ed3d7a111e68dac3a7dee729d514562f514d8d16\n", - " Stored in directory: /root/.cache/pip/wheels/f9/e1/79/c4580a03022dece233bc146286fc9082a8885ee1a7c8d8b980\n", - " Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - " Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9656 sha256=89ee762de6bfb734a087a200bf858bc907b2d58046d585b034b5a992ce46df2a\n", - " Stored in directory: /root/.cache/pip/wheels/8b/f1/7f/5c94f0a7a505ca1c81cd1d9208ae2064675d97582078e6c769\n", - "Successfully built llm-semantic-annotator np wget\n", - "Installing collected packages: wget, np, isodate, rdflib, sentence_transformers, llm-semantic-annotator\n", - "Successfully installed isodate-0.6.1 llm-semantic-annotator-0.1 np-1.0.2 rdflib-7.0.0 sentence_transformers-3.1.0 wget-3.2\n" - ] - } - ], + "outputs": [], "source": [ "#!pip uninstall llm_semantic_annotator\n", "!pip install git+https://github.com/p2m2/encoder-ontology-match-abstract\n" @@ -116,12 +29,12 @@ }, { "cell_type": "markdown", - "source": [ - "Creation du fichier de configuration pour l'alignement des ontologies" - ], "metadata": { "id": "V6uHhs_Bz5B_" - } + }, + "source": [ + "Creation du fichier de configuration pour l'alignement des ontologies" + ] }, { "cell_type": "code", @@ -135,7 +48,7 @@ "\n", "data = {\n", " \"encodeur\" : \"sentence-transformers/all-MiniLM-L6-v2\",\n", - " \"threshold_similarity_tag_chunk\" : 0.65,\n", + " \"threshold_similarity_tag_chunk\" : 0.67,\n", " \"threshold_similarity_tag\" : 0.75,\n", " \"batch_size\" : 32,\n", " \"populate_owl_tag_embeddings\" : {\n", @@ -173,8 +86,7 @@ " },\n", " \"debug_nb_terms_by_ontology\" : -1\n", " },\n", - " \"populate_gbif_taxon_tag_embeddings\" : {\n", - " \"debug_nb_taxon\" : -1,\n", + " \"populate_ncbi_taxon_tag_embeddings\" : {\n", " \"tags_per_file\" : 40000\n", " },\n", " \"populate_abstract_embeddings\" : {\n", @@ -182,31 +94,23 @@ " \"from_ncbi_api\" : {\n", " \"debug_nb_ncbi_request\" : -1,\n", " \"debug_nb_abstracts_by_search\" : -1,\n", - " \"retmax\" : 5000,\n", + " \"retmax\" : 500,\n", " \"selected_term\" : [\n", " \"human+AND+genetics\",\n", - " \"abiotic+AND+stress+AND+mass+AND+spectrometry+AND+glucosinolate+AND+brassicaceae\"\n", - " ]\n", - " },\n", - " \"from_file\" : {\n", - " \"json_files\" : [\n", - " \"data/abstracts/abstracts_1.json\"\n", + " \"abiotic+AND+mass+AND+spectrometry+AND+glucosinolate+AND+brassicaceae\",\n", + " \"plant+AND+development+AND+spectrometry\",\n", " ]\n", " }\n", - "\n", " }\n", "}\n", "\n", - "\n", "with open('config.json', 'w') as fichier:\n", " json.dump(data, fichier, indent=4)\n" ] }, { "cell_type": "code", - "source": [ - "!llm-semantic-annotator config.json populate_owl_tag_embeddings" - ], + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -214,154 +118,14 @@ "id": "yJSBbOQr0Fj4", "outputId": "8d7bcec6-a612-426c-a305-ec9daba01946" }, - "execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "2024-09-13 15:55:22.885397: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2024-09-13 15:55:22.912412: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2024-09-13 15:55:22.920056: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2024-09-13 15:55:22.938770: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", - "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", - "2024-09-13 15:55:24.489230: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "Ontologies : {'planteome_link': {'peco': {'url': 'http://purl.obolibrary.org/obo/peco.owl', 'prefix': 'http://purl.obolibrary.org/obo/PECO_', 'format': 'xml', 'label': '', 'properties': ['']}, 'po': {'url': 'http://purl.obolibrary.org/obo/po.owl', 'prefix': 'http://purl.obolibrary.org/obo/PO_', 'format': 'xml', 'label': '', 'properties': ['']}, 'pso': {'url': 'http://purl.obolibrary.org/obo/pso.owl', 'prefix': 'http://purl.obolibrary.org/obo/PSO_', 'format': 