llama-stack-mirror/llama_stack/providers
IAN MILLER faf891b40c
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refactor: use generic WeightedInMemoryAggregator for hybrid search in SQLiteVecIndex (#3303)
# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
The purpose of this PR is to refactor `SQLiteVecIndex` to eliminate
redundant code and simplify the code using generic
`WeightedInMemoryAggregator` that can be used for any vector db
provider. This pattern is already implemented for `PGVectorIndex` in
#3064

CC: @franciscojavierarceo 

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
1. `./scripts/unit-tests.sh`
2. Integration tests in CI Workflow
2025-09-02 10:38:35 -07:00
..
inline refactor: use generic WeightedInMemoryAggregator for hybrid search in SQLiteVecIndex (#3303) 2025-09-02 10:38:35 -07:00
registry feat: implement keyword, vector and hybrid search inside vector stores for PGVector provider (#3064) 2025-08-29 16:30:12 +02:00
remote docs: add VLM NIM example (#3277) 2025-08-29 16:23:52 -07:00
utils chore(migrate apis): move VectorDBWithIndex from embeddings to openai_embeddings (#3294) 2025-08-31 14:48:35 -07:00
__init__.py API Updates (#73) 2024-09-17 19:51:35 -07:00
datatypes.py feat: create unregister shield API endpoint in Llama Stack (#2853) 2025-08-05 07:33:46 -07:00