feat(stores)!: use backend storage references instead of configs (#3697)

**This PR changes configurations in a backward incompatible way.**

Run configs today repeat full SQLite/Postgres snippets everywhere a
store is needed, which means duplicated credentials, extra connection
pools, and lots of drift between files. This PR introduces named storage
backends so the stack and providers can share a single catalog and
reference those backends by name.

## Key Changes

- Add `storage.backends` to `StackRunConfig`, register each KV/SQL
backend once at startup, and validate that references point to the right
family.
- Move server stores under `storage.stores` with lightweight references
(backend + namespace/table) instead of full configs.
- Update every provider/config/doc to use the new reference style;
docs/codegen now surface the simplified YAML.

## Migration

Before:
```yaml
metadata_store:
  type: sqlite
  db_path: ~/.llama/distributions/foo/registry.db
inference_store:
  type: postgres
  host: ${env.POSTGRES_HOST}
  port: ${env.POSTGRES_PORT}
  db: ${env.POSTGRES_DB}
  user: ${env.POSTGRES_USER}
  password: ${env.POSTGRES_PASSWORD}
conversations_store:
  type: postgres
  host: ${env.POSTGRES_HOST}
  port: ${env.POSTGRES_PORT}
  db: ${env.POSTGRES_DB}
  user: ${env.POSTGRES_USER}
  password: ${env.POSTGRES_PASSWORD}
```

After:
```yaml
storage:
  backends:
    kv_default:
      type: kv_sqlite
      db_path: ~/.llama/distributions/foo/kvstore.db
    sql_default:
      type: sql_postgres
      host: ${env.POSTGRES_HOST}
      port: ${env.POSTGRES_PORT}
      db: ${env.POSTGRES_DB}
      user: ${env.POSTGRES_USER}
      password: ${env.POSTGRES_PASSWORD}
  stores:
    metadata:
      backend: kv_default
      namespace: registry
    inference:
      backend: sql_default
      table_name: inference_store
      max_write_queue_size: 10000
      num_writers: 4
    conversations:
      backend: sql_default
      table_name: openai_conversations
```

Provider configs follow the same pattern—for example, a Chroma vector
adapter switches from:

```yaml
providers:
  vector_io:
  - provider_id: chromadb
    provider_type: remote::chromadb
    config:
      url: ${env.CHROMADB_URL}
      kvstore:
        type: sqlite
        db_path: ~/.llama/distributions/foo/chroma.db
```

to:

```yaml
providers:
  vector_io:
  - provider_id: chromadb
    provider_type: remote::chromadb
    config:
      url: ${env.CHROMADB_URL}
      persistence:
        backend: kv_default
        namespace: vector_io::chroma_remote
```

Once the backends are declared, everything else just points at them, so
rotating credentials or swapping to Postgres happens in one place and
the stack reuses a single connection pool.
This commit is contained in:
Ashwin Bharambe 2025-10-20 13:20:09 -07:00 committed by GitHub
parent add64e8e2a
commit 2c43285e22
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
105 changed files with 2290 additions and 1292 deletions

View file

@ -7,6 +7,24 @@ providers:
- provider_id: kaze
provider_type: remote::kaze
config: {}
storage:
backends:
kv_default:
type: kv_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/external}/kvstore.db
sql_default:
type: sql_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/external}/sql_store.db
stores:
metadata:
namespace: registry
backend: kv_default
inference:
table_name: inference_store
backend: sql_default
conversations:
table_name: openai_conversations
backend: sql_default
external_apis_dir: ~/.llama/apis.d
external_providers_dir: ~/.llama/providers.d
server:

View file

@ -238,7 +238,7 @@ def instantiate_llama_stack_client(session):
run_config = run_config_from_adhoc_config_spec(config)
run_config_file = tempfile.NamedTemporaryFile(delete=False, suffix=".yaml")
with open(run_config_file.name, "w") as f:
yaml.dump(run_config.model_dump(), f)
yaml.dump(run_config.model_dump(mode="json"), f)
config = run_config_file.name
client = LlamaStackAsLibraryClient(

View file

@ -12,9 +12,15 @@ import pytest
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.datatypes import User
from llama_stack.core.storage.datatypes import SqlStoreReference
from llama_stack.providers.utils.sqlstore.api import ColumnType
from llama_stack.providers.utils.sqlstore.authorized_sqlstore import AuthorizedSqlStore
from llama_stack.providers.utils.sqlstore.sqlstore import PostgresSqlStoreConfig, SqliteSqlStoreConfig, sqlstore_impl
from llama_stack.providers.utils.sqlstore.sqlstore import (
PostgresSqlStoreConfig,
SqliteSqlStoreConfig,
register_sqlstore_backends,
sqlstore_impl,
)
def get_postgres_config():
@ -55,8 +61,9 @@ def authorized_store(backend_config):
config_func = backend_config
config = config_func()
base_sqlstore = sqlstore_impl(config)
backend_name = f"sql_{type(config).__name__.lower()}"
register_sqlstore_backends({backend_name: config})
base_sqlstore = sqlstore_impl(SqlStoreReference(backend=backend_name, table_name="authorized_store"))
authorized_store = AuthorizedSqlStore(base_sqlstore, default_policy())
yield authorized_store

