refactor: Replace OpenAI API cal with Foundry SDK

Author: Avijit-Microsoft

infra/main.bicep

@@ -520,3 +520,4 @@ output AZURE_SQL_SERVER_USERNAME string = sqlServerEnabled ? servicesUsername :
 output AZURE_COSMOS_ACCOUNT_NAME string = cosmosDbEnabled ? cosmosDb.outputs.cosmosDBname : ''
 output SAMPLE_APP_URL string = deploySampleApp ? appService.outputs.uri : ''
 output AZURE_APP_SAMPLE_ENABLED bool = deploySampleApp
+output AZURE_AI_AGENT_ENDPOINT string = cognitiveServices.outputs.aiServicesEndpoint

infra/main.parameters.json

@@ -62,6 +62,9 @@
     "authClientSecret": {
       "value": "${AZURE_AUTH_CLIENT_SECRET}"
     },
+    "aiServicesEndpoint":{
+      "value": "${AZURE_AI_AGENT_ENDPOINT}"
+    },
     "aiEmbeddingModelDeployment": {
       "value": {
         "modelName": "text-embedding-3-small",

scripts/index_scripts/02_process_data.py

@@ -1,5 +1,6 @@
-from azure.identity import DefaultAzureCredential, get_bearer_token_provider
-from openai import AzureOpenAI
+from azure.identity import DefaultAzureCredential
+from azure.ai.inference import EmbeddingsClient
+from urllib.parse import urlparse
 import re
 import time
 from pypdf import PdfReader
@@ -10,28 +11,37 @@
 import requests
 
 search_endpoint = os.getenv("SEARCH_ENDPOINT")
-openai_endpoint = os.getenv("OPEN_AI_ENDPOINT_URL")
+ai_project_endpoint = os.getenv("AZURE_AI_AGENT_ENDPOINT")  # AI Foundry Project endpoint
 embedding_model_name = os.getenv("EMBEDDING_MODEL_NAME")
 embedding_model_api_version = os.getenv("EMBEDDING_MODEL_API_VERSION")
 use_local_files = (os.getenv("USE_LOCAL_FILES") == "true")
 index_name = "ai_app_index"
 
 print(f"Creating search index at {search_endpoint} with index name {index_name}")
-print(f"Using OpenAI endpoint: {openai_endpoint}")
+print(f"Using AI Foundry Project endpoint: {ai_project_endpoint}")
 print(f"Using embedding model: {embedding_model_name} with API version: {embedding_model_api_version}")
 
-# Function: Get Embeddings
-def get_embeddings(text: str, openai_endpoint: str, embedding_model_api_version: str):
+# Function: Get Embeddings using Azure AI Inference SDK with Foundry endpoint
+def get_embeddings(text: str, ai_project_endpoint: str, embedding_model_api_version: str):
     credential = DefaultAzureCredential()
-    token_provider = get_bearer_token_provider(credential,
-    "https://cognitiveservices.azure.com/.default")
-    client = AzureOpenAI(
-        api_version=embedding_model_api_version,
-        azure_endpoint=openai_endpoint,
-        azure_ad_token_provider=token_provider
+    
+    # Construct inference endpoint with /models path for Azure AI Foundry
+    inference_endpoint = f"https://{urlparse(ai_project_endpoint).netloc}/models"
+    
+    # Create embeddings client using Azure AI Inference SDK
+    embeddings_client = EmbeddingsClient(
+        endpoint=inference_endpoint,
+        credential=credential,
+        credential_scopes=["https://cognitiveservices.azure.com/.default"]
+    )
+    
+    # Create embeddings using the model name from environment
+    response = embeddings_client.embed(
+        model=embedding_model_name,
+        input=[text]
     )
 
-    embedding = client.embeddings.create(input=text, model=embedding_model_name).data[0].embedding
+    embedding = response.data[0].embedding
     return embedding
 
 # Function: Clean Spaces with Regex -
@@ -92,12 +102,12 @@ def prepare_search_doc(content, document_id, filename):
         chunk_id = document_id + '_' + str(chunk_num).zfill(2)
 
         try:
-            v_contentVector = get_embeddings(str(chunk), openai_endpoint, "2023-05-15")
+            v_contentVector = get_embeddings(str(chunk), ai_project_endpoint, embedding_model_api_version)
         except Exception as e:
             print(f"Error occurred: {e}. Retrying after 30 seconds...")
             time.sleep(30)
             try:
-                v_contentVector = get_embeddings(str(chunk), openai_endpoint, "1")
+                v_contentVector = get_embeddings(str(chunk), ai_project_endpoint, embedding_model_api_version)
             except Exception as e:
                 print(f"Retry failed: {e}. Setting v_contentVector to an empty list.")
                 v_contentVector = []