'xml', 'label': '', 'properties': ['']}, 'to': {'url': 'http://purl.obolibrary.org/obo/to.owl', 'prefix': 'http://purl.obolibrary.org/obo/TO_', 'format': 'xml', 'label': '', 'properties': ['']}}}\n", - "Nb terms to compute : -1\n", - "tokenizer_config.json: 100% 350/350 [00:00<00:00, 1.31MB/s]\n", - "vocab.txt: 100% 232k/232k [00:00<00:00, 1.39MB/s]\n", - "tokenizer.json: 100% 466k/466k [00:00<00:00, 1.90MB/s]\n", - "special_tokens_map.json: 100% 112/112 [00:00<00:00, 601kB/s]\n", - "config.json: 100% 612/612 [00:00<00:00, 2.69MB/s]\n", - "model.safetensors: 100% 90.9M/90.9M [00:00<00:00, 259MB/s]\n", - "------------------------------------\n", - "endoceur: sentence-transformers/all-MiniLM-L6-v2\n", - "threshold_similarity_tag: \u001b[1;36m0.75\u001b[0m\n", - "threshold_similarity_tag_chunk: \u001b[1;36m0.65\u001b[0m\n", - "batch_size: \u001b[1;36m32\u001b[0m\n", - "------------------------------------\n", - "Downloading ontology: peco\n", - "Downloading ontology: po\n", - "Downloading ontology: pso\n", - "Downloading ontology: to\n", - "\n", - " SELECT ?term ?labelLeaf ?prop0 WHERE \u001b[1m{\u001b[0m \n", - " ?term \u001b[1m<\u001b[0m\u001b[4;94mhttp:\u001b[0m\u001b[4;94m//purl.obolibrary.org/obo/IAO_0000115\u001b[0m\u001b[39m> ?prop0 .\u001b[0m\n", - "\u001b[39m ?term <\u001b[0m\u001b[4;94mhttp://www.w3.org/2000/01/rdf-schema#label\u001b[0m\u001b[1m>\u001b[0m ?labelLeaf .\n", - " \u001b[1m}\u001b[0m\n", - " \n", - "Ontology peco NB RECORDS:\u001b[1;36m542\u001b[0m\n", - "100% 542/542 [00:00<00:00, 33356.51it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - "100% 522/522 [00:00<00:00, 726660.04it/s]\n", - "batch encoding\u001b[33m...\u001b[0m..\n", - "100% 17/17 [00:15<00:00, 1.07it/s]\n", - "set encoding\u001b[33m...\u001b[0m..\n", - "522it [00:00, 1437574.98it/s]\n", - "\n", - " SELECT ?term ?labelLeaf ?prop0 WHERE \u001b[1m{\u001b[0m \n", - " ?term \u001b[1m<\u001b[0m\u001b[4;94mhttp:\u001b[0m\u001b[4;94m//purl.obolibrary.org/obo/IAO_0000115\u001b[0m\u001b[39m> ?prop0 .\u001b[0m\n", - "\u001b[39m ?term <\u001b[0m\u001b[4;94mhttp://www.w3.org/2000/01/rdf-schema#label\u001b[0m\u001b[1m>\u001b[0m ?labelLeaf .\n", - " \u001b[1m}\u001b[0m\n", - " \n", - "Ontology po NB RECORDS:\u001b[1;36m1794\u001b[0m\n", - "100% 1794/1794 [00:00<00:00, 32806.29it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - "100% 1660/1660 [00:00<00:00, 295837.89it/s]\n", - "batch encoding\u001b[33m...\u001b[0m..\n", - "100% 52/52 [00:49<00:00, 1.05it/s]\n", - "set encoding\u001b[33m...\u001b[0m..\n", - "1660it [00:00, 1336380.93it/s]\n", - "\n", - " SELECT ?term ?labelLeaf ?prop0 WHERE \u001b[1m{\u001b[0m \n", - " ?term \u001b[1m<\u001b[0m\u001b[4;94mhttp:\u001b[0m\u001b[4;94m//purl.obolibrary.org/obo/IAO_0000115\u001b[0m\u001b[39m> ?prop0 .\u001b[0m\n", - "\u001b[39m ?term <\u001b[0m\u001b[4;94mhttp://www.w3.org/2000/01/rdf-schema#label\u001b[0m\u001b[1m>\u001b[0m ?labelLeaf .\n", - " \u001b[1m}\u001b[0m\n", - " \n", - "Ontology pso NB RECORDS:\u001b[1;36m585\u001b[0m\n", - "100% 585/585 [00:00<00:00, 32176.30it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - "100% 584/584 [00:00<00:00, 453606.21it/s]\n", - "batch encoding\u001b[33m...\u001b[0m..\n", - "100% 19/19 [00:24<00:00, 1.28s/it]\n", - "set encoding\u001b[33m...\u001b[0m..\n", - "584it [00:00, 1336319.44it/s]\n", - "\n", - " SELECT ?term ?labelLeaf ?prop0 WHERE \u001b[1m{\u001b[0m \n", - " ?term \u001b[1m<\u001b[0m\u001b[4;94mhttp:\u001b[0m\u001b[4;94m//purl.obolibrary.org/obo/IAO_0000115\u001b[0m\u001b[39m> ?prop0 .\u001b[0m\n", - "\u001b[39m ?term <\u001b[0m\u001b[4;94mhttp://www.w3.org/2000/01/rdf-schema#label\u001b[0m\u001b[1m>\u001b[0m ?labelLeaf .\n", - " \u001b[1m}\u001b[0m\n", - " \n", - "Ontology to NB RECORDS:\u001b[1;36m1568\u001b[0m\n", - "100% 1568/1568 [00:00<00:00, 33374.28it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - "100% 1535/1535 [00:00<00:00, 449034.50it/s]\n", - "batch encoding\u001b[33m...