Move LTC and MLTC to Python 3.12

metadata/LightTextClassification__8__metadata.json

@@ -0,0 +1,24 @@
+{
+    "name": "LightTextClassification",
+    "retrainable": true,
+    "gpu": 0,
+    "processorType": "CPU",
+    "description": "This is a generic, retrainable model for text classification. It supports all languages based on Latin characters, such as English, French, Spanish, and others. This ML Package must be trained, and if deployed without training first, the deployment will fail with an error stating that the model is not trained. This model operates on bag of Words and supports two variations of algorithms, one based on Logistic Regression and the other one based on Random Forest. You can switch between these two algorithms using environment variables.",
+    "inputDescription": "Text that would be classified.",
+    "outputDescription": "A JSON with predicted class name, associated confidence on that class prediction (between 0-1) and ngrams in the input that affected the prediction (optional)",
+    "changeLog": "Move to Python3.12",
+    "cpu": 1,
+    "inputType": "JSON",
+    "displayName": "LightTextClassification",
+    "memory": 0,
+    "mlPackageLanguage": "PYTHON312",
+    "projectId": "[project-id]",
+    "stagingUri": "[staging-uri]",
+    "projectName": "UiPath Language Analysis",
+    "projectDescription": "Curated Models from UiPath to analyze language in Emails, Documents, Web Pages, Text Messages, Portals and more",
+    "tenantName": "UiPath",
+    "minAIFabricVersion": "v23.10",
+    "version": 8,
+    "customVersion":  "25.9.0",
+    "contentUri": "https://<placeholder-url>/publicmodels/AIC/LightTextClassification/25.9.0/bow_text_classifier_package.zip"
+}

metadata/MultiLingualTextClassification__6__metadata.json

@@ -0,0 +1,24 @@
+{
+    "name": "MultiLingualTextClassification",
+    "retrainable": true,
+    "gpu": 0,
+    "processorType": "CPU",
+    "description": "This is a generic, retrainable model for text classification. It supports the top 100 Wikipedia languages listed here (https://docs.uipath.com/ai-fabric/v0/docs/multi-lingual-text-classification#languages). This ML Package must be trained, and if deployed without training first, the deployment will fail with an error stating that the model is not trained. It is based on BERT, a self-supervised method for pretraining natural language processing systems. A GPU is recommended especially during training. A GPU delivers ~5-10x improvement in speed.",
+    "inputDescription": "Text that would be classified",
+    "outputDescription": "A JSON with predicted class name, associated confidence on that class prediction (between 0-1).",
+    "changeLog": "Move to Python3.12",
+    "cpu": 1,
+    "inputType": "JSON",
+    "displayName": "MultiLingualTextClassification",
+    "memory": 0,
+    "mlPackageLanguage": "PYTHON312",
+    "projectId": "[project-id]",
+    "stagingUri": "[staging-uri]",
+    "projectName": "UiPath Language Analysis",
+    "projectDescription": "Curated Models from UiPath to analyze language in Emails, Documents, Web Pages, Text Messages, Portals and more",
+    "tenantName": "UiPath",
+    "minAIFabricVersion": "v23.10",
+    "version": 6,
+    "customVersion":  "25.9.0",
+    "contentUri": "https://<placeholder-url>/publicmodels/AIC/MultiLingualTextClassification/25.9.0/bert_text_classifier_package.zip"
+}