refactor: migrate to new openai SDK (#73)

* refactor: migrate to new openai SDK

* chore: update deps

* refactor: improve upload errors

infra/main.bicep

@@ -30,6 +30,7 @@ param searchServiceSkuName string
 param openAiLocation string // Set in main.parameters.json
 param openAiSkuName string = 'S0'
 param openAiUrl string = ''
+param openAiApiVersion string // Set in main.parameters.json
 
 // Location is not relevant here as it's only for the built-in api
 // which is not used here. Static Web App is a global service otherwise
@@ -100,7 +101,8 @@ module api './core/host/functions.bicep' = {
     storageAccountName: storage.outputs.name
     managedIdentity: true
     appSettings: {
-      AZURE_OPENAI_API_ENDPOINT: finalOpenAiUrl
+      AZURE_OPENAI_API_INSTANCE_NAME: openAi.outputs.name
+      AZURE_OPENAI_API_VERSION: openAiApiVersion
       AZURE_OPENAI_API_DEPLOYMENT_NAME: chatDeploymentName
       AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME: embeddingsDeploymentName
       AZURE_AISEARCH_ENDPOINT: searchUrl
@@ -294,12 +296,10 @@ output AZURE_TENANT_ID string = tenant().tenantId
 output AZURE_RESOURCE_GROUP string = resourceGroup.name
 
 output AZURE_OPENAI_API_ENDPOINT string = finalOpenAiUrl
+output AZURE_OPENAI_API_INSTANCE_NAME string = openAi.outputs.name
+output AZURE_OPENAI_API_VERSION string = openAiApiVersion
 output AZURE_OPENAI_API_DEPLOYMENT_NAME string = chatDeploymentName
-output AZURE_OPENAI_API_MODEL string = chatModelName
-output AZURE_OPENAI_API_MODEL_VERSION string = chatModelVersion
 output AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME string = embeddingsDeploymentName
-output AZURE_OPENAI_API_EMBEDDINGS_MODEL string = embeddingsModelName
-output AZURE_OPENAI_API_EMBEDDINGS_MODEL_VERSION string = embeddingsModelVersion
 output AZURE_STORAGE_URL string = storageUrl
 output AZURE_STORAGE_CONTAINER_NAME string = blobContainerName
 output AZURE_AISEARCH_ENDPOINT string = searchUrl

infra/main.parameters.json

@@ -17,6 +17,9 @@
     "openAiLocation": {
       "value": "${AZURE_OPENAI_LOCATION=eastus2}"
     },
+    "openAiApiVersion": {
+      "value": "${AZURE_OPENAI_API_VERSION=2024-02-01}"
+    },
     "chatModelName": {
       "value": "${AZURE_OPENAI_API_MODEL=gpt-4}"
     },

packages/api/package.json

@@ -18,9 +18,9 @@
     "@azure/identity": "^4.2.0",
     "@azure/search-documents": "^12.0.0",
     "@azure/storage-blob": "^12.17.0",
-    "@langchain/azure-openai": "^0.0.8",
-    "@langchain/community": "^0.0.55",
+    "@langchain/community": "^0.0.57",
     "@langchain/core": "^0.1.61",
+    "@langchain/openai": "^0.0.31",
     "@microsoft/ai-chat-protocol": "^1.0.0-alpha.20240418.1",
     "dotenv": "^16.4.5",
     "faiss-node": "^0.5.1",

packages/api/src/functions/chat-post.ts

@@ -2,7 +2,7 @@ import { Readable } from 'node:stream';
 import { HttpRequest, InvocationContext, HttpResponseInit, app } from '@azure/functions';
 import { AIChatCompletionRequest, AIChatCompletionDelta } from '@microsoft/ai-chat-protocol';
 import { Document } from '@langchain/core/documents';
-import { AzureOpenAIEmbeddings, AzureChatOpenAI } from '@langchain/azure-openai';
+import { AzureOpenAIEmbeddings, AzureChatOpenAI } from '@langchain/openai';
 import { Embeddings } from '@langchain/core/embeddings';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { VectorStore } from '@langchain/core/vectorstores';
@@ -16,7 +16,7 @@ import { createRetrievalChain } from 'langchain/chains/retrieval';
 import 'dotenv/config';
 import { badRequest, data, serviceUnavailable } from '../http-response';
 import { ollamaChatModel, ollamaEmbeddingsModel, faissStoreFolder } from '../constants';
-import { getCredentials } from '../security';
+import { getAzureOpenAiTokenProvider, getCredentials } from '../security';
 
