How I Turned One Prompt Engine Into 39 Sellable Products On A 2 GB Server

说明与用途

作者构建了一个管道，将单一向量提示引擎转换为39个可售产品，解决了元数据格式化和重复上传问题，全部在2 GB RAM服务器上运行。

问题

Metadata formatting mismatches and duplicate uploads caused failed bulk submissions to stock platforms, wasting time and risking account flags.

结果

The pipeline produced 39 sellable products from a single prompt engine, with 856 MB of finished output, while operating within strict 2 GB RAM constraints.

工作流

• Read asset folder and generate platform‑specific CSV headers with make_metadata.py
• Use upload_tracker.py to track pending and completed uploads, preventing double‑posting
• Convert Markdown guides to styled PDFs with md2pdf.py
• Package assets, covers, and thumbnails into zips with pack_product.py
• Upload packaged products to stock platforms

证据

Adobe wants exactly five columns in a specific order. Vecteezy wants four. Dreamstime wants fifteen.

来源

The fix is dumb and it works: a ledger.

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The whole thing ran on a single-core box with 2 GB of RAM and no GPU.

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