\u001b[0m..\n", - " 4% 2/48 [00:05<02:16, 2.97s/it]\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/bin/llm-semantic-annotator\", line 8, in \n", - " sys.exit(main())\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/__main__.py\", line 58, in main\n", - " main_populate_owl_tag_embeddings(config)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/core.py\", line 28, in main_populate_owl_tag_embeddings\n", - " OwlTagManager(config,mem).manage_tags()\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/tag/owl_tag_manager.py\", line 160, in manage_tags\n", - " self.get_corpus(ontologies)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/tag/owl_tag_manager.py\", line 32, in get_corpus\n", - " self.build_corpus(ontology, ontologies[ontology],self.debug_nb_terms_by_ontology)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/tag/owl_tag_manager.py\", line 154, in build_corpus\n", - " self.mem.save_pth(self.mem.encode_tags(tags),tags_owl_path_filename)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/similarity/model_embedding_manager.py\", line 207, in encode_tags\n", - " embeddings = self.encode_text_batch(toencode)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/similarity/model_embedding_manager.py\", line 169, in encode_text_batch\n", - " return self.encode_text_batch_allMiniLML6V2(texts, self.batch_size)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/similarity/model_embedding_manager.py\", line 154, in encode_text_batch_allMiniLML6V2\n", - " outputs = self.model(**inputs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1553, in _wrapped_call_impl\n", - " return self._call_impl(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1562, in _call_impl\n", - " return forward_call(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/models/bert/modeling_bert.py\", line 1141, in forward\n", - " encoder_outputs = self.encoder(\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1553, in _wrapped_call_impl\n", - " return self._call_impl(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1562, in _call_impl\n", - " return forward_call(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/models/bert/modeling_bert.py\", line 694, in forward\n", - " layer_outputs = layer_module(\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1553, in _wrapped_call_impl\n", - " return self._call_impl(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1562, in _call_impl\n", - " return forward_call(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/models/bert/modeling_bert.py\", line 626, in forward\n", - " layer_output = apply_chunking_to_forward(\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/pytorch_utils.py\", line 239, in apply_chunking_to_forward\n", - " return forward_fn(*input_tensors)\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/models/bert/modeling_bert.py\", line 639, in feed_forward_chunk\n", - " layer_output = self.output(intermediate_output, attention_output)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1553, in _wrapped_call_impl\n", - " return self._call_impl(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1562, in _call_impl\n", - " return forward_call(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/transformers/models/bert/modeling_bert.py\", line 551, in forward\n", - " hidden_states = self.dense(hidden_states)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1553, in _wrapped_call_impl\n", - " return self._call_impl(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\", line 1562, in _call_impl\n", - " return forward_call(*args, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/torch/nn/modules/linear.py\", line 117, in forward\n", - " return