 const systemPrompt = `Assistant helps the Consto Real Estate company customers with questions and support requests. Be brief in your answers. Answer only plain text, DO NOT use Markdown.
 Answer ONLY with information from the sources below. If there isn't enough information in the sources, say you don't know. Do not generate answers that don't use the sources. If asking a clarifying question to the user would help, ask the question.
@@ -53,12 +53,14 @@ export async function postChat(request: HttpRequest, context: InvocationContext)
 
     if (azureOpenAiEndpoint) {
       const credentials = getCredentials();
+      const azureADTokenProvider = getAzureOpenAiTokenProvider();
+
       // Initialize models and vector database
-      embeddings = new AzureOpenAIEmbeddings({ credentials });
+      embeddings = new AzureOpenAIEmbeddings({ azureADTokenProvider });
       model = new AzureChatOpenAI({
         // Controls randomness. 0 = deterministic, 1 = maximum randomness
         temperature: 0.7,
-        credentials,
+        azureADTokenProvider,
       });
       store = new AzureAISearchVectorStore(embeddings, { credentials });
     } else {

packages/api/src/functions/documents-post.ts

@@ -1,5 +1,5 @@
 import { HttpRequest, HttpResponseInit, InvocationContext, app } from '@azure/functions';
-import { AzureOpenAIEmbeddings } from '@langchain/azure-openai';
+import { AzureOpenAIEmbeddings } from '@langchain/openai';
 import { PDFLoader } from 'langchain/document_loaders/fs/pdf';
 import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
 import { AzureAISearchVectorStore } from '@langchain/community/vectorstores/azure_aisearch';
@@ -9,7 +9,7 @@ import 'dotenv/config';
 import { BlobServiceClient } from '@azure/storage-blob';
 import { badRequest, serviceUnavailable, ok } from '../http-response';
 import { ollamaEmbeddingsModel, faissStoreFolder } from '../constants';
-import { getCredentials } from '../security';
+import { getAzureOpenAiTokenProvider, getCredentials } from '../security';
 
 export async function postDocuments(request: HttpRequest, context: InvocationContext): Promise<HttpResponseInit> {
   const storageUrl = process.env.AZURE_STORAGE_URL;
@@ -44,7 +44,10 @@ export async function postDocuments(request: HttpRequest, context: InvocationCon
     // Generate embeddings and save in database
     if (azureOpenAiEndpoint) {
       const credentials = getCredentials();
-      const embeddings = new AzureOpenAIEmbeddings({ credentials });
+      const azureADTokenProvider = getAzureOpenAiTokenProvider();
+
+      // Initialize embeddings model and vector database
+      const embeddings = new AzureOpenAIEmbeddings({ azureADTokenProvider });
       await AzureAISearchVectorStore.fromDocuments(documents, embeddings, { credentials });
     } else {
       // If no environment variables are set, it means we are running locally

packages/api/src/security.ts

@@ -1,4 +1,6 @@
-import { DefaultAzureCredential } from '@azure/identity';
+import { DefaultAzureCredential, getBearerTokenProvider } from '@azure/identity';
+
+const azureOpenAiScope = 'https://cognitiveservices.azure.com/.default';
 
 let credentials: DefaultAzureCredential | undefined;
 
@@ -9,3 +11,7 @@ export function getCredentials(): DefaultAzureCredential {
   credentials ||= new DefaultAzureCredential();
   return credentials;
 }
+
+export function getAzureOpenAiTokenProvider() {
+  return getBearerTokenProvider(getCredentials(), azureOpenAiScope);
+}

scripts/upload-documents.js

@@ -31,7 +31,7 @@ async function uploadDocuments(apiUrl, dataFolder) {
     }
     /* eslint-enable no-await-in-loop */
   } catch (error) {
-    console.error(error);
+    console.error(`Could not upload documents: ${error.message}`);
   }
 }