File size: 1,047 Bytes
c2d58b3
f632edb
c2d58b3
 
2468ba3
f632edb
e26f64e
 
 
 
 
 
 
 
2056fc1
 
6b214e4
 
 
 
 
 
 
e26f64e
 
2468ba3
e26f64e
c2d58b3
f632edb
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
from pydantic import BaseSettings
from typing import Dict

class Settings(BaseSettings):
    # A dictionary to map shipper_id to the appropriate model
    model_map: Dict[int, str] = {
        61: "donut-v16",
        81: "donut-v16",
        139: "donut-v16",
        165: "donut-v17",
        145: "donut-v17",
        127: "donut-v17",
    }
    space_base: str = "senga-ml"
    processor: str = "senga-ml/donut-v16"
    model: str = "senga-ml/donut-v16"
    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"

    def get_model_url(self, shipper_id: int) -> str:
        model = self.model_map.get(shipper_id, "default-model")  
        return f"https://{self.space_base}/{model}"

settings = Settings()