bfa011e0ce
Embedding models are managed on a separate backend, but are run in parallel with the model itself. Therefore, manage this in a separate container with separate routes. Signed-off-by: kingbri <bdashore3@proton.me>
134 lines
4.1 KiB
Python
134 lines
4.1 KiB
Python
import pathlib
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from asyncio import CancelledError
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from typing import Optional
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from common import gen_logging, model
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from common.networking import get_generator_error, handle_request_disconnect
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from common.utils import unwrap
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from endpoints.core.types.model import (
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ModelCard,
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ModelCardParameters,
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ModelList,
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ModelLoadRequest,
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ModelLoadResponse,
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)
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def get_model_list(model_path: pathlib.Path, draft_model_path: Optional[str] = None):
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"""Get the list of models from the provided path."""
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# Convert the provided draft model path to a pathlib path for
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# equality comparisons
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if draft_model_path:
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draft_model_path = pathlib.Path(draft_model_path).resolve()
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model_card_list = ModelList()
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for path in model_path.iterdir():
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# Don't include the draft models path
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if path.is_dir() and path != draft_model_path:
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model_card = ModelCard(id=path.name)
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model_card_list.data.append(model_card) # pylint: disable=no-member
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return model_card_list
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async def get_current_model_list(model_type: str = "model"):
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"""
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Gets the current model in list format and with path only.
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Unified for fetching both models and embedding models.
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"""
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current_models = []
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model_path = None
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# Make sure the model container exists
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if model_type == "model" or model_type == "draft":
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if model.container:
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model_path = model.container.get_model_path(model_type == "draft")
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elif model_type == "embedding":
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if model.embeddings_container:
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model_path = model.embeddings_container.model_dir
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if model_path:
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current_models.append(ModelCard(id=model_path.name))
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return ModelList(data=current_models)
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def get_current_model():
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"""Gets the current model with all parameters."""
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model_params = model.container.get_model_parameters()
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draft_model_params = model_params.pop("draft", {})
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if draft_model_params:
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model_params["draft"] = ModelCard(
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id=unwrap(draft_model_params.get("name"), "unknown"),
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parameters=ModelCardParameters.model_validate(draft_model_params),
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)
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else:
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draft_model_params = None
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model_card = ModelCard(
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id=unwrap(model_params.pop("name", None), "unknown"),
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parameters=ModelCardParameters.model_validate(model_params),
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logging=gen_logging.PREFERENCES,
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)
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if draft_model_params:
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draft_card = ModelCard(
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id=unwrap(draft_model_params.pop("name", None), "unknown"),
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parameters=ModelCardParameters.model_validate(draft_model_params),
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)
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model_card.parameters.draft = draft_card
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return model_card
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async def stream_model_load(
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data: ModelLoadRequest,
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model_path: pathlib.Path,
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draft_model_path: str,
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):
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"""Request generation wrapper for the loading process."""
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# Set the draft model path if it exists
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load_data = data.model_dump()
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if draft_model_path:
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load_data["draft"]["draft_model_dir"] = draft_model_path
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load_status = model.load_model_gen(
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model_path, skip_wait=data.skip_queue, **load_data
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)
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try:
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async for module, modules, model_type in load_status:
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if module != 0:
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response = ModelLoadResponse(
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model_type=model_type,
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module=module,
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modules=modules,
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status="processing",
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)
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yield response.model_dump_json()
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if module == modules:
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response = ModelLoadResponse(
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model_type=model_type,
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module=module,
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modules=modules,
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status="finished",
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)
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yield response.model_dump_json()
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except CancelledError:
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# Get out if the request gets disconnected
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handle_request_disconnect(
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"Model load cancelled by user. "
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"Please make sure to run unload to free up resources."
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)
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except Exception as exc:
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yield get_generator_error(str(exc))
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