View file

@ -0,0 +1,71 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import yaml
from llama_stack.core.datatypes import StackRunConfig
from llama_stack.core.storage.datatypes import (
PostgresKVStoreConfig,
PostgresSqlStoreConfig,
SqliteKVStoreConfig,
SqliteSqlStoreConfig,
)
def test_starter_distribution_config_loads_and_resolves():
"""Integration: Actual starter config should parse and have correct storage structure."""
with open("llama_stack/distributions/starter/run.yaml") as f:
config_dict = yaml.safe_load(f)
config = StackRunConfig(**config_dict)
# Config should have named backends and explicit store references
assert config.storage is not None
assert "kv_default" in config.storage.backends
assert "sql_default" in config.storage.backends
assert isinstance(config.storage.backends["kv_default"], SqliteKVStoreConfig)
assert isinstance(config.storage.backends["sql_default"], SqliteSqlStoreConfig)
stores = config.storage.stores
assert stores.metadata is not None
assert stores.metadata.backend == "kv_default"
assert stores.metadata.namespace == "registry"
assert stores.inference is not None
assert stores.inference.backend == "sql_default"
assert stores.inference.table_name == "inference_store"
assert stores.inference.max_write_queue_size > 0
assert stores.inference.num_writers > 0
assert stores.conversations is not None
assert stores.conversations.backend == "sql_default"
assert stores.conversations.table_name == "openai_conversations"
def test_postgres_demo_distribution_config_loads():
"""Integration: Postgres demo should use Postgres backend for all stores."""
with open("llama_stack/distributions/postgres-demo/run.yaml") as f:
config_dict = yaml.safe_load(f)
config = StackRunConfig(**config_dict)
# Should have postgres backend
assert config.storage is not None
assert "kv_default" in config.storage.backends
assert "sql_default" in config.storage.backends
postgres_backend = config.storage.backends["sql_default"]
assert isinstance(postgres_backend, PostgresSqlStoreConfig)
assert postgres_backend.host == "${env.POSTGRES_HOST:=localhost}"
kv_backend = config.storage.backends["kv_default"]
assert isinstance(kv_backend, PostgresKVStoreConfig)
stores = config.storage.stores
# Stores target the Postgres backends explicitly
assert stores.metadata is not None
assert stores.metadata.backend == "kv_default"
assert stores.inference is not None
assert stores.inference.backend == "sql_default"

View file

@ -23,6 +23,27 @@ def config_with_image_name_int():
image_name: 1234
apis_to_serve: []
built_at: {datetime.now().isoformat()}
storage:
backends:
kv_default:
type: kv_sqlite
db_path: /tmp/test_kv.db
sql_default:
type: sql_sqlite
db_path: /tmp/test_sql.db
stores:
metadata:
backend: kv_default
namespace: metadata
inference:
backend: sql_default
table_name: inference
conversations:
backend: sql_default
table_name: conversations
responses:
backend: sql_default
table_name: responses
providers:
inference:
- provider_id: provider1
@ -54,6 +75,27 @@ def up_to_date_config():
image_name: foo
apis_to_serve: []
built_at: {datetime.now().isoformat()}
storage:
backends:
kv_default:
type: kv_sqlite
db_path: /tmp/test_kv.db
sql_default:
type: sql_sqlite
db_path: /tmp/test_sql.db
stores:
metadata:
backend: kv_default
namespace: metadata
inference:
backend: sql_default
table_name: inference
conversations:
backend: sql_default
table_name: conversations
responses:
backend: sql_default
table_name: responses
providers:
inference:
- provider_id: provider1

View file

@ -20,7 +20,14 @@ from llama_stack.core.conversations.conversations import (
ConversationServiceConfig,
ConversationServiceImpl,
)
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.core.datatypes import StackRunConfig
from llama_stack.core.storage.datatypes import (
ServerStoresConfig,
SqliteSqlStoreConfig,
SqlStoreReference,
StorageConfig,
)
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
@pytest.fixture
@ -28,7 +35,18 @@ async def service():
with tempfile.TemporaryDirectory() as tmpdir:
db_path = Path(tmpdir) / "test_conversations.db"
config = ConversationServiceConfig(conversations_store=SqliteSqlStoreConfig(db_path=str(db_path)), policy=[])
storage = StorageConfig(
backends={
"sql_test": SqliteSqlStoreConfig(db_path=str(db_path)),
},
stores=ServerStoresConfig(
conversations=SqlStoreReference(backend="sql_test", table_name="openai_conversations"),
),
)
register_sqlstore_backends({"sql_test": storage.backends["sql_test"]})
run_config = StackRunConfig(image_name="test", apis=[], providers={}, storage=storage)
config = ConversationServiceConfig(run_config=run_config, policy=[])
service = ConversationServiceImpl(config, {})
await service.initialize()
yield service
@ -121,9 +139,18 @@ async def test_policy_configuration():
AccessRule(forbid=Scope(principal="test_user", actions=[Action.CREATE, Action.READ], resource="*"))
]
config = ConversationServiceConfig(
conversations_store=SqliteSqlStoreConfig(db_path=str(db_path)), policy=restrictive_policy
storage = StorageConfig(
backends={
"sql_test": SqliteSqlStoreConfig(db_path=str(db_path)),
},
stores=ServerStoresConfig(
conversations=SqlStoreReference(backend="sql_test", table_name="openai_conversations"),
),
)
register_sqlstore_backends({"sql_test": storage.backends["sql_test"]})
run_config = StackRunConfig(image_name="test", apis=[], providers={}, storage=storage)
config = ConversationServiceConfig(run_config=run_config, policy=restrictive_policy)
service = ConversationServiceImpl(config, {})
await service.initialize()

