phoenix-oss/llama-stack
1
0
Fork 0
forked from phoenix-oss/llama-stack-mirror
Code Pull requests Releases Packages 2 Activity Actions

Fix precommit check after moving to ruff (#927)

Browse source 
Lint check in main branch is failing. This fixes the lint check after we
moved to ruff in https://github.com/meta-llama/llama-stack/pull/921. We
need to move to a `ruff.toml` file as well as fixing and ignoring some
additional checks.

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
This commit is contained in:
Yuan Tang 2025-02-02 09:46:45 -05:00 • committed by GitHub
parent 4773092dd1
commit 34ab7a3b6c
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
217 changed files with 981 additions and 2681 deletions
Download patch file Download diff file Expand all files Collapse all files

18
llama_stack/providers/remote/vector_io/weaviate/weaviate.py
View file

@ -35,9 +35,9 @@ class WeaviateIndex(EmbeddingIndex):
self.collection_name = collection_name
async def add_chunks(self, chunks: List[Chunk], embeddings: NDArray):
assert len(chunks) == len(
embeddings
), f"Chunk length {len(chunks)} does not match embedding length {len(embeddings)}"
assert len(chunks) == len(embeddings), (
f"Chunk length {len(chunks)} does not match embedding length {len(embeddings)}"
)
data_objects = []
for i, chunk in enumerate(chunks):
@ -56,9 +56,7 @@ class WeaviateIndex(EmbeddingIndex):
# TODO: make this async friendly
collection.data.insert_many(data_objects)
async def query(
self, embedding: NDArray, k: int, score_threshold: float
) -> QueryChunksResponse:
async def query(self, embedding: NDArray, k: int, score_threshold: float) -> QueryChunksResponse:
collection = self.client.collections.get(self.collection_name)
results = collection.query.near_vector(
@ -85,9 +83,7 @@ class WeaviateIndex(EmbeddingIndex):
async def delete(self, chunk_ids: List[str]) -> None:
collection = self.client.collections.get(self.collection_name)
collection.data.delete_many(
where=Filter.by_property("id").contains_any(chunk_ids)
)
collection.data.delete_many(where=Filter.by_property("id").contains_any(chunk_ids))
class WeaviateMemoryAdapter(
@ -149,9 +145,7 @@ class WeaviateMemoryAdapter(
self.inference_api,
)
async def _get_and_cache_vector_db_index(
self, vector_db_id: str
) -> Optional[VectorDBWithIndex]:
async def _get_and_cache_vector_db_index(self, vector_db_id: str) -> Optional[VectorDBWithIndex]:
if vector_db_id in self.cache:
return self.cache[vector_db_id]