llama-stack-mirror/llama_stack
skamenan7 f9afad99f8 docs: update configuration documentation for global default embedding model
- Clarified the optional nature of the default_embedding_dimension in the YAML configuration, specifying that it defaults to 384 if omitted.
- Added a note in the VectorStoreConfig class to indicate that the router will fall back to 384 as the default dimension if not set.
2025-09-18 10:11:44 -04:00
..
apis docs: update configuration documentation for global default embedding model 2025-09-18 10:11:44 -04:00
cli feat: migrate to FIPS-validated cryptographic algorithms (#3423) 2025-09-12 11:18:19 +02:00
core feat(vector-io): implement global default embedding model configuration (Issue #2729) 2025-09-18 10:11:44 -04:00
distributions feat(vector-io): implement global default embedding model configuration (Issue #2729) 2025-09-18 10:11:44 -04:00
models refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
providers feat: combine ProviderSpec datatypes (#3378) 2025-09-18 16:10:00 +02:00
strong_typing chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
testing chore(recorder): update mocks to be closer to non-mock environment (#3442) 2025-09-15 15:25:53 -04:00
ui build: Bump version to 0.2.22 2025-09-16 19:44:03 +00:00
__init__.py chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
env.py refactor(test): move tools, evals, datasetio, scoring and post training tests (#1401) 2025-03-04 14:53:47 -08:00
log.py chore(pre-commit): add pre-commit hook to enforce llama_stack logger usage (#3061) 2025-08-20 07:15:35 -04:00
schema_utils.py feat(auth): API access control (#2822) 2025-07-24 15:30:48 -07:00