F.linear(input, self.weight, self.bias)\n", - "KeyboardInterrupt\n", - "^C\n" - ] - } + "outputs": [], + "source": [ + "!llm-semantic-annotator config.json populate_owl_tag_embeddings" ] }, { "cell_type": "code", - "source": [ - "!llm-semantic-annotator config.json populate_gbif_taxon_tag_embeddings" - ], + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -369,5043 +133,35 @@ "id": "_D4-Z28z8E6a", "outputId": "f7967200-2131-4802-b565-306f870a95c4" }, - "execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "\u001b[1;30;43mLe flux de sortie a été tronqué et ne contient que les 5000 dernières lignes.\u001b[0m\n", - "set encoding\u001b[33m...\u001b[0m..\n", - "5000it [00:00, 1509502.63it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - "100% 5000/5000 [00:00<00:00, 2016492.31it/s]\n", - "batch encoding\u001b[33m...\u001b[0m..\n", - "100% 157/157 [00:01<00:00, 83.03it/s]\n", - "set encoding\u001b[33m...\u001b[0m..\n", - "5000it [00:00, 1650131.40it/s]\n", - "Flat tags to build batch\u001b[33m...\u001b[0m..\n", - 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"source": [], + "execution_count": null, "metadata": { "id": "S7IB2o9B3d2k" }, - "execution_count": null, - "outputs": [] + "outputs": [], + "source": [] }, { "cell_type": "markdown", + "metadata": { + "id": "j9DsD4l48FLe" + }, "source": [ "\n", "## Abstract\n", "---\n", "\n" - ], - "metadata": { - "id": "j9DsD4l48FLe" - } + ] }, { "cell_type": "code", - "source": [ - "!llm-semantic-annotator config.json populate_abstract_embeddings" - ], + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -5413,54 +169,24 @@ "id": "DrfFNtbS8FZU", "outputId": "69284d62-bce2-49d8-8348-b006006a48d1" }, - "execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "2024-09-13 13:32:07.342670: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2024-09-13 13:32:07.362712: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2024-09-13 13:32:07.368522: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2024-09-13 13:32:07.382571: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", - "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", - "2024-09-13 13:32:08.522501: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "------------------------------------\n", - "endoceur: sentence-transformers/all-MiniLM-L6-v2\n", - "threshold_similarity_tag: \u001b[1;36m0.75\u001b[0m\n", - "threshold_similarity_tag_chunk: \u001b[1;36m0.65\u001b[0m\n", - "batch_size: \u001b[1;36m32\u001b[0m\n", - "------------------------------------\n", - "100% 250/250 [02:34<00:00, 1.62it/s]\n", - 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"execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "2024-09-13 15:15:52.230210: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2024-09-13 15:15:52.251028: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2024-09-13 15:15:52.257354: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2024-09-13 15:15:52.272472: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", - "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", - "2024-09-13 15:15:53.561522: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "------------------------------------\n", - "endoceur: sentence-transformers/all-MiniLM-L6-v2\n", - "threshold_similarity_tag: \u001b[1;36m0.75\u001b[0m\n", - "threshold_similarity_tag_chunk: \u001b[1;36m0.65\u001b[0m\n", - "batch_size: \u001b[1;36m32\u001b[0m\n", - "------------------------------------\n", - "100% 250/250 [00:01<00:00, 228.43it/s]\n", - "100% 250/250 [00:01<00:00, 248.95it/s]\n", - "100% 250/250 [00:00<00:00, 698.24it/s]\n", - "100% 250/250 [00:00<00:00, 665.49it/s]\n", - "100% 250/250 [00:04<00:00, 60.33it/s]\n", - "100% 250/250 [00:03<00:00, 75.29it/s]\n", - "100% 250/250 [00:03<00:00, 76.31it/s]\n", - "100% 250/250 [00:03<00:00, 72.38it/s]\n", - "100% 250/250 [00:04<00:00, 55.60it/s]\n", - "100% 