Batched Chat Completion Requests Only Process the First Prompt

Below is some insight regarding your experience with batching and the chat completion endpoint:

What’s Going On

The chat completion API is designed to work with a single conversation per request, where each conversation is expressed as a list of messages. Unlike the standard completions endpoint where you can pass an array of independent prompts, the chat model expects the conversation history (i.e., a properly structured list of messages) for a single chat turn. This design means that if you try to send multiple separate conversations in one request by batching them into a single prompt, only the first one may be processed correctly.

Workarounds and Community Experience

Some users have reported similar challenges when attempting to implement true batching with the chat endpoint. The workaround you mentioned—modifying the prompt to force additional completions—is one of the interim solutions many have tried. However, it’s acknowledged that this isn’t ideal for production use since it complicates the request structure and may lead to unpredictable behavior.

Next Steps

• Stay Updated: Since throughput improvements and batching are active areas of improvement, it’s a good idea to keep an eye on official OpenAI announcements or community forums for any updates or best practices specific to chat completions.
• Consider Alternatives: If throughput is critical and batching for chat completions isn’t providing the expected results, you might evaluate whether splitting the workload across multiple parallel requests or using the asynchronous Batch API (designed for handling large volumes of data) could be a viable alternative.
• Experiment and Report: Testing your production use case is key. Some have found creative ways to optimize throughput, but sharing your findings in developer communities can also help in getting broader insights.

Conclusion

In short, you’re not alone—several others have encountered this limitation with the chat completions endpoint. The workaround is currently one of the few options, but it indeed isn’t a perfect solution for every scenario. Monitoring updates from OpenAI and experimenting with alternative throughput strategies are the recommended paths forward.

I hope this helps clarify the situation!