Help: Keyword Deduplication and De-Clutter

LrGeniusAI offers two complementary keyword management features to keep your Lightroom catalog clean:

Deduplicate Keyword Synonyms — an interactive workflow to find and merge near-duplicate or synonym keywords that already exist in your catalog.
Auto De-Clutter during Indexing — an automatic step inside Analyze & Index Photos that prevents newly AI-generated keywords from creating near-duplicates of what’s already in your catalog.

Deduplicate Keyword Synonyms

What it does

Scans your existing Lightroom keywords using AI semantic similarity to find groups of keywords that mean the same thing (e.g. Car / Automobile / Vehicle). For each group it picks one canonical name and lets you merge the others into it.

This is a catalog-modifying operation. Back up your catalog before running it.

How to run it

Library -> Plug-in Extras -> Deduplicate Keyword Synonyms...

The workflow has five steps:

Step 1 — Configuration

AI Model — choose which LLM validates the similarity clusters. Options: ChatGPT, Gemini, Ollama, LM Studio. If no key/server is configured, the task falls back to CLIP-only (no LLM validation).
Matching Strictness — slider from 0.70 to 0.98.
- Lower values (0.70) produce more suggestions and may include false positives.
- Higher values (0.98) are conservative; fewer but more certain matches.
- Default: 0.85. Your last-used value is remembered.
Backup confirmation — you must tick the checkbox confirming you have a backup before you can continue.

Step 2 — Select keyword branches

A list of all top-level keywords in your catalog is shown with checkboxes. Select the branches you want to scan.

Only leaf keywords (keywords with no children) are considered for deduplication. Category keywords with sub-keywords are never touched.

Step 3 — AI clustering (background)

For each selected branch the plugin:

Generates CLIP/SigLIP semantic embeddings for all leaf keyword names.
Builds a similarity matrix and groups keywords using complete-linkage clustering: a keyword joins a cluster only if it is above the threshold with every existing member. This prevents false chains where A≈B and B≈C but A is unrelated to C.
Optionally submits candidate clusters to the selected LLM for refinement. The LLM is instructed to:
- Keep only true synonyms (e.g. Car / Automobile).
- Split groups that contain related-but-distinct concepts (e.g. Cat vs Kitten).
- Put the clearest, most common name first — this becomes the canonical name.

If the LLM call fails, the CLIP-only clusters are used as a fallback.

Step 4 — Preview and approve

A list of all proposed merge pairs is shown:

"Automobile"  →  "Car"
"Vehicle"     →  "Car"
"Pic"         →  "Photo"

Deselect any pair you want to keep separate. When satisfied, click Merge.

There is also a Sync backend checkbox (recommended on). When checked, the backend’s ChromaDB metadata is updated so that semantic search and future AI operations reflect the merged keywords.

Step 5 — Execution

For each approved pair:

All photos tagged with the duplicate keyword are re-tagged with the canonical keyword.
The duplicate keyword tag is removed from those photos.
The now-empty duplicate keyword remains in the catalog keyword list with 0 photos. To purge it, use Lightroom’s built-in Metadata → Purge Unused Keywords.

A summary is shown at the end: how many keywords were merged, how many pairs were skipped, and how many backend records were updated.

Auto De-Clutter during Indexing

What it does

When Analyze & Index Photos generates new keywords, the de-clutter step compares those new keywords against what’s already in your catalog. If a new keyword is semantically near-identical to an existing one, it is replaced by the existing one before anything is written to Lightroom.

This means: if your catalog already has Car and the AI generates Automobile, the photo receives Car, not a second keyword entry.

When it runs

Automatically, as part of the Apply Metadata phase inside Analyze & Index Photos — no separate action needed. It only runs when new keywords are being written.

What the validation dialog shows

If any replacements were made, the keyword validation dialog shows a two-column view:

Generated (AI)		De-cluttered (final)
Automobile	→	Car
Vehicle	→	Car
Tree		Tree

Left column: what the AI originally produced.
Right column: what will actually be written to Lightroom (editable).
An arrow is shown only when the name was changed.
A label below the list shows the total number of merges applied.

You can edit any entry in the right column before confirming.

How the canonical name is chosen

Existing catalog keywords always win over newly generated ones. If the AI generates a keyword that already exists in the catalog (case-insensitively), the existing form is used as-is. If multiple new keywords cluster together and none already exists in the catalog, the first member of the cluster is used as the canonical name.

Tips

Run Deduplicate Keyword Synonyms after a large initial indexing run. A freshly indexed catalog often has synonym sprawl that is easiest to clean up in one batch before you build more keyword structure on top of it.
Use a higher strictness (0.90+) with LLM validation for precise taxonomies (wildlife, botany, places). Use lower strictness (0.75–0.85) with CLIP-only if you want a fast first pass and are happy to review more suggestions manually.
De-clutter is CLIP-only (no LLM call) to keep indexing latency low. For finer control, run the interactive Deduplicate task afterwards.
Back up your catalog before running the interactive deduplication. The merge step modifies keyword assignments across potentially thousands of photos and cannot be undone automatically.
After a merge run, use Metadata → Purge Unused Keywords in Lightroom to remove the now-empty duplicate entries from the keyword list.

Preferences persisted across runs

Preference	Description
Matching Strictness	Last-used slider value (0.70–0.98).
AI Model	Last-selected LLM provider and model.