250/250 [00:03<00:00, 77.04it/s]\n", - "100% 250/250 [00:03<00:00, 75.42it/s]\n", - "100% 250/250 [00:03<00:00, 68.55it/s]\n", - "100% 250/250 [00:04<00:00, 58.33it/s]\n", - 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" 48% 120/250 [00:01<00:02, 60.24it/s]\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/bin/llm-semantic-annotator\", line 8, in \n", - " sys.exit(main())\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/__main__.py\", line 64, in main\n", - " main_compute_tag_chunk_similarities(config)\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/core.py\", line 73, in main_compute_tag_chunk_similarities\n", - " for doi,res in mem.compare_tags_with_chunks(\n", - " File \"/usr/local/lib/python3.10/dist-packages/llm_semantic_annotator/similarity/model_embedding_manager.py\", line 275, in compare_tags_with_chunks\n", - " similarities = 1 - cdist(chunks_matrix, tag_embeddings_matrix, metric='cosine')\n", - " File \"/usr/local/lib/python3.10/dist-packages/scipy/spatial/distance.py\", line 2980, in cdist\n", - " return cdist_fn(XA, XB, out=out, **kwargs)\n", - " File \"/usr/local/lib/python3.10/dist-packages/scipy/spatial/distance.py\", line 1638, in __call__\n", - " cdist_fn(XA, XB, dm, **kwargs)\n", - "KeyboardInterrupt\n", - "^C\n" - ] - } + "outputs": [], + "source": [ + "!llm-semantic-annotator config.json compute_tag_chunk_similarities" ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 329 + }, + "id": "d7GB-u4C3eyz", + "outputId": "8e08fa54-9819-4bbc-f737-7ae7cb2494c3" + }, + "outputs": [], "source": [ "import os\n", "import tarfile\n", @@ -5984,38 +237,14 @@ "# Utilisation de la fonction\n", "directory_to_compress = \"config_workdir\"\n", "compress_and_download(directory_to_compress)\n" - ], - "metadata": { - "id": "d7GB-u4C3eyz", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 329 - }, - "outputId": "8e08fa54-9819-4bbc-f737-7ae7cb2494c3" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "error", - "ename": "FileNotFoundError", - "evalue": "[Errno 2] No such file or directory: 'config_workdir'", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[0;31m# Utilisation de la fonction\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0mdirectory_to_compress\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"config_workdir\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m \u001b[0mcompress_and_download\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdirectory_to_compress\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m\u001b[0m in \u001b[0;36mcompress_and_download\u001b[0;34m(directory_name)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;31m# Compression du répertoire\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtarfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marchive_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"w:gz\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mtar\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mtar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdirectory_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marcname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbasename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdirectory_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Compression terminée : {archive_name}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - 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"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'config_workdir'" - ] - } ] } ], "metadata": { + "accelerator": "TPU", "colab": { - "provenance": [], - "gpuType": "V28" + "gpuType": "V28", + "provenance": [] }, "kernelspec": { "display_name": "Python 3", @@ -6023,9 +252,8 @@ }, "language_info": { "name": "python" - }, - "accelerator": "TPU" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +}