Adding CQA Retriever
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const filter = {
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filterExpression: CQA_RetrieverSettings.filterExpression,
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};
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const embedding = new langchain.openai.AzureOpenAIEmbeddings({
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azureOpenAIApiInstanceName:
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CQA_RetrieverSettings.azure_openai_api.instance_name,
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azureOpenAIApiDeploymentName:
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CQA_RetrieverSettings.azure_openai_api.deployment_name,
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azureOpenAIApiVersion: CQA_RetrieverSettings.azure_openai_api.version,
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azureOpenAIApiKey: CQA_RetrieverSettings.azure_openai_api.key,
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});
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const store =
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new langchain.community.vectorstores.azure_aisearch.AzureAISearchVectorStore(
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embedding,
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{
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endpoint: CQA_RetrieverSettings.azure_aisearch.endpoint,
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key: CQA_RetrieverSettings.azure_aisearch.key,
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indexName: CQA_RetrieverSettings.azure_aisearch.index_name,
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search: {
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type: langchain.community.vectorstores.azure_aisearch
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.AzureAISearchQueryType.SimilarityHybrid,
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},
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}
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);
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function getSourceId(document) {
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if (document.metadata) {
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const mergedMetadata = Object.values(document.metadata).join("");
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const metatDataObj = JSON.parse(mergedMetadata);
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if ("sourceURL" in metatDataObj) {
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return metatDataObj.sourceURL;
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}
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if ("source" in metatDataObj) {
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return metatDataObj.source;
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}
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if ("source_id" in metatDataObj) {
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return metatDataObj.source_id;
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}
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if ("sourceName" in metatDataObj) {
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return metatDataObj.sourceName;
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}
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} else return "no source found";
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}
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return {
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async retrieve(query) {
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const resultDocuments = await store.similaritySearch(query, 20, filter);
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const sources = resultDocuments.map((doc) => ({
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source_id: getSourceId(doc),
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text: doc.pageContent,
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}));
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const cqaSources = {
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instances: [
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{
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sources: sources,
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question: query,
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generate_question: true,
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knowledgebase_description: "iva-vector-demo",
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extra_guidance: "",
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language_code: "en-GB",
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},
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],
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};
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if (CQA_RetrieverSettings.debug)
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console.log(JSON.stringify(cqaSources, null, 2));
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return cqaSources;
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},
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};
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{
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"azure_aisearch": {
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"endpoint": "https://iva-demo-vector-service.search.windows.net",
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"key": "<azure_aisearch_key>",
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"index_name": "iva-vector-demo"
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},
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"azure_openai_api": {
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"key": "<azure_openai_key>",
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"instance_name": "iva-open-ai",
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"deployment_name": "text-embedding-3-small",
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"embeddings_deployment_name": null,
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"version": "2024-08-01-preview"
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},
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"filterExpression": "search.in(company, 'Verint')",
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"debug": true
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}
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5
CQA_Retriever/_studio_dependencies/HubPackage.json
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5
CQA_Retriever/_studio_dependencies/HubPackage.json
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{
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"Name": "CQA Retriever",
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"Description": "Example of a RAG retriever using the CQA API",
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"OfficialVerintPackage": false
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}
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80
CQA_Retriever/_studio_dependencies/README.md
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80
CQA_Retriever/_studio_dependencies/README.md
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# CQA Retriever
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This package provides an example RAG process using Azure AI Search for Retrieval and the Verint DaVinci Contextual Question Answer (CQA) Service.
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## What's New: Updated [24/05/2025]
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- Initial Release
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## Setup Instructions
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### Prerequisites
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- This package requires the CQA Widget to be installed and configured.
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### Installation
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1. Copy the CQA_Retriever and CQA_RetieverSettings files into **Global Variables**
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2. _Optional:_ Import the Example Conversation Flow and Intent
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### Configuration
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#### CQA_RetieverSettings
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Fill out the settings below.
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```json
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{
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"azure_aisearch": {
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"endpoint": "https://iva-demo-vector-service.search.windows.net",
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"key": "<azure_aisearch_key>",
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"index_name": "iva-vector-demo"
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},
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"azure_openai_api": {
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"key": "<azure_openai_key>",
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"instance_name": "iva-open-ai",
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"deployment_name": "text-embedding-3-small",
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"embeddings_deployment_name": null,
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"version": "2024-08-01-preview"
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},
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"filterExpression": "search.in(company, 'Verint')",
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"debug": true
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}
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```
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## Package Content Details
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### CQA_RetieverSettings
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A global variable JSON object with environment-specific settings. See above for details.
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### CQA_Retriever
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A global variable function which handles the logic and API calls used to retrieve documents for Context.
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### Example code block that should be using in your Conversation Flows
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This is included in the Example Conversation Flow if you have imported that.
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```javascript
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(async () => {
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console.log(`CQA Retrieval: ${conversationData.cqa_question}`);
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conversationData.cqa_source = await CQA_Retriever().retrieve(
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conversationData.cqa_question
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);
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})()
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.catch((error) => {
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console.log(error.message);
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recognizedObject.answers.push(error.message);
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recognizedObject.errorInfo = {
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...recognizedObject.errorInfo,
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label: {
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data: error.toJSON ? error.toJSON() : {},
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message: error.message,
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},
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};
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})
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.finally(() => {
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next(0);
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});
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```
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