View file

@ -0,0 +1,84 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
"""Unit tests for storage backend/reference validation."""
import pytest
from pydantic import ValidationError
from llama_stack.core.datatypes import (
LLAMA_STACK_RUN_CONFIG_VERSION,
StackRunConfig,
)
from llama_stack.core.storage.datatypes import (
InferenceStoreReference,
KVStoreReference,
ServerStoresConfig,
SqliteKVStoreConfig,
SqliteSqlStoreConfig,
SqlStoreReference,
StorageConfig,
)
def _base_run_config(**overrides):
metadata_reference = overrides.pop(
"metadata_reference",
KVStoreReference(backend="kv_default", namespace="registry"),
)
inference_reference = overrides.pop(
"inference_reference",
InferenceStoreReference(backend="sql_default", table_name="inference"),
)
conversations_reference = overrides.pop(
"conversations_reference",
SqlStoreReference(backend="sql_default", table_name="conversations"),
)
storage = overrides.pop(
"storage",
StorageConfig(
backends={
"kv_default": SqliteKVStoreConfig(db_path="/tmp/kv.db"),
"sql_default": SqliteSqlStoreConfig(db_path="/tmp/sql.db"),
},
stores=ServerStoresConfig(
metadata=metadata_reference,
inference=inference_reference,
conversations=conversations_reference,
),
),
)
return StackRunConfig(
version=LLAMA_STACK_RUN_CONFIG_VERSION,
image_name="test-distro",
apis=[],
providers={},
storage=storage,
**overrides,
)
def test_references_require_known_backend():
with pytest.raises(ValidationError, match="unknown backend 'missing'"):
_base_run_config(metadata_reference=KVStoreReference(backend="missing", namespace="registry"))
def test_references_must_match_backend_family():
with pytest.raises(ValidationError, match="kv_.* is required"):
_base_run_config(metadata_reference=KVStoreReference(backend="sql_default", namespace="registry"))
with pytest.raises(ValidationError, match="sql_.* is required"):
_base_run_config(
inference_reference=InferenceStoreReference(backend="kv_default", table_name="inference"),
)
def test_valid_configuration_passes_validation():
config = _base_run_config()
stores = config.storage.stores
assert stores.metadata is not None and stores.metadata.backend == "kv_default"
assert stores.inference is not None and stores.inference.backend == "sql_default"
assert stores.conversations is not None and stores.conversations.backend == "sql_default"

View file

@ -13,6 +13,15 @@ from pydantic import BaseModel, Field, ValidationError
from llama_stack.core.datatypes import Api, Provider, StackRunConfig
from llama_stack.core.distribution import INTERNAL_APIS, get_provider_registry, providable_apis
from llama_stack.core.storage.datatypes import (
InferenceStoreReference,
KVStoreReference,
ServerStoresConfig,
SqliteKVStoreConfig,
SqliteSqlStoreConfig,
SqlStoreReference,
StorageConfig,
)
from llama_stack.providers.datatypes import ProviderSpec
@ -29,6 +38,32 @@ class SampleConfig(BaseModel):
}
def _default_storage() -> StorageConfig:
return StorageConfig(
backends={
"kv_default": SqliteKVStoreConfig(db_path=":memory:"),
"sql_default": SqliteSqlStoreConfig(db_path=":memory:"),
},
stores=ServerStoresConfig(
metadata=KVStoreReference(backend="kv_default", namespace="registry"),
inference=InferenceStoreReference(backend="sql_default", table_name="inference_store"),
conversations=SqlStoreReference(backend="sql_default", table_name="conversations"),
),
)
def make_stack_config(**overrides) -> StackRunConfig:
storage = overrides.pop("storage", _default_storage())
defaults = dict(
image_name="test_image",
apis=[],
providers={},
storage=storage,
)
defaults.update(overrides)
return StackRunConfig(**defaults)
@pytest.fixture
def mock_providers():
"""Mock the available_providers function to return test providers."""
@ -47,8 +82,8 @@ def mock_providers():
@pytest.fixture
def base_config(tmp_path):
"""Create a base StackRunConfig with common settings."""
return StackRunConfig(
image_name="test_image",
return make_stack_config(
apis=["inference"],
providers={
"inference": [
Provider(
@ -222,8 +257,8 @@ class TestProviderRegistry:
def test_missing_directory(self, mock_providers):
"""Test handling of missing external providers directory."""
config = StackRunConfig(
image_name="test_image",
config = make_stack_config(
apis=["inference"],
providers={
"inference": [
Provider(
@ -278,7 +313,6 @@ pip_packages:
"""Test loading an external provider from a module (success path)."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.providers.datatypes import Api, ProviderSpec
# Simulate a provider module with get_provider_spec
@ -293,7 +327,7 @@ pip_packages:
import_module_side_effect = make_import_module_side_effect(external_module=fake_module)
with patch("importlib.import_module", side_effect=import_module_side_effect) as mock_import:
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -317,12 +351,11 @@ pip_packages:
def test_external_provider_from_module_not_found(self, mock_providers):
"""Test handling ModuleNotFoundError for missing provider module."""
from llama_stack.core.datatypes import Provider, StackRunConfig
import_module_side_effect = make_import_module_side_effect(raise_for_external=True)
with patch("importlib.import_module", side_effect=import_module_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -341,12 +374,11 @@ pip_packages:
def test_external_provider_from_module_missing_get_provider_spec(self, mock_providers):
"""Test handling missing get_provider_spec in provider module (should raise ValueError)."""
from llama_stack.core.datatypes import Provider, StackRunConfig
import_module_side_effect = make_import_module_side_effect(missing_get_provider_spec=True)
with patch("importlib.import_module", side_effect=import_module_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -399,13 +431,12 @@ class TestGetExternalProvidersFromModule:
def test_stackrunconfig_provider_without_module(self, mock_providers):
"""Test that providers without module attribute are skipped."""
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
import_module_side_effect = make_import_module_side_effect()
with patch("importlib.import_module", side_effect=import_module_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -426,7 +457,6 @@ class TestGetExternalProvidersFromModule:
"""Test provider with module containing version spec (e.g., package==1.0.0)."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
from llama_stack.providers.datatypes import ProviderSpec
@ -444,7 +474,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -564,7 +594,6 @@ class TestGetExternalProvidersFromModule:
"""Test when get_provider_spec returns a list of specs."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
from llama_stack.providers.datatypes import ProviderSpec
@ -589,7 +618,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -613,7 +642,6 @@ class TestGetExternalProvidersFromModule:
"""Test that list return filters specs by provider_type."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
from llama_stack.providers.datatypes import ProviderSpec
@ -638,7 +666,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -662,7 +690,6 @@ class TestGetExternalProvidersFromModule:
"""Test that list return adds multiple different provider_types when config requests them."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
from llama_stack.providers.datatypes import ProviderSpec
@ -688,7 +715,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -718,7 +745,6 @@ class TestGetExternalProvidersFromModule:
def test_module_not_found_raises_value_error(self, mock_providers):
"""Test that ModuleNotFoundError raises ValueError with helpful message."""
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
def import_side_effect(name):
@ -727,7 +753,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -751,7 +777,6 @@ class TestGetExternalProvidersFromModule:
"""Test that generic exceptions are properly raised."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
def bad_spec():
@ -765,7 +790,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [
@ -787,10 +812,9 @@ class TestGetExternalProvidersFromModule:
def test_empty_provider_list(self, mock_providers):
"""Test with empty provider list."""
from llama_stack.core.datatypes import StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={},
)
@ -805,7 +829,6 @@ class TestGetExternalProvidersFromModule:
"""Test multiple APIs with providers."""
from types import SimpleNamespace
from llama_stack.core.datatypes import Provider, StackRunConfig
from llama_stack.core.distribution import get_external_providers_from_module
from llama_stack.providers.datatypes import ProviderSpec
@ -830,7 +853,7 @@ class TestGetExternalProvidersFromModule:
raise ModuleNotFoundError(name)
with patch("importlib.import_module", side_effect=import_side_effect):
config = StackRunConfig(
config = make_stack_config(
image_name="test_image",
providers={
"inference": [

