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fix: update VectorIORouter to get provider before calling openai_* methods

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VectorDBsRoutingTable was removed in a165b8b5, so VectorIORouter needs to get the provider directly using routing_table.get_provider_impl() before calling provider methods, consistent with how insert_chunks() already works.
This commit is contained in:
Ashwin Bharambe 2025-10-11 17:37:10 -07:00
parent 3568ccdc81
commit 58fcaa445e
2 changed files with 44 additions and 41 deletions
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43
tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py
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@ -15,6 +15,7 @@ from llama_stack.apis.common.errors import VectorStoreNotFoundError
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.vector_io import (
Chunk,
OpenAICreateVectorStoreFileBatchRequestWithExtraBody,
QueryChunksResponse,
VectorStoreChunkingStrategyAuto,
VectorStoreFileObject,
@ -326,8 +327,7 @@ async def test_create_vector_store_file_batch(vector_io_adapter):
vector_io_adapter._process_file_batch_async = AsyncMock()
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
assert batch.vector_store_id == store_id
@ -354,8 +354,7 @@ async def test_retrieve_vector_store_file_batch(vector_io_adapter):
# Create batch first
created_batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Retrieve batch
@ -388,8 +387,7 @@ async def test_cancel_vector_store_file_batch(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Cancel batch
@ -434,8 +432,7 @@ async def test_list_files_in_vector_store_file_batch(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# List files
@ -454,8 +451,7 @@ async def test_file_batch_validation_errors(vector_io_adapter):
# Test nonexistent vector store
with pytest.raises(VectorStoreNotFoundError):
await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id="nonexistent",
file_ids=["file_1"],
vector_store_id="nonexistent", params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"])
)
# Setup store for remaining tests
@ -472,8 +468,7 @@ async def test_file_batch_validation_errors(vector_io_adapter):
# Test wrong vector store for batch
vector_io_adapter.openai_attach_file_to_vector_store = AsyncMock()
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=["file_1"],
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"])
)
# Create wrong_store so it exists but the batch doesn't belong to it
@ -520,8 +515,7 @@ async def test_file_batch_pagination(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Test pagination with limit
@ -593,8 +587,7 @@ async def test_file_batch_status_filtering(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Test filtering by completed status
@ -636,8 +629,7 @@ async def test_cancel_completed_batch_fails(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Manually update status to completed
@ -671,8 +663,7 @@ async def test_file_batch_persistence_across_restarts(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
batch_id = batch.id
@ -727,8 +718,7 @@ async def test_cancelled_batch_persists_in_storage(vector_io_adapter):
# Create batch
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
batch_id = batch.id
@ -775,10 +765,10 @@ async def test_only_in_progress_batches_resumed(vector_io_adapter):
# Create multiple batches
batch1 = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id, file_ids=["file_1"]
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_1"])
)
batch2 = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id, file_ids=["file_2"]
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_2"])
)
# Complete one batch (should persist with completed status)
@ -791,7 +781,7 @@ async def test_only_in_progress_batches_resumed(vector_io_adapter):
# Create a third batch that stays in progress
batch3 = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id, file_ids=["file_3"]
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=["file_3"])
)
# Simulate restart - clear memory and reload from persistence
@ -952,8 +942,7 @@ async def test_max_concurrent_files_per_batch(vector_io_adapter):
file_ids = [f"file_{i}" for i in range(8)] # 8 files, but limit should be 5
batch = await vector_io_adapter.openai_create_vector_store_file_batch(
vector_store_id=store_id,
file_ids=file_ids,
vector_store_id=store_id, params=OpenAICreateVectorStoreFileBatchRequestWithExtraBody(file_ids=file_ids)
)
# Give time for the semaphore logic to start processing files