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I think image-encoder from CLIP (even smallest variant ViT B/32) is good enough to capture a lot of semantic information to allow natural language query once images are indexed. A lot of work actually goes into integrating with existing meta-data like local-directory, date-time to augment NL query and re-ranking the results.
I work on such a tool[0] to enable end to end indexing of user's personal photos and recently added functionality to index Google Photos too!
[0] https://github.com/eagledot/hachi
I haven't used it for search, but I believe Insightface's embeddings can be used for this purpose. https://insightface.ai/
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