phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-12-23 00:29:41 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

refactor component path

Browse source 
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-29 21:20:21 -04:00
parent a29b62f820
commit 19d2555424
116 changed files with 7064 additions and 1265 deletions
Download patch file Download diff file Expand all files Collapse all files

7
llama_stack/distribution/routing_tables/vector_dbs.py
View file

@ -8,6 +8,7 @@ from typing import Any
from pydantic import TypeAdapter
from llama_stack.apis.common.errors import ModelNotFoundError, VectorStoreNotFoundError
from llama_stack.apis.models import ModelType
from llama_stack.apis.resource import ResourceType
from llama_stack.apis.vector_dbs import ListVectorDBsResponse, VectorDB, VectorDBs
@ -39,7 +40,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
async def get_vector_db(self, vector_db_id: str) -> VectorDB:
vector_db = await self.get_object_by_identifier("vector_db", vector_db_id)
if vector_db is None:
raise ValueError(f"Vector DB '{vector_db_id}' not found")
raise VectorStoreNotFoundError(vector_db_id)
return vector_db
async def register_vector_db(
@ -63,7 +64,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
raise ValueError("No provider available. Please configure a vector_io provider.")
model = await lookup_model(self, embedding_model)
if model is None:
raise ValueError(f"Model {embedding_model} not found")
raise ModelNotFoundError(embedding_model)
if model.model_type != ModelType.embedding:
raise ValueError(f"Model {embedding_model} is not an embedding model")
if "embedding_dimension" not in model.metadata:
@ -84,7 +85,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
async def unregister_vector_db(self, vector_db_id: str) -> None:
existing_vector_db = await self.get_vector_db(vector_db_id)
if existing_vector_db is None:
raise ValueError(f"Vector DB {vector_db_id} not found")
raise VectorStoreNotFoundError(vector_db_id)
await self.unregister_object(existing_vector_db)
async def openai_retrieve_vector_store(