View file

@ -11,11 +11,12 @@ from llama_stack.apis.common.errors import ResourceNotFoundError
from llama_stack.apis.common.responses import Order
from llama_stack.apis.files import OpenAIFilePurpose
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.storage.datatypes import SqliteSqlStoreConfig, SqlStoreReference
from llama_stack.providers.inline.files.localfs import (
LocalfsFilesImpl,
LocalfsFilesImplConfig,
)
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
class MockUploadFile:
@ -36,8 +37,11 @@ async def files_provider(tmp_path):
storage_dir = tmp_path / "files"
db_path = tmp_path / "files_metadata.db"
backend_name = "sql_localfs_test"
register_sqlstore_backends({backend_name: SqliteSqlStoreConfig(db_path=db_path.as_posix())})
config = LocalfsFilesImplConfig(
storage_dir=storage_dir.as_posix(), metadata_store=SqliteSqlStoreConfig(db_path=db_path.as_posix())
storage_dir=storage_dir.as_posix(),
metadata_store=SqlStoreReference(backend=backend_name, table_name="files_metadata"),
)
provider = LocalfsFilesImpl(config, default_policy())

View file

@ -9,7 +9,16 @@ import random
import pytest
from llama_stack.core.prompts.prompts import PromptServiceConfig, PromptServiceImpl
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
from llama_stack.core.storage.datatypes import (
InferenceStoreReference,
KVStoreReference,
ServerStoresConfig,
SqliteKVStoreConfig,
SqliteSqlStoreConfig,
SqlStoreReference,
StorageConfig,
)
from llama_stack.providers.utils.kvstore import kvstore_impl, register_kvstore_backends
@pytest.fixture
@ -19,12 +28,28 @@ async def temp_prompt_store(tmp_path_factory):
db_path = str(temp_dir / f"{unique_id}.db")
from llama_stack.core.datatypes import StackRunConfig
from llama_stack.providers.utils.kvstore import kvstore_impl
mock_run_config = StackRunConfig(image_name="test-distribution", apis=[], providers={})
storage = StorageConfig(
backends={
"kv_test": SqliteKVStoreConfig(db_path=db_path),
"sql_test": SqliteSqlStoreConfig(db_path=str(temp_dir / f"{unique_id}_sql.db")),
},
stores=ServerStoresConfig(
metadata=KVStoreReference(backend="kv_test", namespace="registry"),
inference=InferenceStoreReference(backend="sql_test", table_name="inference"),
conversations=SqlStoreReference(backend="sql_test", table_name="conversations"),
),
)
mock_run_config = StackRunConfig(
image_name="test-distribution",
apis=[],
providers={},
storage=storage,
)
config = PromptServiceConfig(run_config=mock_run_config)
store = PromptServiceImpl(config, deps={})
store.kvstore = await kvstore_impl(SqliteKVStoreConfig(db_path=db_path))
register_kvstore_backends({"kv_test": storage.backends["kv_test"]})
store.kvstore = await kvstore_impl(KVStoreReference(backend="kv_test", namespace="prompts"))
yield store

View file

@ -26,6 +26,20 @@ from llama_stack.providers.inline.agents.meta_reference.config import MetaRefere
from llama_stack.providers.inline.agents.meta_reference.persistence import AgentInfo
@pytest.fixture(autouse=True)
def setup_backends(tmp_path):
"""Register KV and SQL store backends for testing."""
from llama_stack.core.storage.datatypes import SqliteKVStoreConfig, SqliteSqlStoreConfig
from llama_stack.providers.utils.kvstore.kvstore import register_kvstore_backends
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
kv_path = str(tmp_path / "test_kv.db")
sql_path = str(tmp_path / "test_sql.db")
register_kvstore_backends({"kv_default": SqliteKVStoreConfig(db_path=kv_path)})
register_sqlstore_backends({"sql_default": SqliteSqlStoreConfig(db_path=sql_path)})
@pytest.fixture
def mock_apis():
return {
@ -40,15 +54,20 @@ def mock_apis():
@pytest.fixture
def config(tmp_path):
from llama_stack.core.storage.datatypes import KVStoreReference, ResponsesStoreReference
from llama_stack.providers.inline.agents.meta_reference.config import AgentPersistenceConfig
return MetaReferenceAgentsImplConfig(
persistence_store={
"type": "sqlite",
"db_path": str(tmp_path / "test.db"),
},
responses_store={
"type": "sqlite",
"db_path": str(tmp_path / "test.db"),
},
persistence=AgentPersistenceConfig(
agent_state=KVStoreReference(
backend="kv_default",
namespace="agents",
),
responses=ResponsesStoreReference(
backend="sql_default",
table_name="responses",
),
)
)

