𝗛𝗼𝘄 𝗜 𝗠𝗲𝘀𝘀𝗲𝗱 𝗨𝗽 𝗔𝗜 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴

𝗛𝗼𝘄 𝗜 𝗠𝗲𝘀𝘀𝗲𝗱 𝗨𝗽 𝗔𝗜 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴

I built an AI code review tool. I wanted real-time feedback. I failed several times before it worked.

My first version used a standard REST endpoint. The AI took too long. The frontend timed out. Users hated the speed.

I tried streaming. I stored the whole response in a buffer before sending it. This did not fix the lag.

Then I used Server-Sent Events. I did not handle the flow of data. Memory grew. Connections crashed.

I fixed it with these steps:

• I used FastAPI for async support.
• I used async generators to handle tokens.
• I sent tokens to the user immediately.
• I used asyncio.Queue to manage backpressure.

Lessons for you:

• Streaming adds complexity.
• Connections drop on weak networks. Build retry logic.
• Localhost tests hide problems. Test with real network lag.
• Avoid over-engineering. Start with a simple prototype.
• Use an event-driven setup for better scaling.

Streaming AI responses is a challenge of reliability.

Source: https://dev.to/__c1b9e06dc90a7e0a676b/how-i-messed-up-ai-streaming-and-how-you-can-avoid-it-11h6 Optional learning community: https://t.me/GyaanSetuAi