From Prompt To 39 Products: A Metadata And Upload Tracking Pipeline For Stock Vector Sellers

Description and use

A pipeline for vector image sellers that generates metadata, tracks uploads, and packages products, successfully creating 39 items on a 1 vCPU, 2 GB RAM server.

Problem

Rejections from stock platforms due to incorrect CSV headers and duplicate uploads.

Outcome

Pipeline produced 39 finished products and 856 MB of output on a 1 vCPU, 2 GB RAM server, eliminating rejections and duplicate uploads.

Workflow

• Generate platform‑specific CSV with make_metadata.py
• Track uploads with upload_tracker.py to avoid duplicates
• Package assets into PDFs and zips with md2pdf.py and pack_product.py
• Maintain a fixed folder layout (assets/, output/, packs/, research/, scripts/)
• Run on a memory‑constrained server using single‑process, memory‑cleaning habits

Evidence

47 assets submitted to Adobe Stock, all bounced in one review pass. The CSV header was wrong.

Source

The script accepts a titles.json for exactly that reason.

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upload_tracker.py keeps a record of what you have already marked done.

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md2pdf.py converts Markdown to a styled PDF with real headings, tables, lists, and links, in one command. It uses reportlab, one of only two third‑party packages in the whole kit.

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Everything above ran on 1 vCPU, 2 GB RAM, no GPU.

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