View file

@ -42,7 +42,7 @@ from llama_stack.apis.inference import (
)
from llama_stack.apis.tools.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.datatypes import ResponsesStoreConfig
from llama_stack.core.storage.datatypes import ResponsesStoreReference, SqliteSqlStoreConfig
from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import (
OpenAIResponsesImpl,
)
@ -50,7 +50,7 @@ from llama_stack.providers.utils.responses.responses_store import (
ResponsesStore,
_OpenAIResponseObjectWithInputAndMessages,
)
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
from tests.unit.providers.agents.meta_reference.fixtures import load_chat_completion_fixture
@ -917,8 +917,10 @@ async def test_responses_store_list_input_items_logic():
# Create mock store and response store
mock_sql_store = AsyncMock()
backend_name = "sql_responses_test"
register_sqlstore_backends({backend_name: SqliteSqlStoreConfig(db_path="mock_db_path")})
responses_store = ResponsesStore(
ResponsesStoreConfig(sql_store_config=SqliteSqlStoreConfig(db_path="mock_db_path")), policy=default_policy()
ResponsesStoreReference(backend=backend_name, table_name="responses"), policy=default_policy()
)
responses_store.sql_store = mock_sql_store

View file

@ -12,10 +12,10 @@ from unittest.mock import AsyncMock
import pytest
from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
from llama_stack.providers.inline.batches.reference.batches import ReferenceBatchesImpl
from llama_stack.providers.inline.batches.reference.config import ReferenceBatchesImplConfig
from llama_stack.providers.utils.kvstore import kvstore_impl
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
from llama_stack.providers.utils.kvstore import kvstore_impl, register_kvstore_backends
@pytest.fixture
@ -23,8 +23,10 @@ async def provider():
"""Create a test provider instance with temporary database."""
with tempfile.TemporaryDirectory() as tmpdir:
db_path = Path(tmpdir) / "test_batches.db"
backend_name = "kv_batches_test"
kvstore_config = SqliteKVStoreConfig(db_path=str(db_path))
config = ReferenceBatchesImplConfig(kvstore=kvstore_config)
register_kvstore_backends({backend_name: kvstore_config})
config = ReferenceBatchesImplConfig(kvstore=KVStoreReference(backend=backend_name, namespace="batches"))
# Create kvstore and mock APIs
kvstore = await kvstore_impl(config.kvstore)

View file

@ -8,8 +8,9 @@ import boto3
import pytest
from moto import mock_aws
from llama_stack.core.storage.datatypes import SqliteSqlStoreConfig, SqlStoreReference
from llama_stack.providers.remote.files.s3 import S3FilesImplConfig, get_adapter_impl
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
class MockUploadFile:
@ -38,11 +39,13 @@ def sample_text_file2():
def s3_config(tmp_path):
db_path = tmp_path / "s3_files_metadata.db"
backend_name = f"sql_s3_{tmp_path.name}"
register_sqlstore_backends({backend_name: SqliteSqlStoreConfig(db_path=db_path.as_posix())})
return S3FilesImplConfig(
bucket_name=f"test-bucket-{tmp_path.name}",
region="not-a-region",
auto_create_bucket=True,
metadata_store=SqliteSqlStoreConfig(db_path=db_path.as_posix()),
metadata_store=SqlStoreReference(backend=backend_name, table_name="s3_files_metadata"),
)

View file

@ -12,13 +12,14 @@ import pytest
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.vector_io import Chunk, ChunkMetadata, QueryChunksResponse
from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, FaissVectorIOAdapter
from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig
from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter
from llama_stack.providers.remote.vector_io.pgvector.config import PGVectorVectorIOConfig
from llama_stack.providers.remote.vector_io.pgvector.pgvector import PGVectorIndex, PGVectorVectorIOAdapter
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
from llama_stack.providers.utils.kvstore import register_kvstore_backends
EMBEDDING_DIMENSION = 768
COLLECTION_PREFIX = "test_collection"
@ -112,8 +113,9 @@ async def unique_kvstore_config(tmp_path_factory):
unique_id = f"test_kv_{np.random.randint(1e6)}"
temp_dir = tmp_path_factory.getbasetemp()
db_path = str(temp_dir / f"{unique_id}.db")
return SqliteKVStoreConfig(db_path=db_path)
backend_name = f"kv_vector_{unique_id}"
register_kvstore_backends({backend_name: SqliteKVStoreConfig(db_path=db_path)})
return KVStoreReference(backend=backend_name, namespace=f"vector_io::{unique_id}")
@pytest.fixture(scope="session")
@ -138,7 +140,7 @@ async def sqlite_vec_vec_index(embedding_dimension, tmp_path_factory):
async def sqlite_vec_adapter(sqlite_vec_db_path, unique_kvstore_config, mock_inference_api, embedding_dimension):
config = SQLiteVectorIOConfig(
db_path=sqlite_vec_db_path,
kvstore=unique_kvstore_config,
persistence=unique_kvstore_config,
)
adapter = SQLiteVecVectorIOAdapter(
config=config,
@ -177,7 +179,7 @@ async def faiss_vec_index(embedding_dimension):
@pytest.fixture
async def faiss_vec_adapter(unique_kvstore_config, mock_inference_api, embedding_dimension):
config = FaissVectorIOConfig(
kvstore=unique_kvstore_config,
persistence=unique_kvstore_config,
)
adapter = FaissVectorIOAdapter(
config=config,
@ -253,7 +255,7 @@ async def pgvector_vec_adapter(unique_kvstore_config, mock_inference_api, embedd
db="test_db",
user="test_user",
password="test_password",
kvstore=unique_kvstore_config,
persistence=unique_kvstore_config,
)
adapter = PGVectorVectorIOAdapter(config, mock_inference_api, None)