scripts/index_scripts/requirements.txt

@@ -1,4 +1,4 @@
-openai
+azure-ai-inference>=1.0.0b1
 pypdf
 # pyodbc
 tiktoken

scripts/postprovision.ps1

@@ -22,12 +22,12 @@ if (-not $virtualMachineId) {
     Write-Host "2. Navigate to the scripts directory: cd $PSScriptRoot"
     Write-Host "3. Run the below commands to process & ingest the sample data:"
     Write-Host "Set-ExecutionPolicy RemoteSigned -Scope CurrentUser"
-    Write-Host ".\process_sample_data.ps1 -SearchEndpoint '$env:AZURE_SEARCH_ENDPOINT' -OpenAiEndpoint '$env:AZURE_OPENAI_ENDPOINT' -EmbeddingModelName '$env:EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview' -UseLocalFiles `$true"
+    Write-Host ".\process_sample_data.ps1 -SearchEndpoint '$env:AZURE_SEARCH_ENDPOINT' -ProjectEndpoint '$env:AZURE_AI_AGENT_ENDPOINT' -EmbeddingModelName '$env:EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview' -UseLocalFiles `$true"
 } else {
     Write-Host "To ingest the sample data, follow these steps:"
     Write-Host "1. Login to the Virtual Machine using the username '$userName' and Password provided during deployment."
     Write-Host "2. Open the PowerShell terminal."
     Write-Host "3. Navigate to the scripts directory: cd C:\DataIngestionScripts"
     Write-Host "4. Run the following commands to process & ingest the sample data:"
-    Write-Host "powershell -ExecutionPolicy Bypass -File process_sample_data.ps1 -SearchEndpoint '$env:AZURE_SEARCH_ENDPOINT' -OpenAiEndpoint '$env:AZURE_OPENAI_ENDPOINT' -EmbeddingModelName '$env:EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview'"
+    Write-Host "powershell -ExecutionPolicy Bypass -File process_sample_data.ps1 -SearchEndpoint '$env:AZURE_SEARCH_ENDPOINT' -ProjectEndpoint '$env:AZURE_AI_AGENT_ENDPOINT' -EmbeddingModelName '$env:EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview'"
 }

scripts/postprovision.sh

@@ -19,12 +19,12 @@ if [ -z "$virtualMachineId" ]; then
   echo "1. Open the terminal."
   echo "2. Navigate to the scripts directory: cd $SCRIPT_DIR/scripts"
   echo "3. Run the following command to process the sample data:"
-  echo "./process_sample_data.sh '$AZURE_SEARCH_ENDPOINT' '$AZURE_OPENAI_ENDPOINT' '$EMBEDDING_MODEL_NAME' '2025-01-01-preview'"
+  echo "./process_sample_data.sh '$AZURE_SEARCH_ENDPOINT' '$AZURE_AI_AGENT_ENDPOINT' '$EMBEDDING_MODEL_NAME' '2025-01-01-preview'"
 else
   echo "To ingest the sample data, follow these steps:"
   echo "1. Login to the Virtual Machine using the username '$userName' and Password provided during deployment."
   echo "2. Open the PowerShell terminal."
   echo "3. Navigate to the scripts directory: cd C:\\DataIngestionScripts"
   echo "4. Run the following command to process the sample data:"
-  echo "powershell -ExecutionPolicy Bypass -File process_sample_data.ps1 -SearchEndpoint '$AZURE_SEARCH_ENDPOINT' -OpenAiEndpoint '$AZURE_OPENAI_ENDPOINT' -EmbeddingModelName '$EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview'"
+  echo "powershell -ExecutionPolicy Bypass -File process_sample_data.ps1 -SearchEndpoint '$AZURE_SEARCH_ENDPOINT' -ProjectEndpoint '$AZURE_AI_AGENT_ENDPOINT' -EmbeddingModelName '$EMBEDDING_MODEL_NAME' -EmbeddingModelApiVersion '2025-01-01-preview'"
 fi

scripts/process_sample_data.ps1

@@ -1,6 +1,6 @@
 param (
     [string]$SearchEndpoint,
-    [string]$OpenAiEndpoint,
+    [string]$ProjectEndpoint,
     [string]$EmbeddingModelName,
     [string]$EmbeddingModelApiVersion,
     [bool]$UseLocalFiles = $false
@@ -59,7 +59,7 @@ Write-Host "Using Python command: $pythonExe"
 
 # --- Set Environment Variables ---
 $env:SEARCH_ENDPOINT = $SearchEndpoint
-$env:OPEN_AI_ENDPOINT_URL = $OpenAiEndpoint
+$env:AZURE_AI_AGENT_ENDPOINT = $ProjectEndpoint
 $env:EMBEDDING_MODEL_NAME = $EmbeddingModelName
 $env:EMBEDDING_MODEL_API_VERSION = $EmbeddingModelApiVersion
 $env:USE_LOCAL_FILES = $UseLocalFiles.ToString().ToLower()

scripts/process_sample_data.sh

@@ -5,12 +5,12 @@ set -o pipefail
 
 # --- Input Parameters ---
 SearchEndpoint="$1"
-OpenAiEndpoint="$2"
+ProjectEndpoint="$2"
 EmbeddingModelName="$3"
 EmbeddingModelApiVersion="$4"
 
 if [ $# -ne 4 ]; then
-  echo "Usage: $0 <SearchEndpoint> <OpenAiEndpoint> <EmbeddingModelName> <EmbeddingModelApiVersion>"
+  echo "Usage: $0 <SearchEndpoint> <ProjectEndpoint> <EmbeddingModelName> <EmbeddingModelApiVersion>"
   exit 1
 fi
 
@@ -43,7 +43,7 @@ echo "$PROCESS_DATA_SCRIPT" | tee -a "$LOG_FILE"
 
 # --- Export environment variables ---
 export SEARCH_ENDPOINT="$SearchEndpoint"
-export OPEN_AI_ENDPOINT_URL="$OpenAiEndpoint"
+export AZURE_AI_AGENT_ENDPOINT="$ProjectEndpoint"
 export EMBEDDING_MODEL_NAME="$EmbeddingModelName"
 export EMBEDDING_MODEL_API_VERSION="$EmbeddingModelApiVersion"
 export USE_LOCAL_FILES="true"