chore: Consistent naming for VectorIO providers

llama_stack/apis/telemetry/telemetry.py

@@ -13,8 +13,8 @@
     Literal,
     Optional,
     Protocol,
-    runtime_checkable,
     Union,
+    runtime_checkable,
 )
 
 from llama_models.llama3.api.datatypes import Primitive

llama_stack/providers/inline/vector_io/chroma/__init__.py

@@ -8,10 +8,10 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import ChromaInlineImplConfig
+from .config import ChromaVectorIOConfig
 
 
-async def get_provider_impl(config: ChromaInlineImplConfig, deps: Dict[Api, ProviderSpec]):
+async def get_provider_impl(config: ChromaVectorIOConfig, deps: Dict[Api, ProviderSpec]):
     from llama_stack.providers.remote.vector_io.chroma.chroma import (
         ChromaVectorIOAdapter,
     )

llama_stack/providers/inline/vector_io/chroma/config.py

@@ -9,7 +9,7 @@
 from pydantic import BaseModel
 
 
-class ChromaInlineImplConfig(BaseModel):
+class ChromaVectorIOConfig(BaseModel):
     db_path: str
 
     @classmethod

llama_stack/providers/inline/vector_io/faiss/__init__.py

@@ -8,14 +8,14 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import FaissImplConfig
+from .config import FaissVectorIOConfig
 
 
-async def get_provider_impl(config: FaissImplConfig, deps: Dict[Api, ProviderSpec]):
-    from .faiss import FaissVectorIOImpl
+async def get_provider_impl(config: FaissVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .faiss import FaissVectorIOAdapter
 
-    assert isinstance(config, FaissImplConfig), f"Unexpected config type: {type(config)}"
+    assert isinstance(config, FaissVectorIOConfig), f"Unexpected config type: {type(config)}"
 
-    impl = FaissVectorIOImpl(config, deps[Api.inference])
+    impl = FaissVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/inline/vector_io/faiss/config.py

@@ -16,7 +16,7 @@
 
 
 @json_schema_type
-class FaissImplConfig(BaseModel):
+class FaissVectorIOConfig(BaseModel):
     kvstore: KVStoreConfig
 
     @classmethod

llama_stack/providers/inline/vector_io/faiss/faiss.py

@@ -24,7 +24,7 @@
     VectorDBWithIndex,
 )
 
-from .config import FaissImplConfig
+from .config import FaissVectorIOConfig
 
 logger = logging.getLogger(__name__)
 
@@ -112,8 +112,8 @@ async def query(self, embedding: NDArray, k: int, score_threshold: float) -> Que
         return QueryChunksResponse(chunks=chunks, scores=scores)
 
 
-class FaissVectorIOImpl(VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: FaissImplConfig, inference_api: Api.inference) -> None:
+class FaissVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
+    def __init__(self, config: FaissVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
         self.cache = {}

llama_stack/providers/remote/vector_io/chroma/__init__.py

@@ -8,10 +8,10 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import ChromaRemoteImplConfig
+from .config import ChromaVectorIOConfig
 
 
-async def get_adapter_impl(config: ChromaRemoteImplConfig, deps: Dict[Api, ProviderSpec]):
+async def get_adapter_impl(config: ChromaVectorIOConfig, deps: Dict[Api, ProviderSpec]):
     from .chroma import ChromaVectorIOAdapter
 
     impl = ChromaVectorIOAdapter(config, deps[Api.inference])

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -16,13 +16,12 @@
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
-from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
 from llama_stack.providers.utils.memory.vector_store import (
     EmbeddingIndex,
     VectorDBWithIndex,
 )
 
-from .config import ChromaRemoteImplConfig
+from .config import ChromaVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -89,7 +88,7 @@ async def delete(self):
 class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(
         self,
-        config: Union[ChromaRemoteImplConfig, ChromaInlineImplConfig],
+        config: Union[ChromaVectorIOConfig, ChromaVectorIOConfig],
         inference_api: Api.inference,
     ) -> None:
         log.info(f"Initializing ChromaVectorIOAdapter with url: {config}")
@@ -100,7 +99,7 @@ def __init__(
         self.cache = {}
 
     async def initialize(self) -> None:
-        if isinstance(self.config, ChromaRemoteImplConfig):
+        if isinstance(self.config, ChromaVectorIOConfig):
             log.info(f"Connecting to Chroma server at: {self.config.url}")
             url = self.config.url.rstrip("/")
             parsed = urlparse(url)

llama_stack/providers/remote/vector_io/chroma/config.py

@@ -9,7 +9,7 @@
 from pydantic import BaseModel
 
 
-class ChromaRemoteImplConfig(BaseModel):
+class ChromaVectorIOConfig(BaseModel):
     url: str
 
     @classmethod

llama_stack/providers/remote/vector_io/pgvector/__init__.py

@@ -8,12 +8,12 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import PGVectorConfig
+from .config import PGVectorVectorIOConfig
 
