# CQA Retriever

This package provides an example RAG process using Azure AI Search for Retrieval and the Verint DaVinci Contextual Question Answer (CQA) Service.

## What's New: Updated [24/05/2025]

- Initial Release

## Setup Instructions

### Prerequisites

- This package requires the CQA Widget to be installed and configured.

### Installation

1. Copy the CQA_Retriever and CQA_RetieverSettings files into **Global Variables**
2. _Optional:_ Import the Example Conversation Flow and Intent

### Configuration

#### CQA_RetieverSettings

Fill out the settings below.

```json
{
  "azure_aisearch": {
    "endpoint": "https://iva-demo-vector-service.search.windows.net",
    "key": "<azure_aisearch_key>",
    "index_name": "iva-vector-demo"
  },
  "azure_openai_api": {
    "key": "<azure_openai_key>",
    "instance_name": "iva-open-ai",
    "deployment_name": "text-embedding-3-small",
    "embeddings_deployment_name": null,
    "version": "2024-08-01-preview"
  },
  "filterExpression": "search.in(company, 'Verint')",
  "debug": true
}
```

## Package Content Details

### CQA_RetieverSettings

A global variable JSON object with environment-specific settings. See above for details.

### CQA_Retriever

A global variable function which handles the logic and API calls used to retrieve documents for Context.

### Example code block that should be using in your Conversation Flows

This is included in the Example Conversation Flow if you have imported that.

```javascript
(async () => {
  console.log(`CQA Retrieval: ${conversationData.cqa_question}`);
  conversationData.cqa_source = await CQA_Retriever().retrieve(
    conversationData.cqa_question
  );
})()
  .catch((error) => {
    console.log(error.message);
    recognizedObject.answers.push(error.message);
    recognizedObject.errorInfo = {
      ...recognizedObject.errorInfo,
      label: {
        data: error.toJSON ? error.toJSON() : {},
        message: error.message,
      },
    };
  })
  .finally(() => {
    next(0);
  });
```