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feat: Allow multiple ML models to be preloaded (#15418)

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2 changed files with 14 additions and 12 deletions
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8
docs/docs/install/environment-variables.md
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@ -159,10 +159,10 @@ Redis (Sentinel) URL example JSON before encoding:
| `MACHINE_LEARNING_WORKERS`<sup>\*2</sup> | Number of worker processes to spawn | `1` | machine learning |
| `MACHINE_LEARNING_HTTP_KEEPALIVE_TIMEOUT_S`<sup>\*3</sup> | HTTP Keep-alive time in seconds | `2` | machine learning |
| `MACHINE_LEARNING_WORKER_TIMEOUT` | Maximum time (s) of unresponsiveness before a worker is killed | `120` (`300` if using OpenVINO) | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL` | Name of the textual CLIP model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP__VISUAL` | Name of the visual CLIP model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION` | Name of the recognition portion of the facial recognition model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION` | Name of the detection portion of the facial recognition model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL` | Comma-separated list of (textual) CLIP model(s) to preload and cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP__VISUAL` | Comma-separated list of (visual) CLIP model(s) to preload and cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION` | Comma-separated list of (recognition) facial recognition model(s) to preload and cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION` | Comma-separated list of (detection) facial recognition model(s) to preload and cache | | machine learning |
| `MACHINE_LEARNING_ANN` | Enable ARM-NN hardware acceleration if supported | `True` | machine learning |
| `MACHINE_LEARNING_ANN_FP16_TURBO` | Execute operations in FP16 precision: increasing speed, reducing precision (applies only to ARM-NN) | `False` | machine learning |
| `MACHINE_LEARNING_ANN_TUNING_LEVEL` | ARM-NN GPU tuning level (1: rapid, 2: normal, 3: exhaustive) | `2` | machine learning |

18
machine-learning/app/main.py
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@ -77,29 +77,31 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
async def preload_models(preload: PreloadModelData) -> None:
log.info(f"Preloading models: clip:{preload.clip} facial_recognition:{preload.facial_recognition}")
async def load_models(model_string: str, model_type: ModelType, model_task: ModelTask) -> None:
for model_name in model_string.split(","):
model_name = model_name.strip()
model = await model_cache.get(model_name, model_type, model_task)
await load(model)
if preload.clip.textual is not None:
model = await model_cache.get(preload.clip.textual, ModelType.TEXTUAL, ModelTask.SEARCH)
await load(model)
await load_models(preload.clip.textual, ModelType.TEXTUAL, ModelTask.SEARCH)
if preload.clip.visual is not None:
model = await model_cache.get(preload.clip.visual, ModelType.VISUAL, ModelTask.SEARCH)
await load(model)
await load_models(preload.clip.visual, ModelType.VISUAL, ModelTask.SEARCH)
if preload.facial_recognition.detection is not None:
model = await model_cache.get(
await load_models(
preload.facial_recognition.detection,
ModelType.DETECTION,
ModelTask.FACIAL_RECOGNITION,
)
await load(model)
if preload.facial_recognition.recognition is not None:
model = await model_cache.get(
await load_models(
preload.facial_recognition.recognition,
ModelType.RECOGNITION,
ModelTask.FACIAL_RECOGNITION,
)
await load(model)
if preload.clip_fallback is not None:
log.warning(