View file

@ -10,13 +10,13 @@ import pytest
from llama_stack.apis.inference import Model
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.core.datatypes import VectorDBWithOwner
from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
from llama_stack.core.store.registry import (
KEY_FORMAT,
CachedDiskDistributionRegistry,
DiskDistributionRegistry,
)
from llama_stack.providers.utils.kvstore import kvstore_impl
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
from llama_stack.providers.utils.kvstore import kvstore_impl, register_kvstore_backends
@pytest.fixture
@ -72,7 +72,11 @@ async def test_cached_registry_initialization(sqlite_kvstore, sample_vector_db,
# Test cached version loads from disk
db_path = sqlite_kvstore.db_path
cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(SqliteKVStoreConfig(db_path=db_path)))
backend_name = "kv_cached_test"
register_kvstore_backends({backend_name: SqliteKVStoreConfig(db_path=db_path)})
cached_registry = CachedDiskDistributionRegistry(
await kvstore_impl(KVStoreReference(backend=backend_name, namespace="registry"))
)
await cached_registry.initialize()
result_vector_db = await cached_registry.get("vector_db", "test_vector_db")
@ -101,7 +105,11 @@ async def test_cached_registry_updates(cached_disk_dist_registry):
# Verify persisted to disk
db_path = cached_disk_dist_registry.kvstore.db_path
new_registry = DiskDistributionRegistry(await kvstore_impl(SqliteKVStoreConfig(db_path=db_path)))
backend_name = "kv_cached_new"
register_kvstore_backends({backend_name: SqliteKVStoreConfig(db_path=db_path)})
new_registry = DiskDistributionRegistry(
await kvstore_impl(KVStoreReference(backend=backend_name, namespace="registry"))
)
await new_registry.initialize()
result_vector_db = await new_registry.get("vector_db", "test_vector_db_2")
assert result_vector_db is not None

View file

@ -4,6 +4,8 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from uuid import uuid4
import pytest
from fastapi import FastAPI, Request
from fastapi.testclient import TestClient
@ -11,7 +13,8 @@ from starlette.middleware.base import BaseHTTPMiddleware
from llama_stack.core.datatypes import QuotaConfig, QuotaPeriod
from llama_stack.core.server.quota import QuotaMiddleware
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
from llama_stack.providers.utils.kvstore import register_kvstore_backends
class InjectClientIDMiddleware(BaseHTTPMiddleware):
@ -29,8 +32,10 @@ class InjectClientIDMiddleware(BaseHTTPMiddleware):
def build_quota_config(db_path) -> QuotaConfig:
backend_name = f"kv_quota_{uuid4().hex}"
register_kvstore_backends({backend_name: SqliteKVStoreConfig(db_path=str(db_path))})
return QuotaConfig(
kvstore=SqliteKVStoreConfig(db_path=str(db_path)),
kvstore=KVStoreReference(backend=backend_name, namespace="quota"),
anonymous_max_requests=1,
authenticated_max_requests=2,
period=QuotaPeriod.DAY,

View file

@ -12,15 +12,22 @@ from unittest.mock import AsyncMock, MagicMock
from pydantic import BaseModel, Field
from llama_stack.apis.inference import Inference
from llama_stack.core.datatypes import (
Api,
Provider,
StackRunConfig,
)
from llama_stack.core.datatypes import Api, Provider, StackRunConfig
from llama_stack.core.resolver import resolve_impls
from llama_stack.core.routers.inference import InferenceRouter
from llama_stack.core.routing_tables.models import ModelsRoutingTable
from llama_stack.core.storage.datatypes import (
InferenceStoreReference,
KVStoreReference,
ServerStoresConfig,
SqliteKVStoreConfig,
SqliteSqlStoreConfig,
SqlStoreReference,
StorageConfig,
)
from llama_stack.providers.datatypes import InlineProviderSpec, ProviderSpec
from llama_stack.providers.utils.kvstore import register_kvstore_backends
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
def add_protocol_methods(cls: type, protocol: type[Protocol]) -> None:
@ -65,6 +72,35 @@ class SampleImpl:
pass
def make_run_config(**overrides) -> StackRunConfig:
storage = overrides.pop(
"storage",
StorageConfig(
backends={
"kv_default": SqliteKVStoreConfig(db_path=":memory:"),
"sql_default": SqliteSqlStoreConfig(db_path=":memory:"),
},
stores=ServerStoresConfig(
metadata=KVStoreReference(backend="kv_default", namespace="registry"),
inference=InferenceStoreReference(backend="sql_default", table_name="inference_store"),
conversations=SqlStoreReference(backend="sql_default", table_name="conversations"),
),
),
)
register_kvstore_backends({name: cfg for name, cfg in storage.backends.items() if cfg.type.value.startswith("kv_")})
register_sqlstore_backends(
{name: cfg for name, cfg in storage.backends.items() if cfg.type.value.startswith("sql_")}
)
defaults = dict(
image_name="test_image",
apis=[],
providers={},
storage=storage,
)
defaults.update(overrides)
return StackRunConfig(**defaults)
async def test_resolve_impls_basic():
# Create a real provider spec
provider_spec = InlineProviderSpec(
@ -78,7 +114,7 @@ async def test_resolve_impls_basic():
# Create provider registry with our provider
provider_registry = {Api.inference: {provider_spec.provider_type: provider_spec}}
run_config = StackRunConfig(
run_config = make_run_config(
image_name="test_image",
providers={
"inference": [

