5 Commits

Author	SHA1	Message	Date
Roman Rizzi	89bcf9b1f0	FIX: Process succesfully generated embeddings even if some failed (#1500)	2025-07-10 17:51:01 -03:00
Rafael dos Santos Silva	6247906c13	FEATURE: Seamless embedding model upgrades (#1486)	2025-07-04 16:44:03 -03:00
Alan Guo Xiang Tan	01eced74a3	FIX: Ensure that we shutdown thread pool (#1207)	2025-03-21 11:08:36 +08:00
Roman Rizzi	f5cf1019fb	FEATURE: configurable embeddings (#1049) ... * Use AR model for embeddings features * endpoints * Embeddings CRUD UI * Add presets. Hide a couple more settings * system specs * Seed embedding definition from old settings * Generate search bit index on the fly. cleanup orphaned data * support for seeded models * Fix run test for new embedding * fix selected model not set correctly	2025-01-21 12:23:19 -03:00
Roman Rizzi	534b0df391	REFACTOR: Separation of concerns for embedding generation. (#1027) ... In a previous refactor, we moved the responsibility of querying and storing embeddings into the `Schema` class. Now, it's time for embedding generation. The motivation behind these changes is to isolate vector characteristics in simple objects to later replace them with a DB-backed version, similar to what we did with LLM configs.	2024-12-16 09:55:39 -03:00