| from inference.core.cache import cache |
| from inference.core.interfaces.http.http_api import HttpInterface |
| from inference.core.managers.active_learning import ActiveLearningManager, BackgroundTaskActiveLearningManager |
| from inference.core.managers.base import ModelManager |
| from inference.core.managers.decorators.fixed_size_cache import WithFixedSizeCache |
| from inference.core.registries.roboflow import ( |
| RoboflowModelRegistry, |
| ) |
| import os |
| from prometheus_fastapi_instrumentator import Instrumentator |
|
|
| from inference.core.env import MAX_ACTIVE_MODELS, ACTIVE_LEARNING_ENABLED, LAMBDA |
| from inference.models.utils import ROBOFLOW_MODEL_TYPES |
|
|
| model_registry = RoboflowModelRegistry(ROBOFLOW_MODEL_TYPES) |
|
|
| if ACTIVE_LEARNING_ENABLED: |
| if LAMBDA: |
| model_manager = ActiveLearningManager(model_registry=model_registry, cache=cache) |
| else: |
| model_manager = BackgroundTaskActiveLearningManager(model_registry=model_registry, cache=cache) |
| else: |
| model_manager = ModelManager(model_registry=model_registry) |
|
|
| model_manager = WithFixedSizeCache( |
| model_manager, |
| max_size=MAX_ACTIVE_MODELS |
| ) |
|
|
| model_manager.model_manager.init_pingback() |
| interface = HttpInterface(model_manager) |
| app = interface.app |
| |
| |
| if os.environ.get("ENABLE_PROMETHEUS", False): |
| instrumentor = Instrumentator() |
| instrumentor.instrument(app).expose(app) |
|
|
| @app.on_event("startup") |
| async def _startup(): |
| instrumentor.expose(app) |
|
|