View file

@ -5,7 +5,6 @@
# the root directory of this source tree.
import time
from tempfile import TemporaryDirectory
import pytest
@ -16,8 +15,16 @@ from llama_stack.apis.inference import (
OpenAIUserMessageParam,
Order,
)
from llama_stack.core.storage.datatypes import InferenceStoreReference, SqliteSqlStoreConfig
from llama_stack.providers.utils.inference.inference_store import InferenceStore
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
@pytest.fixture(autouse=True)
def setup_backends(tmp_path):
"""Register SQL store backends for testing."""
db_path = str(tmp_path / "test.db")
register_sqlstore_backends({"sql_default": SqliteSqlStoreConfig(db_path=db_path)})
def create_test_chat_completion(
@ -44,167 +51,162 @@ def create_test_chat_completion(
async def test_inference_store_pagination_basic():
"""Test basic pagination functionality."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = InferenceStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
await store.initialize()
reference = InferenceStoreReference(backend="sql_default", table_name="chat_completions")
store = InferenceStore(reference, policy=[])
await store.initialize()
# Create test data with different timestamps
base_time = int(time.time())
test_data = [
("zebra-task", base_time + 1),
("apple-job", base_time + 2),
("moon-work", base_time + 3),
("banana-run", base_time + 4),
("car-exec", base_time + 5),
]
# Create test data with different timestamps
base_time = int(time.time())
test_data = [
("zebra-task", base_time + 1),
("apple-job", base_time + 2),
("moon-work", base_time + 3),
("banana-run", base_time + 4),
("car-exec", base_time + 5),
]
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Wait for all queued writes to complete
await store.flush()
# Test 1: First page with limit=2, descending order (default)
result = await store.list_chat_completions(limit=2, order=Order.desc)
assert len(result.data) == 2
assert result.data[0].id == "car-exec" # Most recent first
assert result.data[1].id == "banana-run"
assert result.has_more is True
assert result.last_id == "banana-run"
# Test 1: First page with limit=2, descending order (default)
result = await store.list_chat_completions(limit=2, order=Order.desc)
assert len(result.data) == 2
assert result.data[0].id == "car-exec" # Most recent first
assert result.data[1].id == "banana-run"
assert result.has_more is True
assert result.last_id == "banana-run"
# Test 2: Second page using 'after' parameter
result2 = await store.list_chat_completions(after="banana-run", limit=2, order=Order.desc)
assert len(result2.data) == 2
assert result2.data[0].id == "moon-work"
assert result2.data[1].id == "apple-job"
assert result2.has_more is True
# Test 2: Second page using 'after' parameter
result2 = await store.list_chat_completions(after="banana-run", limit=2, order=Order.desc)
assert len(result2.data) == 2
assert result2.data[0].id == "moon-work"
assert result2.data[1].id == "apple-job"
assert result2.has_more is True
# Test 3: Final page
result3 = await store.list_chat_completions(after="apple-job", limit=2, order=Order.desc)
assert len(result3.data) == 1
assert result3.data[0].id == "zebra-task"
assert result3.has_more is False
# Test 3: Final page
result3 = await store.list_chat_completions(after="apple-job", limit=2, order=Order.desc)
assert len(result3.data) == 1
assert result3.data[0].id == "zebra-task"
assert result3.has_more is False
async def test_inference_store_pagination_ascending():
"""Test pagination with ascending order."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = InferenceStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
await store.initialize()
reference = InferenceStoreReference(backend="sql_default", table_name="chat_completions")
store = InferenceStore(reference, policy=[])
await store.initialize()
# Create test data
base_time = int(time.time())
test_data = [
("delta-item", base_time + 1),
("charlie-task", base_time + 2),
("alpha-work", base_time + 3),
]
# Create test data
base_time = int(time.time())
test_data = [
("delta-item", base_time + 1),
("charlie-task", base_time + 2),
("alpha-work", base_time + 3),
]
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Wait for all queued writes to complete
await store.flush()
# Test ascending order pagination
result = await store.list_chat_completions(limit=1, order=Order.asc)
assert len(result.data) == 1
assert result.data[0].id == "delta-item" # Oldest first
assert result.has_more is True
# Test ascending order pagination
result = await store.list_chat_completions(limit=1, order=Order.asc)
assert len(result.data) == 1
assert result.data[0].id == "delta-item" # Oldest first
assert result.has_more is True
# Second page with ascending order
result2 = await store.list_chat_completions(after="delta-item", limit=1, order=Order.asc)
assert len(result2.data) == 1
assert result2.data[0].id == "charlie-task"
assert result2.has_more is True
# Second page with ascending order
result2 = await store.list_chat_completions(after="delta-item", limit=1, order=Order.asc)
assert len(result2.data) == 1
assert result2.data[0].id == "charlie-task"
assert result2.has_more is True
async def test_inference_store_pagination_with_model_filter():
"""Test pagination combined with model filtering."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = InferenceStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
await store.initialize()
reference = InferenceStoreReference(backend="sql_default", table_name="chat_completions")
store = InferenceStore(reference, policy=[])
await store.initialize()
# Create test data with different models
base_time = int(time.time())
test_data = [
("xyz-task", base_time + 1, "model-a"),
("def-work", base_time + 2, "model-b"),
("pqr-job", base_time + 3, "model-a"),
("abc-run", base_time + 4, "model-b"),
]
# Create test data with different models
base_time = int(time.time())
test_data = [
("xyz-task", base_time + 1, "model-a"),
("def-work", base_time + 2, "model-b"),
("pqr-job", base_time + 3, "model-a"),
("abc-run", base_time + 4, "model-b"),
]
# Store test chat completions
for completion_id, timestamp, model in test_data:
completion = create_test_chat_completion(completion_id, timestamp, model)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Store test chat completions
for completion_id, timestamp, model in test_data:
completion = create_test_chat_completion(completion_id, timestamp, model)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Wait for all queued writes to complete
await store.flush()
# Test pagination with model filter
result = await store.list_chat_completions(limit=1, model="model-a", order=Order.desc)
assert len(result.data) == 1
assert result.data[0].id == "pqr-job" # Most recent model-a
assert result.data[0].model == "model-a"
assert result.has_more is True
# Test pagination with model filter
result = await store.list_chat_completions(limit=1, model="model-a", order=Order.desc)
assert len(result.data) == 1
assert result.data[0].id == "pqr-job" # Most recent model-a
assert result.data[0].model == "model-a"
assert result.has_more is True
# Second page with model filter
result2 = await store.list_chat_completions(after="pqr-job", limit=1, model="model-a", order=Order.desc)
assert len(result2.data) == 1
assert result2.data[0].id == "xyz-task"
assert result2.data[0].model == "model-a"
assert result2.has_more is False
# Second page with model filter
result2 = await store.list_chat_completions(after="pqr-job", limit=1, model="model-a", order=Order.desc)
assert len(result2.data) == 1
assert result2.data[0].id == "xyz-task"
assert result2.data[0].model == "model-a"
assert result2.has_more is False
async def test_inference_store_pagination_invalid_after():
"""Test error handling for invalid 'after' parameter."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = InferenceStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
await store.initialize()
reference = InferenceStoreReference(backend="sql_default", table_name="chat_completions")
store = InferenceStore(reference, policy=[])
await store.initialize()
# Try to paginate with non-existent ID
with pytest.raises(ValueError, match="Record with id='non-existent' not found in table 'chat_completions'"):
await store.list_chat_completions(after="non-existent", limit=2)
# Try to paginate with non-existent ID
with pytest.raises(ValueError, match="Record with id='non-existent' not found in table 'chat_completions'"):
await store.list_chat_completions(after="non-existent", limit=2)
async def test_inference_store_pagination_no_limit():
"""Test pagination behavior when no limit is specified."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = InferenceStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
await store.initialize()
reference = InferenceStoreReference(backend="sql_default", table_name="chat_completions")
store = InferenceStore(reference, policy=[])
await store.initialize()
# Create test data
base_time = int(time.time())
test_data = [
("omega-first", base_time + 1),
("beta-second", base_time + 2),
]
# Create test data
base_time = int(time.time())
test_data = [
("omega-first", base_time + 1),
("beta-second", base_time + 2),
]
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Store test chat completions
for completion_id, timestamp in test_data:
completion = create_test_chat_completion(completion_id, timestamp)
input_messages = [OpenAIUserMessageParam(role="user", content=f"Test message for {completion_id}")]
await store.store_chat_completion(completion, input_messages)
# Wait for all queued writes to complete
await store.flush()
# Wait for all queued writes to complete
await store.flush()
# Test without limit
result = await store.list_chat_completions(order=Order.desc)
assert len(result.data) == 2
assert result.data[0].id == "beta-second" # Most recent first
assert result.data[1].id == "omega-first"
assert result.has_more is False
# Test without limit
result = await store.list_chat_completions(order=Order.desc)
assert len(result.data) == 2
assert result.data[0].id == "beta-second" # Most recent first
assert result.data[1].id == "omega-first"
assert result.has_more is False

