𝗦𝘁𝗼𝗽 𝗔𝗜 𝗔𝗣𝗜 𝗥𝗮𝘁𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝘄𝗶𝘁𝗵 𝗔𝘀𝘆𝗻𝗰 𝗤𝘂𝗲𝘂𝗲𝘀

𝗦𝘁𝗼𝗽 𝗔𝗜 𝗔𝗣𝗜 𝗥𝗮𝘁𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝘄𝗶𝘁𝗵 𝗔𝘀𝘆𝗻𝗰 𝗤𝘂𝗲𝘂𝗲𝘀

I tried to analyze 500 blog posts with an AI API. I got 429 Too Many Requests.

My first try used a sync loop. It worked. It took 83 minutes. Your users will not wait for this.

My second try used asyncio.gather. It sent 500 requests at once. The server blocked me in 3 seconds.

I needed a better way. I built an async task queue using asyncio.Queue.

The system does this:

• Limits concurrent requests to 5.
• Retries 429 errors.
• Uses exponential backoff with jitter.

Here are the lessons:

• Async handles I/O but you still need to throttle.
• Jitter stops all clients from retrying at the same time.
• Tune your concurrency limit. Start low and increase until you hit errors.

You have other options:

• Use a proxy for built-in rate limits.
• Use asyncio.Semaphore for simple tasks.
• Use the tenacity library for better retry logic.

Respect the server capacity. It keeps your app responsive.

How do you handle API throttling?

Source: https://dev.to/__c1b9e06dc90a7e0a676b/how-i-stopped-hitting-ai-api-rate-limits-with-a-simple-async-queue-11jp Optional learning community: https://t.me/GyaanSetuAi