Merge pull request #33 from Azure-Samples/delegenz

Updating Service Creation, AML Config, and a few other items

Author: HeidiSteen

AzureML-Custom-Skill/notebook/custom_skill_azureml.ipynb

@@ -21,7 +21,7 @@
     "\n",
     "To train the aspect-based sentiment model, you will be using the [nlp recipes repository](https://github.com/microsoft/nlp-recipes/tree/master/examples/sentiment_analysis/absa). The model will then be deployed as an endpoint on an Azure Kubernetes cluster. Once deployed, the model is added to the enrichment pipeline as a custom skill for use by the Cognitive Search service.\n",
     "\n",
-    "There are two datasets provided. To train the model the larger of the two datasets, the hotel_reviews_1000.csv, is required. Prefer to skip the training step? Download the hotel_reviews_100.csv.\n",
+    "There are two datasets provided. To train the model the larger of the two datasets, the `hotel_reviews_1000.csv`, is required. Prefer to skip the training step? Download the `hotel_reviews_100.csv`.\n",
     "\n",
     "## Prerequisites\n",
     "\n",
@@ -177,16 +177,17 @@
     "\n",
     "headers = {'api-key': api_key, 'Content-Type': content_type}\n",
     "# Test out the URLs to ensure that the configuration works\n",
-    "print(construct_Url(search_service, \"indexes\", \"custom-ner\", \"analyze\", api_version))\n",
-    "print(construct_Url(search_service, \"indexes\", \"custom-ner\", None, api_version))\n",
+    "print(construct_Url(search_service, \"indexes\", \"azureml-sentiment\", \"analyze\", api_version))\n",
+    "print(construct_Url(search_service, \"indexes\", \"azureml-sentiment\", None, api_version))\n",
     "print(construct_Url(search_service, \"indexers\", None, None, api_version))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 1.1 Create datasource"
+    "## 1.1 Create datasource\n",
+    "Be sure to upload `hotel_reviews_1000.csv` or `hotel_reviews_100.csv` to your storage account before continuing."
    ]
   },
   {
@@ -195,17 +196,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Replace with the container name, storage account name, storage account connection string\n",
     "container = datasource_container\n",
     "\n",
-    "\n",
     "datsource_def = {\n",
     "    'name': f'{datasource_container}-ds',\n",
-    "    'description': f'km-aml solution accelerator- Datasource to label and extract custom entities from a corpus in STORAGEACCOUNTNAME, container datasource_container',\n",
+    "    'description': f'Datasource with hotel reviews',\n",
     "    'type': 'azureblob',\n",
     "    'subtype': None,\n",
     "    'credentials': {\n",
-    "        'connectionString': f'STORAGECONNSTRING'\n",
+    "        'connectionString': f'{STORAGECONNSTRING}'\n",
     "    },\n",
     "    'container': {\n",
     "        'name': f'{datasource_container}'\n",
@@ -233,8 +232,7 @@
    "source": [
     "skillset_name = f'{datasource_container}-ss'\n",
     "skillset_def = {\n",
-    "    '@odata.etag': '\\'0x8D7F6C769AC06B2\\'',\n",
-    "    'name': f'skillset_name',\n",
+    "    'name': f'{skillset_name}',\n",
     "    'description': 'Skillset to enrich hotel reviews with aspect based sentiment',\n",
     "    'skills': [\n",
     "        {\n",
@@ -482,16 +480,16 @@
     "    'cognitiveServices': {\n",
     "        '@odata.type': '#Microsoft.Azure.Search.CognitiveServicesByKey',\n",
     "        'description': '/subscriptions/subscription_id/resourceGroups/resource_group/providers/Microsoft.CognitiveServices/accounts/cog_svcs_acct',\n",
-    "        'key': f'cog_svcs_key'\n",
+    "        'key': f'{cog_svcs_key}'\n",
     "    },\n",
     "    'knowledgeStore': {\n",
-    "        'storageConnectionString': f'STORAGECONNSTRING',\n",
+    "        'storageConnectionString': f'{STORAGECONNSTRING}',\n",
     "        'projections': [\n",
     "            {\n",
     "                'tables': [],\n",
     "                'objects': [\n",
     "                    {\n",
-    "                        'storageContainer':  f'datasource_container-enriched',\n",
