phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-08-15 14:08:00 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

moar

Browse source
This commit is contained in:
Ashwin Bharambe 2025-08-12 14:54:01 -07:00
parent 61bffe8b56
commit 363dc83041
5 changed files with 9 additions and 4 deletions
Download patch file Download diff file Expand all files Collapse all files

2
llama_stack/core/build.py
View file

@ -91,7 +91,7 @@ def get_provider_dependencies(
def print_pip_install_help(config: BuildConfig): def print_pip_install_help(config: BuildConfig):
normal_deps, special_deps = get_provider_dependencies(config) normal_deps, special_deps, _ = get_provider_dependencies(config)
cprint( cprint(
f"Please install needed dependencies using the following commands:\n\nuv pip install {' '.join(normal_deps)}", f"Please install needed dependencies using the following commands:\n\nuv pip install {' '.join(normal_deps)}",

4
llama_stack/providers/remote/vector_io/qdrant/qdrant.py
View file

@ -266,7 +266,9 @@ class QdrantVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
) -> VectorStoreFileObject: ) -> VectorStoreFileObject:
# Qdrant doesn't allow multiple clients to access the same storage path simultaneously. # Qdrant doesn't allow multiple clients to access the same storage path simultaneously.
async with self._qdrant_lock: async with self._qdrant_lock:
await super().openai_attach_file_to_vector_store(vector_store_id, file_id, attributes, chunking_strategy) return await super().openai_attach_file_to_vector_store(
vector_store_id, file_id, attributes, chunking_strategy
)
async def delete_chunks(self, store_id: str, chunks_for_deletion: list[ChunkForDeletion]) -> None: async def delete_chunks(self, store_id: str, chunks_for_deletion: list[ChunkForDeletion]) -> None:
"""Delete chunks from a Qdrant vector store.""" """Delete chunks from a Qdrant vector store."""

3
llama_stack/providers/remote/vector_io/weaviate/weaviate.py
View file

@ -68,6 +68,7 @@ class WeaviateIndex(EmbeddingIndex):
data_objects.append( data_objects.append(
wvc.data.DataObject( wvc.data.DataObject(
properties={ properties={
"chunk_id": chunk.chunk_id,
"chunk_content": chunk.model_dump_json(), "chunk_content": chunk.model_dump_json(),
}, },
vector=embeddings[i].tolist(), vector=embeddings[i].tolist(),
@ -84,7 +85,7 @@ class WeaviateIndex(EmbeddingIndex):
sanitized_collection_name = sanitize_collection_name(self.collection_name, weaviate_format=True) sanitized_collection_name = sanitize_collection_name(self.collection_name, weaviate_format=True)
collection = self.client.collections.get(sanitized_collection_name) collection = self.client.collections.get(sanitized_collection_name)
chunk_ids = [chunk.chunk_id for chunk in chunks_for_deletion] chunk_ids = [chunk.chunk_id for chunk in chunks_for_deletion]
collection.data.delete_many(where=Filter.by_property("id").contains_any(chunk_ids)) collection.data.delete_many(where=Filter.by_property("chunk_id").contains_any(chunk_ids))
async def query_vector(self, embedding: NDArray, k: int, score_threshold: float) -> QueryChunksResponse: async def query_vector(self, embedding: NDArray, k: int, score_threshold: float) -> QueryChunksResponse:
sanitized_collection_name = sanitize_collection_name(self.collection_name, weaviate_format=True) sanitized_collection_name = sanitize_collection_name(self.collection_name, weaviate_format=True)

3
llama_stack/providers/utils/memory/openai_vector_store_mixin.py
View file

@ -37,6 +37,7 @@ from llama_stack.apis.vector_io import (
VectorStoreSearchResponse, VectorStoreSearchResponse,
VectorStoreSearchResponsePage, VectorStoreSearchResponsePage,
) )
from llama_stack.log import get_logger
from llama_stack.providers.utils.kvstore.api import KVStore from llama_stack.providers.utils.kvstore.api import KVStore
from llama_stack.providers.utils.memory.vector_store import ( from llama_stack.providers.utils.memory.vector_store import (
ChunkForDeletion, ChunkForDeletion,
@ -44,7 +45,7 @@ from llama_stack.providers.utils.memory.vector_store import (
make_overlapped_chunks, make_overlapped_chunks,
) )
logger = logging.getLogger(__name__) logger = get_logger(__name__, category="vector_io")
# Constants for OpenAI vector stores # Constants for OpenAI vector stores
CHUNK_MULTIPLIER = 5 CHUNK_MULTIPLIER = 5

1
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -592,6 +592,7 @@ def test_openai_vector_store_list_files(compat_client_with_empty_stores, client_
vector_store_id=vector_store.id, vector_store_id=vector_store.id,
file_id=file.id, file_id=file.id,
) )
assert response is not None
assert response.status == "completed", ( assert response.status == "completed", (
f"Failed to attach file {file.id} to vector store {vector_store.id}: {response=}" f"Failed to attach file {file.id} to vector store {vector_store.id}: {response=}"
) )