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CatalogMesh

CatalogMesh is a cross-platform AI workspace for product catalog operations: product-photo grouping, human review, SKU matching, exports, storage and guarded catalog automation.

Install

Requires Python 3.10 or newer.

python -m pip install --upgrade catalogmesh

Launch the desktop GUI:

catalogmesh-gui

Or use the main CLI:

catalogmesh --help

Optional runtimes:

python -m pip install "catalogmesh[local-embeddings]"
python -m pip install "catalogmesh[local-evidence]"
python -m pip install "catalogmesh[mcp]"

What CatalogMesh includes

  • Cloud vision providers: Gemini, OpenAI and Anthropic.
  • Ollama local vision and local-first/cloud-fallback workflows.
  • Crash-safe resumable product-photo grouping.
  • Non-destructive Review Center with human approval state.
  • Deterministic SKU/catalog candidate matching with mandatory human confirmation.
  • Safe offline Shopify/PIM exports.
  • Approval-aware Shopify, Akeneo and Odoo connector workflows.
  • Local-first rclone Storage Center.
  • Reports, benchmarks, environment management and automation tools.
  • English, Arabic and Chinese desktop localization.

Safety model

CatalogMesh never treats an AI guess as confirmed catalog identity. SKU confirmation remains human-controlled. Publication and remote connector mutations keep explicit approval/reservation boundaries, and MCP does not expose autonomous publication or generic remote mutation.

Compatibility

catalogmesh is the primary PyPI project name.

The historical package name ai-product-photo-sorter, legacy product-sorter-* command aliases and PRODUCT_SORTER_* settings were used by earlier v3.x releases. The command aliases and persisted configuration identifiers remain supported so existing local workflows are not unnecessarily broken.

Desktop builds

Ready-to-run Windows, Linux and macOS artifacts are published on the GitHub Releases page for the project repository.

Repository: https://github.com/mhmdwaelanwr/CatalogMesh

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