Quick Guide to Realtime Data in Azure OpenAI Service without Webhooks

Hey there, fellow JavaScript devs! Ready to dive into the world of real-time data with Azure OpenAI Service? Let's skip the fluff and get straight to the good stuff – polling for data like pros.

Introduction

Azure OpenAI Service is a powerhouse, but sometimes webhooks just aren't in the cards. No worries! We're going to tackle this with good old-fashioned polling. It's like checking your crush's social media every five minutes, but way more productive.

Setting up Azure OpenAI Service

First things first, let's get you set up:

1. Head to the Azure portal
2. Create an Azure OpenAI Service resource
3. Grab your API keys and endpoints

Easy peasy, right? Now let's get to the fun part.

Implementing Polling in JavaScript

Here's the basic structure we're working with:

function poll(fn, interval, maxAttempts) {
  let attempts = 0;

  const executePoll = async () => {
    const result = await fn();
    attempts++;

    if (result) {
      // We're done!
      return result;
    } else if (maxAttempts && attempts === maxAttempts) {
      // We've hit our limit
      throw new Error('Max attempts reached');
    } else {
      // Try again
      setTimeout(executePoll, interval);
    }
  };

  return executePoll();
}

Optimizing Polling for Azure OpenAI Service

Now, let's make this Azure-friendly with some adaptive polling:

function adaptivePolling(fn, initialInterval = 1000, maxInterval = 30000) {
  let interval = initialInterval;

  const executePoll = async () => {
    try {
      const result = await fn();
      if (result) return result;

      // Increase interval, but cap it
      interval = Math.min(interval * 2, maxInterval);
      setTimeout(executePoll, interval);
    } catch (error) {
      if (error.status === 429) {
        // Rate limited, back off
        interval = Math.min(interval * 2, maxInterval);
        setTimeout(executePoll, interval);
      } else {
        throw error;
      }
    }
  };

  return executePoll();
}

Fetching Data from Azure OpenAI Service

Let's put our polling to work:

const fetchCompletionStatus = async (operationId) => {
  const response = await fetch(`${AZURE_ENDPOINT}/operations/${operationId}`, {
    headers: { 'api-key': AZURE_API_KEY }
  });
  const data = await response.json();
  return data.status === 'succeeded' ? data : null;
};

adaptivePolling(() => fetchCompletionStatus('your-operation-id'))
  .then(result => console.log('Operation complete:', result))
  .catch(error => console.error('Polling failed:', error));

Processing and Updating UI

Keep your users in the loop:

function updateUI(data) {
  const statusElement = document.getElementById('status');
  statusElement.textContent = `Status: ${data.status}`;
  if (data.result) {
    const resultElement = document.getElementById('result');
    resultElement.textContent = data.result.text;
  }
}

adaptivePolling(() => fetchCompletionStatus('your-operation-id'))
  .then(result => {
    updateUI(result);
    console.log('Operation complete:', result);
  })
  .catch(error => {
    updateUI({ status: 'error' });
    console.error('Polling failed:', error);
  });

Error Handling and Resilience

Let's beef up our error handling:

function robustPolling(fn, maxAttempts = 5) {
  let attempts = 0;

  const executePoll = async () => {
    try {
      attempts++;
      const result = await fn();
      if (result) return result;
      if (attempts >= maxAttempts) throw new Error('Max attempts reached');
      await new Promise(resolve => setTimeout(resolve, 2000 * attempts));
      return executePoll();
    } catch (error) {
      if (error.status === 429 && attempts < maxAttempts) {
        await new Promise(resolve => setTimeout(resolve, 5000));
        return executePoll();
      }
      throw error;
    }
  };

  return executePoll();
}

Performance Considerations

Don't be a bandwidth hog. Let's add some caching:

const cache = new Map();

async function cachedFetch(url, options) {
  const cacheKey = `${url}${JSON.stringify(options)}`;
  if (cache.has(cacheKey)) {
    return cache.get(cacheKey);
  }
  const response = await fetch(url, options);
  const data = await response.json();
  cache.set(cacheKey, data);
  return data;
}

Alternatives to Polling

While we're all about polling today, keep Server-Sent Events and WebSockets in your back pocket for when you need that extra real-time oomph.

Conclusion

And there you have it! You're now armed and ready to tackle real-time data in Azure OpenAI Service without breaking a sweat. Remember, polling might not be the new kid on the block, but it's reliable, easy to implement, and gets the job done.

Now go forth and poll like a champ! 🚀