Analyzing an email with ChatGPT and saving the analysis as CAD

In this example, we'll use ChatGPT to analyze an email message, suggest a draft reply, and save the result so the agent can see it in Communication Panel.

For this integration, you'll need to configure the following:

• Endpoint URL: https://api.openai.com/v1/chat/completions

• Conversation Direction: Inbound

• Queues: Email queue

  You need to configure Extra Data Included When E-Mail Allocated for either the email channel (System Management > Channels > Email Channel > Extra Data Settings) or the email queue (Queue Management > [email queue] > Contact Management).

• Authentications:
  • Authentication ID: api-key
  • Secret: API key of the OpenAI platform
• JSON for Configuration

  This example uses an authentication header and the POST method for prompting ChatGPT to analyze a customer email and write a draft reply. It works on the email channel. The response saves the returned data, specified in the request. This data will then be visible as conversation attached data (CAD) to the agent in Communication Panel's Conversation Details extension. To show the data in its own AI analysis block in Conversation Details, see Using Extra Data in the System Configurator document.

  {
    "request": {
      "method": "POST",
      "headers": {
        "authorization": "Bearer {authentications.api-key}"
      },
      "body": {
        "model": "gpt-4o",
        "messages": [
          {
            "role": "user",
            "content": "Analyze the following email and provide the results in a JSON object with the following keys: Email language, Sentiment, Context, Summary, and Draft reply. The JSON object values should be in the original language of the email.\n\nSubject: {contact.email.subject}\n\nEmail: {contact.email.body}\n\nProvide the JSON object with these keys:\n\n{\n  \"Email language\": \"Detected language of the email.\",\n  \"Sentiment\": \"Customer sentiment in the email.\",\n  \"Context\": \"Context of the email in one word (Spam, Marketing, Service, etc).\",\n  \"Summary\": \"Compact summary of the email.\",\n  \"Draft reply\": \"Compact draft reply\"\n}"
          }
        ],
        "max_tokens": 1024,
        "response_format": {
          "type": "json_object"
        }
      }
    },
    "response": {
      "save": {
        "AI-analysis": "{response.body.choices[-1].message.content}"
      }
    }
  }