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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,158 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Populate Azure AI Search Index" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import os\n", | ||
| "import dotenv\n", | ||
| "import sys\n", | ||
| "\n", | ||
| "dotenv.load_dotenv(\".env\")\n", | ||
| "sys.path.append(os.path.join(os.getcwd(), \"..\", \"src\"))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Approach 1: Pull-based\n", | ||
| "\n", | ||
| "The pull model uses indexers connecting to a supported data source, automatically uploading the data into your index. This is the recommended approach for data sources that are frequently updated." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from search.utilities import SearchClient\n", | ||
| "\n", | ||
| "# Create search client\n", | ||
| "search_client = SearchClient(\n", | ||
| " search_endpoint=os.environ[\"AZURE_AI_SEARCH_ENDPOINT\"],\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Generate list of variables to be used in templates\n", | ||
| "template_variables = {\n", | ||
| " key: value for key, value in os.environ.items() if key.startswith((\"AZURE\"))\n", | ||
| "}\n", | ||
| "\n", | ||
| "# Define template paths\n", | ||
| "base_path = os.path.join(os.getcwd(), \"..\", \"src\", \"search\", \"templates\")\n", | ||
| "datasource_template_path = os.path.join(base_path, \"product-info\", \"datasource.json\")\n", | ||
| "index_template_path = os.path.join(base_path, \"product-info\", \"index.json\")\n", | ||
| "skillset_template_path = os.path.join(base_path, \"product-info\", \"skillset.json\")\n", | ||
| "indexer_template_path = os.path.join(base_path, \"product-info\", \"indexer.json\")\n", | ||
| "\n", | ||
| "# List of search assets\n", | ||
| "assets = [\n", | ||
| " {\n", | ||
| " \"type\": \"indexes\",\n", | ||
| " \"name\": os.environ[\"AZURE_AI_SEARCH_INDEX_NAME\"],\n", | ||
| " \"template_path\": index_template_path,\n", | ||
| " \"template_variables\": template_variables,\n", | ||
| " },\n", | ||
| " {\n", | ||
| " \"type\": \"datasources\",\n", | ||
| " \"name\": os.environ[\"AZURE_AI_SEARCH_DATASOURCE_NAME\"],\n", | ||
| " \"template_path\": datasource_template_path,\n", | ||
| " \"template_variables\": template_variables,\n", | ||
| " },\n", | ||
| " {\n", | ||
| " \"type\": \"skillsets\",\n", | ||
| " \"name\": os.environ[\"AZURE_AI_SEARCH_SKILLSET_NAME\"],\n", | ||
| " \"template_path\": skillset_template_path,\n", | ||
| " \"template_variables\": template_variables,\n", | ||
| " },\n", | ||
| " {\n", | ||
| " \"type\": \"indexers\",\n", | ||
| " \"name\": os.environ[\"AZURE_AI_SEARCH_INDEXER_NAME\"],\n", | ||
| " \"template_path\": indexer_template_path,\n", | ||
| " \"template_variables\": template_variables,\n", | ||
| " },\n", | ||
| "]\n", | ||
| "\n", | ||
| "# Load search asset templates\n", | ||
| "search_client.load_search_management_asset_templates(assets)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Create the index\n", | ||
| "index_response = search_client.create_search_management_asset(asset_type=\"indexes\")\n", | ||
| "\n", | ||
| "# Create the data source\n", | ||
| "datasource_response = search_client.create_search_management_asset(asset_type=\"datasources\")\n", | ||
| "\n", | ||
| "# Create skillset to enhance the indexer\n", | ||
| "skillset_response = search_client.create_search_management_asset(asset_type=\"skillsets\")\n", | ||
| "\n", | ||
| "# Create the indexer\n", | ||
| "indexer_response = search_client.create_search_management_asset(asset_type=\"indexers\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Run the indexer\n", | ||
| "indexer_run_response = search_client.run_indexer()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Run the indexer with reset\n", | ||
| "indexer_run_reset_response = search_client.run_indexer(reset_flag=True)" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "base", | ||
| "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": "3.11.4" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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