 
-async def get_adapter_impl(config: PGVectorConfig, deps: Dict[Api, ProviderSpec]):
-    from .pgvector import PGVectorVectorDBAdapter
+async def get_adapter_impl(config: PGVectorVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .pgvector import PGVectorVectorIOAdapter
 
-    impl = PGVectorVectorDBAdapter(config, deps[Api.inference])
+    impl = PGVectorVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/pgvector/config.py

@@ -9,7 +9,7 @@
 
 
 @json_schema_type
-class PGVectorConfig(BaseModel):
+class PGVectorVectorIOConfig(BaseModel):
     host: str = Field(default="localhost")
     port: int = Field(default=5432)
     db: str = Field(default="postgres")

llama_stack/providers/remote/vector_io/pgvector/pgvector.py

@@ -22,7 +22,7 @@
     VectorDBWithIndex,
 )
 
-from .config import PGVectorConfig
+from .config import PGVectorVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -121,8 +121,8 @@ async def delete(self):
             cur.execute(f"DROP TABLE IF EXISTS {self.table_name}")
 
 
-class PGVectorVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: PGVectorConfig, inference_api: Api.inference) -> None:
+class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
+    def __init__(self, config: PGVectorVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
         self.conn = None

llama_stack/providers/remote/vector_io/qdrant/__init__.py

@@ -8,12 +8,12 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import QdrantConfig
+from .config import QdrantVectorIOConfig
 
 
-async def get_adapter_impl(config: QdrantConfig, deps: Dict[Api, ProviderSpec]):
-    from .qdrant import QdrantVectorDBAdapter
+async def get_adapter_impl(config: QdrantVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .qdrant import QdrantVectorIOAdapter
 
-    impl = QdrantVectorDBAdapter(config, deps[Api.inference])
+    impl = QdrantVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/qdrant/config.py

@@ -11,7 +11,7 @@
 
 
 @json_schema_type
-class QdrantConfig(BaseModel):
+class QdrantVectorIOConfig(BaseModel):
     location: Optional[str] = None
     url: Optional[str] = None
     port: Optional[int] = 6333

llama_stack/providers/remote/vector_io/qdrant/qdrant.py

@@ -21,7 +21,7 @@
     VectorDBWithIndex,
 )
 
-from .config import QdrantConfig
+from .config import QdrantVectorIOConfig
 
 log = logging.getLogger(__name__)
 CHUNK_ID_KEY = "_chunk_id"
@@ -98,8 +98,8 @@ async def delete(self):
         await self.client.delete_collection(collection_name=self.collection_name)
 
 
-class QdrantVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: QdrantConfig, inference_api: Api.inference) -> None:
+class QdrantVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
+    def __init__(self, config: QdrantVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.client = AsyncQdrantClient(**self.config.model_dump(exclude_none=True))
         self.cache = {}

llama_stack/providers/remote/vector_io/sample/__init__.py

@@ -6,12 +6,12 @@
 
 from typing import Any
 
-from .config import SampleConfig
+from .config import SampleVectorIOConfig
 
 
-async def get_adapter_impl(config: SampleConfig, _deps) -> Any:
-    from .sample import SampleMemoryImpl
+async def get_adapter_impl(config: SampleVectorIOConfig, _deps) -> Any:
+    from .sample import SampleVectorIOImpl
 
-    impl = SampleMemoryImpl(config)
+    impl = SampleVectorIOImpl(config)
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/sample/config.py

@@ -7,6 +7,6 @@
 from pydantic import BaseModel
 
 
-class SampleConfig(BaseModel):
+class SampleVectorIOConfig(BaseModel):
     host: str = "localhost"
     port: int = 9999

llama_stack/providers/remote/vector_io/sample/sample.py

@@ -7,11 +7,11 @@
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import VectorIO
 
-from .config import SampleConfig
+from .config import SampleVectorIOConfig
 
 
-class SampleMemoryImpl(VectorIO):
-    def __init__(self, config: SampleConfig):
+class SampleVectorIOImpl(VectorIO):
+    def __init__(self, config: SampleVectorIOConfig):
         self.config = config
 
     async def register_vector_db(self, vector_db: VectorDB) -> None:

llama_stack/providers/remote/vector_io/weaviate/__init__.py

@@ -8,12 +8,12 @@
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import WeaviateConfig, WeaviateRequestProviderData  # noqa: F401
+from .config import WeaviateRequestProviderData, WeaviateVectorIOConfig  # noqa: F401
 
 
-async def get_adapter_impl(config: WeaviateConfig, deps: Dict[Api, ProviderSpec]):
-    from .weaviate import WeaviateMemoryAdapter
+async def get_adapter_impl(config: WeaviateVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .weaviate import WeaviateVectorIOAdapter
 
-    impl = WeaviateMemoryAdapter(config, deps[Api.inference])
+    impl = WeaviateVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/weaviate/config.py