View file

@ -6,6 +6,7 @@
import time
from tempfile import TemporaryDirectory
from uuid import uuid4
import pytest
@ -15,8 +16,18 @@ from llama_stack.apis.agents.openai_responses import (
OpenAIResponseObject,
)
from llama_stack.apis.inference import OpenAIMessageParam, OpenAIUserMessageParam
from llama_stack.core.storage.datatypes import ResponsesStoreReference, SqliteSqlStoreConfig
from llama_stack.providers.utils.responses.responses_store import ResponsesStore
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from llama_stack.providers.utils.sqlstore.sqlstore import register_sqlstore_backends
def build_store(db_path: str, policy: list | None = None) -> ResponsesStore:
backend_name = f"sql_responses_{uuid4().hex}"
register_sqlstore_backends({backend_name: SqliteSqlStoreConfig(db_path=db_path)})
return ResponsesStore(
ResponsesStoreReference(backend=backend_name, table_name="responses"),
policy=policy or [],
)
def create_test_response_object(
@ -54,7 +65,7 @@ async def test_responses_store_pagination_basic():
"""Test basic pagination functionality for responses store."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Create test data with different timestamps
@ -103,7 +114,7 @@ async def test_responses_store_pagination_ascending():
"""Test pagination with ascending order."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Create test data
@ -141,7 +152,7 @@ async def test_responses_store_pagination_with_model_filter():
"""Test pagination combined with model filtering."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Create test data with different models
@ -182,7 +193,7 @@ async def test_responses_store_pagination_invalid_after():
"""Test error handling for invalid 'after' parameter."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Try to paginate with non-existent ID
@ -194,7 +205,7 @@ async def test_responses_store_pagination_no_limit():
"""Test pagination behavior when no limit is specified."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Create test data
@ -226,7 +237,7 @@ async def test_responses_store_get_response_object():
"""Test retrieving a single response object."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Store a test response
@ -254,7 +265,7 @@ async def test_responses_store_input_items_pagination():
"""Test pagination functionality for input items."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Store a test response with many inputs with explicit IDs
@ -335,7 +346,7 @@ async def test_responses_store_input_items_before_pagination():
"""Test before pagination functionality for input items."""
with TemporaryDirectory() as tmp_dir:
db_path = tmp_dir + "/test.db"
store = ResponsesStore(SqliteSqlStoreConfig(db_path=db_path), policy=[])
store = build_store(db_path)
await store.initialize()
# Store a test response with many inputs with explicit IDs