+    "                        'storageContainer':  f'{datasource_container}-enriched',\n",
     "                        'referenceKeyName': None,\n",
     "                        'generatedKeyName': None,\n",
     "                        'source': '/document/objectprojection',\n",
@@ -527,7 +525,7 @@
    "source": [
     "indexname = f'{datasource_container}-idx'\n",
     "index_def = {\n",
-    "    \"name\":f'indexname',\n",
+    "    \"name\":f'{indexname}',\n",
     "      \"defaultScoringProfile\": \"\",\n",
     "    \"fields\": [\n",
     "        {\n",
@@ -1024,7 +1022,7 @@
    "source": [
     "indexername = f'{datasource_container}-idxr'\n",
     "indexer_def = {\n",
-    "    \"name\": f'indexername',\n",
+    "    \"name\": f'{indexername}',\n",
     "    \"description\": \"Indexer to enrich hotel reviews\",\n",
     "    \"dataSourceName\": f'{datasource_container}-ds',\n",
     "    \"skillsetName\": f'{datasource_container}-ss',\n",
@@ -1076,7 +1074,7 @@
     "    ],\n",
     "    \"cache\": {\n",
     "        \"enableReprocessing\": True,\n",
-    "        \"storageConnectionString\": f'know_store_cache'\n",
+    "        \"storageConnectionString\": f'{know_store_cache}'\n",
     "    }\n",
     "}\n",
     "r = requests.post(construct_Url(search_service, \"indexers\", None, None, api_version), data=json.dumps(indexer_def),  headers=headers)\n",
@@ -1142,8 +1140,8 @@
    },
    "outputs": [],
    "source": [
-    "!pip install azure-storage-blob\n",
-    "!pip install --upgrade azureml-sdk"
+    "%pip install azure-storage-blob\n",
+    "%pip install --upgrade azureml-sdk"
    ]
   },
   {
@@ -1161,11 +1159,12 @@
    "source": [
     "from azureml.core import Workspace, Datastore\n",
     "try:\n",
-    "    ws = Workspace.from_config()\n",
+    "    ws = Workspace(subscription_id, resource_group, workspace_name)\n",
     "    print(ws.name, ws.location, ws.resource_group, ws.location, sep='\\t')\n",
     "    print('Library configuration succeeded')\n",
     "except:\n",
     "    print('Workspace not found')\n",
+    "    \n",
     "ds = ws.get_default_datastore()"
    ]
   },
@@ -1496,8 +1495,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "docs = [ \"Great\", \"The bathroom sink splashes water, need to be fixed. The bathtub/shower make loud noises. Other than that, it was a good stay.\" ]\n",
+    "%pip install git+https://github.com/NervanaSystems/nlp-architect.git@absa --user"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nlp_architect.models.absa.inference.inference import SentimentInference\n",
     "\n",
+    "aspect_lex_path = \"../models/hotel_aspect_lex.csv\"\n",
+    "opinion_lex_path = \"../models/hotel_opinion_lex_reranked.csv\"\n",
+    "inference = SentimentInference(aspect_lex_path, opinion_lex_path)\n",
+    "\n",
+    "docs = [ \"Great\", \"The bathroom sink splashes water, need to be fixed. The bathtub/shower make loud noises. Other than that, it was a good stay.\" ]\n",
     "sentiment_docs = []\n",
     "\n",
     "for doc_raw in docs:\n",
@@ -1772,7 +1785,7 @@
    "source": [
     "## Endpoint Deployed!\n",
     "\n",
-    "Next, add the endpoint in as a Azure ML skill. Either follow the instructions in (the tutorial)[https://docs.microsoft.com/azure/search/cognitive-search-tutorial-aml-custom-skill] to add the skill in the portal or continue through the notebook for the API experience.\n",
+    "Next, add the endpoint in as a Azure ML skill. Either follow the instructions in [the tutorial](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-aml-custom-skill) to add the skill in the portal or continue through the notebook for the API experience.\n",
     "\n",
     "## 4.0 Add AML Skill - Update Skillset"
    ]
@@ -1795,7 +1808,6 @@
    "outputs": [],
    "source": [
     "skillset_def = {\n",
-    "    '@odata.etag': '\\'0x8D7F6C769AC06B2\\'',\n",
     "    'name': f'{skillset_name}',\n",
     "    'description': 'Skillset to enrich hotel reviews with aspect based sentiment',\n",
     "    'skills': [\n",
@@ -2207,7 +2219,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,