tabbyAPI-ollama/common/model.py
turboderp 0eb8fa5d1e
[fix] Bring draft progress and model progress in sync with model loader (#125)
* Bring draft progress and model progress in sync with model loader

* Fix formatting
2024-06-03 19:41:02 +02:00

93 lines
2.5 KiB
Python

"""
Manages the storage and utility of model containers.
Containers exist as a common interface for backends.
"""
import pathlib
from loguru import logger
from typing import Optional
from backends.exllamav2.model import ExllamaV2Container
from common.logger import get_loading_progress_bar
# Global model container
container: Optional[ExllamaV2Container] = None
def load_progress(module, modules):
"""Wrapper callback for load progress."""
yield module, modules
async def unload_model(skip_wait: bool = False):
"""Unloads a model"""
global container
await container.unload(skip_wait=skip_wait)
container = None
async def load_model_gen(model_path: pathlib.Path, **kwargs):
"""Generator to load a model"""
global container
# Check if the model is already loaded
if container and container.model:
loaded_model_name = container.get_model_path().name
if loaded_model_name == model_path.name and container.model_loaded:
raise ValueError(
f'Model "{loaded_model_name}" is already loaded! Aborting.'
)
# Unload the existing model
if container and container.model:
logger.info("Unloading existing model.")
await unload_model()
container = ExllamaV2Container(model_path.resolve(), False, **kwargs)
model_type = "draft" if container.draft_config else "model"
load_status = container.load_gen(load_progress, **kwargs)
progress = get_loading_progress_bar()
progress.start()
try:
async for module, modules in load_status:
if module == 0:
loading_task = progress.add_task(
f"[cyan]Loading {model_type} modules", total=modules
)
else:
progress.advance(loading_task)
yield module, modules, model_type
if module == modules:
# Switch to model progress if the draft model is loaded
if model_type == "draft":
model_type = "model"
else:
progress.stop()
finally:
progress.stop()
async def load_model(model_path: pathlib.Path, **kwargs):
async for _ in load_model_gen(model_path, **kwargs):
pass
async def load_loras(lora_dir, **kwargs):
"""Wrapper to load loras."""
if len(container.get_loras()) > 0:
await unload_loras()
return await container.load_loras(lora_dir, **kwargs)
async def unload_loras():
"""Wrapper to unload loras"""
await container.unload(loras_only=True)