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from pydantic import BaseSettings
class Settings(BaseSettings):
# Default values for the processor and model
processor: str = "senga-ml/naivas_lpos"
model: str = "senga-ml/naivas_lpos"
dataset: str = "senga-ml/dnotes-data-v6"
base_config: str = "naver-clova-ix/donut-base"
base_processor: str = "naver-clova-ix/donut-base"
base_model: str = "naver-clova-ix/donut-base"
inference_stats_file: str = "data/donut_inference_stats.json"
training_stats_file: str = "data/donut_training_stats.json"
evaluate_stats_file: str = "data/donut_evaluate_stats.json"
# The shipper_id to dynamically select model and processor
shipper_id: str = "default_shipper"
# Function to dynamically select model and processor based on shipper_id
def set_model(self):
if self.shipper_id == "61":
self.model = "senga-ml/donut-16"
self.processor = "senga-ml/donut-16"
elif self.shipper_id == "81":
self.model = "senga-ml/donut-16"
self.processor = "senga-ml/donut-16"
elif self.shipper_id == "139":
self.model = "senga-ml/donut-16"
self.processor = "senga-ml/donut-16"
elif self.shipper_id == "165"
self.model = "senga-ml/donut-17"
self.processor = "senga-ml/donut-17"
elif self.shipper_id == "127"
self.model = "senga-ml/donut-17"
self.processor = "senga-ml/donut-17"
elif self.shipper_id == "145"
self.model = "senga-ml/donut-17"
self.processor = "senga-ml/donut-17"
else:
self.model = self.base_model # Default to base model
self.processor = self.base_processor # Default to base processor
# Initialize dynamic model selection when settings are loaded
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.set_model() # Set the model based on shipper_id
settings = Settings()
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