@@ -12,5 +12,5 @@ class WeaviateRequestProviderData(BaseModel):
     weaviate_cluster_url: str
 
 
-class WeaviateConfig(BaseModel):
+class WeaviateVectorIOConfig(BaseModel):
     pass

llama_stack/providers/remote/vector_io/weaviate/weaviate.py

@@ -23,7 +23,7 @@
     VectorDBWithIndex,
 )
 
-from .config import WeaviateConfig, WeaviateRequestProviderData
+from .config import WeaviateRequestProviderData, WeaviateVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -85,12 +85,12 @@ async def delete(self, chunk_ids: List[str]) -> None:
         collection.data.delete_many(where=Filter.by_property("id").contains_any(chunk_ids))
 
 
-class WeaviateMemoryAdapter(
+class WeaviateVectorIOAdapter(
     VectorIO,
     NeedsRequestProviderData,
     VectorDBsProtocolPrivate,
 ):
-    def __init__(self, config: WeaviateConfig, inference_api: Api.inference) -> None:
+    def __init__(self, config: WeaviateVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
         self.client_cache = {}

llama_stack/providers/tests/vector_io/fixtures.py

@@ -12,12 +12,12 @@
 
 from llama_stack.apis.models import ModelInput, ModelType
 from llama_stack.distribution.datatypes import Api, Provider
-from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
-from llama_stack.providers.inline.vector_io.faiss import FaissImplConfig
+from llama_stack.providers.inline.vector_io.chroma import ChromaVectorIOConfig as InlineChromaVectorIOConfig
+from llama_stack.providers.inline.vector_io.faiss import FaissVectorIOConfig
 from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig
-from llama_stack.providers.remote.vector_io.chroma import ChromaRemoteImplConfig
-from llama_stack.providers.remote.vector_io.pgvector import PGVectorConfig
-from llama_stack.providers.remote.vector_io.weaviate import WeaviateConfig
+from llama_stack.providers.remote.vector_io.chroma import ChromaVectorIOConfig
+from llama_stack.providers.remote.vector_io.pgvector import PGVectorVectorIOConfig
+from llama_stack.providers.remote.vector_io.weaviate import WeaviateVectorIOConfig
 from llama_stack.providers.tests.resolver import construct_stack_for_test
 from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
 
@@ -45,7 +45,7 @@ def vector_io_faiss() -> ProviderFixture:
             Provider(
                 provider_id="faiss",
                 provider_type="inline::faiss",
-                config=FaissImplConfig(
+                config=FaissVectorIOConfig(
                     kvstore=SqliteKVStoreConfig(db_path=temp_file.name).model_dump(),
                 ).model_dump(),
             )
@@ -76,7 +76,7 @@ def vector_io_pgvector() -> ProviderFixture:
             Provider(
                 provider_id="pgvector",
                 provider_type="remote::pgvector",
-                config=PGVectorConfig(
+                config=PGVectorVectorIOConfig(
                     host=os.getenv("PGVECTOR_HOST", "localhost"),
                     port=os.getenv("PGVECTOR_PORT", 5432),
                     db=get_env_or_fail("PGVECTOR_DB"),
@@ -95,7 +95,7 @@ def vector_io_weaviate() -> ProviderFixture:
             Provider(
                 provider_id="weaviate",
                 provider_type="remote::weaviate",
-                config=WeaviateConfig().model_dump(),
+                config=WeaviateVectorIOConfig().model_dump(),
             )
         ],
         provider_data=dict(
@@ -109,12 +109,12 @@ def vector_io_weaviate() -> ProviderFixture:
 def vector_io_chroma() -> ProviderFixture:
     url = os.getenv("CHROMA_URL")
     if url:
-        config = ChromaRemoteImplConfig(url=url)
+        config = ChromaVectorIOConfig(url=url)
         provider_type = "remote::chromadb"
     else:
         if not os.getenv("CHROMA_DB_PATH"):
             raise ValueError("CHROMA_DB_PATH or CHROMA_URL must be set")
-        config = ChromaInlineImplConfig(db_path=os.getenv("CHROMA_DB_PATH"))
+        config = InlineChromaVectorIOConfig(db_path=os.getenv("CHROMA_DB_PATH"))
         provider_type = "inline::chromadb"
     return ProviderFixture(
         providers=[

llama_stack/templates/bedrock/bedrock.py

@@ -10,7 +10,7 @@
 
 from llama_stack.apis.models import ModelInput
 from llama_stack.distribution.datatypes import Provider, ToolGroupInput
-from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.remote.inference.bedrock.bedrock import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -37,7 +37,7 @@ def get_distribution_template() -> DistributionTemplate:
     vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
-        config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
+        config=FaissVectorIOConfig.sample_run_config(f"distributions/{name}"),
     )
 
     core_model_to_hf_repo = {m.descriptor(): m.huggingface_repo for m in all_registered_models()}