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{
"cells": [
{
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"metadata": {},
"outputs": [
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"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n",
"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
" warnings.warn(\n",
"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
" warnings.warn(msg)\n",
"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/torch/functional.py:512: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3587.)\n",
" return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]\n",
"Using CPU. Note: This module is much faster with a GPU.\n",
"Using CPU. Note: This module is much faster with a GPU.\n",
"Using CPU. Note: This module is much faster with a GPU.\n",
"Using CPU. Note: This module is much faster with a GPU.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tool_calls:[ChatCompletionMessageToolCall(id='call_2UKpohzEX3jid2f0RgsAfDYF', function=Function(arguments='{\"image_path\":\"path/to/reaction_image.png\"}', name='process_reaction_image_with_table_R_group'), type='function')]\n"
]
},
{
"name": "stderr",
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"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
" warnings.warn(\n",
"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None\n",
" warnings.warn(\n",
"Config of the encoder: <class 'transformers.models.bert.modeling_bert.BertModel'> is overwritten by shared encoder config: BertConfig {\n",
" \"attention_probs_dropout_prob\": 0.1,\n",
" \"classifier_dropout\": null,\n",
" \"hidden_act\": \"gelu\",\n",
" \"hidden_dropout_prob\": 0.1,\n",
" \"hidden_size\": 256,\n",
" \"initializer_range\": 0.02,\n",
" \"intermediate_size\": 1024,\n",
" \"layer_norm_eps\": 1e-12,\n",
" \"max_position_embeddings\": 1764,\n",
" \"model_type\": \"bert\",\n",
" \"num_attention_heads\": 4,\n",
" \"num_hidden_layers\": 4,\n",
" \"pad_token_id\": 0,\n",
" \"position_embedding_type\": \"absolute\",\n",
" \"transformers_version\": \"4.47.0\",\n",
" \"type_vocab_size\": 2,\n",
" \"use_cache\": true,\n",
" \"vocab_size\": 2094\n",
"}\n",
"\n",
"Config of the decoder: <class 'transformers.models.bert.modeling_bert.BertLMHeadModel'> is overwritten by shared decoder config: BertConfig {\n",
" \"add_cross_attention\": true,\n",
" \"attention_probs_dropout_prob\": 0.1,\n",
" \"classifier_dropout\": null,\n",
" \"hidden_act\": \"gelu\",\n",
" \"hidden_dropout_prob\": 0.1,\n",
" \"hidden_size\": 256,\n",
" \"initializer_range\": 0.02,\n",
" \"intermediate_size\": 1024,\n",
" \"is_decoder\": true,\n",
" \"layer_norm_eps\": 1e-12,\n",
" \"max_position_embeddings\": 1764,\n",
" \"model_type\": \"bert\",\n",
" \"num_attention_heads\": 4,\n",
" \"num_hidden_layers\": 4,\n",
" \"pad_token_id\": 0,\n",
" \"position_embedding_type\": \"absolute\",\n",
" \"transformers_version\": \"4.47.0\",\n",
" \"type_vocab_size\": 2,\n",
" \"use_cache\": true,\n",
" \"vocab_size\": 2094\n",
"}\n",
"\n",
"Using CPU. Note: This module is much faster with a GPU.\n",
"/home/chenyufan/anaconda3/envs/openchemie/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:818: UserWarning: `return_dict_in_generate` is NOT set to `True`, but `output_hidden_states` is. When `return_dict_in_generate` is not `True`, `output_hidden_states` is ignored.\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
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" \"entry\": 10,\n",
" \"yield\": \"36%\"\n",
" }\n",
" ]\n",
" },\n",
" {\n",
" \"reaction_id\": \"11_1\",\n",
" \"reactants\": [\n",
" {\n",
" \"smiles\": \"[H]CC(=O)C#Cc1ccccc1\",\n",
" \"label\": \"1k\"\n",
" },\n",
" {\n",
" \"smiles\": \"N#CC(=Cc1ccc(Cl)cc1Cl)C(=O)c1ccccc1\",\n",
" \"label\": \"2k\"\n",
" }\n",
" ],\n",
" \"conditions\": [\n",
" {\n",
" \"role\": \"reagent\",\n",
" \"text\": \"DABCO (100 mol %)\"\n",
" },\n",
" {\n",
" \"role\": \"solvent\",\n",
" \"text\": \"ethylene glycol/toluene = 2:1\"\n",
" },\n",
" {\n",
" \"role\": \"temperature\",\n",
" \"text\": \"60 \\u00b0C\"\n",
" },\n",
" {\n",
" \"role\": \"time\",\n",
" \"text\": \"48 h\"\n",
" },\n",
" {\n",
" \"role\": \"yield\",\n",
" \"text\": \"66%\"\n",
" }\n",
" ],\n",
" \"products\": [\n",
" {\n",
" \"smiles\": \"[H]C1C(=O)/C=C(/c2ccccc2)O/C(c2ccccc2)=C(/C#N)C1c1ccc(Cl)cc1Cl\",\n",
" \"label\": \"3k\"\n",
" }\n",
" ],\n",
" \"additional_info\": [\n",
" {\n",
" \"entry\": 11,\n",
" \"yield\": \"66%\"\n",
" }\n",
" ]\n",
" }\n",
" ]\n",
"}\n"
]
}
],
"source": [
"import json\n",
"from main import ChemEagle\n",
"image_path = './examples/img1.png'\n",
"results = ChemEagle(image_path)\n",
"print(json.dumps(results, indent=4))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "openchemie",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|