Analysis

Based on current documentation and community observations, here are some points to consider regarding the issues you’re seeing with gpt-3.5-turbo-1106:

• Improved Instruction Following vs. Latency Trade-offs:
  The gpt-3.5-turbo-1106 model was designed with improved instruction-following capabilities, enhanced JSON mode, and reproducible outputs. However, these improvements sometimes come with trade-offs in token processing speed. This could be why you observe longer wait times or even errors like “I’m sorry, but I cannot fulfill that request” when processing your prompts.

• Server Load and Performance:
  There have been reports from other users noting that gpt-3.5-turbo-1106 can be slower. It’s possible that during periods of high demand, the model experiences increased latency, which might result in timeouts or incomplete processing of your request.

• Model Suitability for Specific Tasks:
  Your use case of revising emails may work better with the larger context window provided by gpt-3.5-turbo-16k, especially if the prompt structure or overall token count benefits from it. In latency-sensitive tasks, sometimes sticking with a model variant known for faster token processing might be preferable.

• Potential Next Steps:

  • Retry or Adjust Prompts: If you suspect server load, you might try reissuing the request during off-peak times. Alternatively, examine if slight modifications to the prompt structure could lead to more efficient processing.
  • Fallback Option: For now, if the 16k variant is working reliably, you may consider using that version for your email revision tasks until the performance of gpt-3.5-turbo-1106 stabilizes.
  • Monitor OpenAI Updates: Changes in performance metrics and potential optimizations are common as models receive updates. Monitoring OpenAI’s status updates or documentation might provide further insights or improvements.

Example Debugging Snippet

Below is an example snippet in JavaScript showing how you might set up a basic request and handle timeouts with the API:

JSXCopied
const axios = require('axios');

async function sendEmailRevisionRequest(prompt) {
  try {
    const response = await axios.post('https://api.openai.com/v1/chat/completions', {
      model: 'gpt-3.5-turbo-1106',
      messages: prompt,
      timeout: 10000, // set a 10 second timeout
    }, {
      headers: {
        'Content-Type': 'application/json',
        'Authorization': `Bearer YOUR_API_KEY`,
      }
    });
    console.log(response.data);
  } catch (error) {
    if (error.code === 'ECONNABORTED') {
      console.error('Request timed out');
    } else {
      console.error('Error:', error.response ? error.response.data : error.message);
    }
  }
}

// Your prompt chain might look similar to this
const promptChain = [
  { role: 'user', content: 'Below quoted in triple backticks are emails written for [charity]. Read the emails first and say "done" when finished.' },
  { role: 'user', content: 'Adapt the email as follows... [further instructions here]' }
];

sendEmailRevisionRequest(promptChain);

This snippet demonstrates setting a timeout to detect if the request is taking too long, which might help in diagnosing whether the issue is related to latency.

---

In summary, the performance differences you’re observing with gpt-3.5-turbo-1106 likely reflect the model’s increased capabilities and certain performance trade-offs. If consistent fast response times are critical for your application, consider using gpt-3.5-turbo-16k until performance improvements are made, or adjust your usage based on further feedback from OpenAI’s documentation and community updates.