Integrating OpenAI/ChatGPT with Power Pages

Integrating OpenAI’s ChatGPT with Power Pages enables you to provide intelligent, conversational experiences directly on your external-facing websites. Whether you’re creating a virtual assistant, knowledge bot, or automating responses to user queries, this integration elevates the user experience dramatically.

This guide walks through how to integrate ChatGPT into Power Pages, covering architectural overview, setup, API security, embedding techniques, and sample scenarios — all with practical detail.

1. Use Cases of ChatGPT in Power Pages

Here are some practical applications:

AI-powered virtual assistants for customer service
Conversational forms that guide users through processes
Product recommendation bots
Internal knowledge base agents for authenticated users
Natural language search within your portal content

2. Prerequisites

Before starting, ensure you have:

A Power Pages site already set up
Access to OpenAI API (via platform.openai.com)
Basic knowledge of JavaScript, Power Automate, and Dataverse
Environment variables or Azure Key Vault for securely storing API keys

3. Understanding the Architecture

There are three main ways to integrate ChatGPT into Power Pages:

Method	Description
JavaScript + API	Direct API call to OpenAI from portal JavaScript
Power Automate	Backend flow triggered by form input to get ChatGPT response
Custom Dataverse Table	Store queries and AI responses for tracking and analytics

4. Direct API Integration via JavaScript

Step 1: Get OpenAI API Key

Log into platform.openai.com
Navigate to API Keys, generate a key, and store it securely

Step 2: Create a Web Page and Script

In Power Pages studio, create a custom page
Insert an HTML form with a textbox and button
Add a Web Page Script with the following JavaScript:

<script>
async function askChatGPT() {
    const prompt = document.getElementById("userPrompt").value;
    const responseArea = document.getElementById("response");

    const result = await fetch("https://api.openai.com/v1/chat/completions", {
        method: "POST",
        headers: {
            "Authorization": "Bearer YOUR_OPENAI_API_KEY",
            "Content-Type": "application/json"
        },
        body: JSON.stringify({
            model: "gpt-3.5-turbo",
            messages: [{ role: "user", content: prompt }]
        })
    });

    const data = await result.json();
    responseArea.innerText = data.choices[0].message.content;
}
</script>

<div>
    <input type="text" id="userPrompt" placeholder="Ask something..." />
    <button onclick="askChatGPT()">Ask</button>
    <p id="response"></p>
</div>

Note: NEVER expose API keys in client-side code for production. This method is suitable for prototypes only.

5. Secure Integration via Power Automate

Step 1: Create a Power Automate Flow

Trigger: When a HTTP request is received
Action: HTTP (Premium)
- Method: POST
- URL: https://api.openai.com/v1/chat/completions
- Headers:
  - Authorization: Bearer YOUR_OPENAI_API_KEY
  - Content-Type: application/json
- Body:

{
  "model": "gpt-3.5-turbo",
  "messages": [
    {
      "role": "user",
      "content": "@{triggerBody()?['prompt']}"
    }
  ]
}

Respond with: ChatGPT’s reply

Step 2: Call Flow from Power Pages

In Power Pages, add a JavaScript fetch call to invoke the flow endpoint securely with an input
Optionally, use Dataverse or custom connector to manage access

6. Display the ChatGPT Responses

There are multiple ways to show the AI-generated reply:

Directly in an HTML element (<p> or <div>)
Populate a Dataverse table for logged user history
Use Power Pages Lists to show conversation logs per user
Trigger a custom modal or panel with the reply

7. Advanced Techniques

A. Contextual Chat (Session Memory)

Save conversation history in Dataverse and pass it back in each request as part of messages array

B. Role-based Prompt Engineering

Customize the bot’s tone or expertise based on user role

{ "role": "system", "content": "You are a professional IT support agent" }

C. Language Translation or Sentiment Analysis

Combine GPT responses with Azure Cognitive Services for multi-language support

8. Security & Best Practices

Avoid direct API key exposure in scripts — use a secure backend or Power Automate
Limit token usage using model parameters (max_tokens, temperature, etc.)
Use environment variables or Azure Key Vault to store keys
Implement rate limiting and logging via Dataverse or Azure Monitoring

9. Example Scenarios

Scenario	Description
FAQ Bot	Users ask common queries, and GPT responds based on trained context
Guided Form Assistant	GPT helps users fill long forms interactively
Personalized Recommendations	GPT suggests services or actions based on user profile
Helpdesk Agent	Conversational UI for ticket logging and follow-up

10. Maintenance and Monitoring

Monitor API usage on the OpenAI dashboard
Track user interaction in Dataverse
Retrain or enhance prompt design as needed
Add logging for debugging and compliance