It is the most common deployment issue in LLM engineering today. You build a sophisticated RAG pipeline or a chat interface on your local machine. It works flawlessly. You push to Vercel. You type a prompt. The AI responds for exactly 10 or 15 seconds, and then the stream abruptly dies mid-sentence. No error appears in the browser console other than a generic network disconnect or JSON parsing error. The server logs usually show nothing because the execution context was essentially "kill -9'd" by the platform. Here is the architectural root cause and the specific configuration patterns required to fix it in Next.js App Router. The Architecture of a Timeout To fix this, you must understand the discrepancy between your local environment and Vercel’s serverless infrastructure. Localhost (Node.js): Your local server is a long-lived process. When you initiate a stream with streamText or OpenAIStream , the connection remains open indefinitely until the LLM finis...
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