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SN-87 (Include additional annotations for LLM notebook) (#1319)
Co-authored-by: ovalle15 <aovalle@Andreas-MacBook-Pro-2.local>
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‎examples/annotation_import/conversational.ipynb‎

Lines changed: 36 additions & 38 deletions
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@@ -140,11 +140,11 @@
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" )\n",
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")\n",
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"\n",
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"ner_annotation_ndjson = { \n",
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"ner_annotation_ndjson = {\n",
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" \"name\": \"ner\",\n",
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" \"location\": { \n",
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" \"start\": 0, \n",
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" \"end\": 8 \n",
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" \"location\": {\n",
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" \"start\": 0,\n",
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" \"end\": 8\n",
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" },\n",
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" \"messageId\": \"4\"\n",
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" }"
@@ -178,15 +178,15 @@
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{
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"metadata": {},
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"source": [
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"##### Checklist Classification ####### \n",
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"##### Checklist Classification #######\n",
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"\n",
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"checklist_annotation= lb_types.ClassificationAnnotation(\n",
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" name=\"checklist_convo\", # must match your ontology feature\"s name\n",
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" value=lb_types.Checklist(\n",
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" answer = [\n",
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" lb_types.ClassificationAnswer(\n",
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" name = \"first_checklist_answer\"\n",
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" ), \n",
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" ),\n",
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" lb_types.ClassificationAnswer(\n",
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" name = \"second_checklist_answer\"\n",
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" )\n",
@@ -215,7 +215,7 @@
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"######## Radio Classification ######\n",
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"\n",
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"radio_annotation = lb_types.ClassificationAnnotation(\n",
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" name=\"radio_convo\", \n",
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" name=\"radio_convo\",\n",
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" value=lb_types.Radio(answer = lb_types.ClassificationAnswer(name = \"first_radio_answer\")),\n",
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" message_id=\"0\"\n",
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")\n",
@@ -264,12 +264,12 @@
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" \"name\": \"first_checklist_answer\",\n",
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" \"classifications\" : [\n",
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" {\n",
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" \"name\": \"sub_checklist_question\", \n",
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" \"name\": \"sub_checklist_question\",\n",
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" \"answer\": {\n",
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" \"name\": \"first_sub_checklist_answer\"\n",
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" }\n",
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" } \n",
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" ] \n",
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" }\n",
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" ]\n",
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" }]\n",
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"}\n",
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"# Global\n",
@@ -360,27 +360,27 @@
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"metadata": {},
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"source": [
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"ontology_builder = lb.OntologyBuilder(\n",
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" tools=[ \n",
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" tools=[\n",
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" lb.Tool(tool=lb.Tool.Type.NER,name=\"ner\"),\n",
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" ], \n",
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" classifications=[ \n",
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" lb.Classification( \n",
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" ],\n",
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" classifications=[\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.TEXT,\n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" name=\"text_convo\"), \n",
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" lb.Classification( \n",
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" class_type=lb.Classification.Type.CHECKLIST, \n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" name=\"checklist_convo\", \n",
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" scope=lb.Classification.Scope.INDEX,\n",
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" name=\"text_convo\"),\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.CHECKLIST,\n",
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" scope=lb.Classification.Scope.INDEX,\n",
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" name=\"checklist_convo\",\n",
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" options=[\n",
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" lb.Option(value=\"first_checklist_answer\"),\n",
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" lb.Option(value=\"second_checklist_answer\") \n",
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" lb.Option(value=\"second_checklist_answer\")\n",
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" ]\n",
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" ), \n",
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" lb.Classification( \n",
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" class_type=lb.Classification.Type.RADIO, \n",
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" name=\"radio_convo\", \n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" ),\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.RADIO,\n",
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" name=\"radio_convo\",\n",
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" scope=lb.Classification.Scope.INDEX,\n",
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" options=[\n",
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" lb.Option(value=\"first_radio_answer\"),\n",
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" lb.Option(value=\"second_radio_answer\")\n",
@@ -395,7 +395,7 @@
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" options=[\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.CHECKLIST,\n",
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" name=\"sub_checklist_question\", \n",
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" name=\"sub_checklist_question\",\n",
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" options=[lb.Option(\"first_sub_checklist_answer\")]\n",
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" )\n",
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" ])\n",
@@ -438,10 +438,10 @@
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"metadata": {},
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"source": [
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"# Create Labelbox project\n",
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"project = client.create_project(name=\"Conversational Text Annotation Import Demo\", \n",
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"project = client.create_project(name=\"Conversational Text Annotation Import Demo\",\n",
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" media_type=lb.MediaType.Conversational)\n",
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"\n",
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"# Setup your ontology \n",
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"# Setup your ontology\n",
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"project.setup_editor(ontology) # Connect your ontology and editor to your project"
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],
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"cell_type": "code",
@@ -458,8 +458,6 @@
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{
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"metadata": {},
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"source": [
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"# Setup Batches and Ontology\n",
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"\n",
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"# Create a batch to send to your MAL project\n",
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"batch = project.create_batch(\n",
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" \"first-batch-convo-demo\", # Each batch in a project must have a unique name\n",
@@ -566,9 +564,9 @@
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"source": [
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"# Upload our label using Model-Assisted Labeling\n",
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"upload_job = lb.MALPredictionImport.create_from_objects(\n",
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" client = client, \n",
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" project_id = project.uid, \n",
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" name=f\"mal_job-{str(uuid.uuid4())}\", \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=f\"mal_job-{str(uuid.uuid4())}\",\n",
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" predictions=label)\n",
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"\n",
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"upload_job.wait_until_done()\n",
@@ -589,11 +587,11 @@
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{
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"metadata": {},
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"source": [
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"# Upload label for this data row in project \n",
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"# Upload label for this data row in project\n",
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"upload_job = lb.LabelImport.create_from_objects(\n",
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" client = client, \n",
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" project_id = project.uid, \n",
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" name=\"label_import_job\"+str(uuid.uuid4()), \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=\"label_import_job\"+str(uuid.uuid4()),\n",
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" labels=label)\n",
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"\n",
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"upload_job.wait_until_done()\n",

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