upd lang env

app.py

@@ -5,7 +5,7 @@ import argparse
 import warnings
 import gradio as gr
 from generate import generate_music, get_args
-from utils import WEIGHTS_DIR, TEMP_DIR, LANG
+from utils import WEIGHTS_DIR, TEMP_DIR, EN_US
 
 EN2ZH = {
     "Cite": "引用",
@@ -43,7 +43,7 @@ EN2ZH = {
 
 
 def _L(en_txt: str):
-    return en_txt if LANG else f"{en_txt} ({EN2ZH[en_txt]})"
+    return en_txt if EN_US else f"{en_txt} ({EN2ZH[en_txt]})"
 
 
 def infer_by_template(dataset: str, v: str, a: str, add_chord: bool):
@@ -190,14 +190,14 @@ def save_template(label: str, pitch_std: str, mode: str, tempo: int, octave: int
 if __name__ == "__main__":
     warnings.filterwarnings("ignore")
     with gr.Blocks() as demo:
-        if LANG:
+        if EN_US:
             gr.Markdown(
                 "## The current CPU-based version on HuggingFace has slow inference, you can access the GPU-based mirror on [ModelScope](https://www.modelscope.cn/studios/monetjoe/EMelodyGen)"
             )
         with gr.Row():
             with gr.Column():
                 gr.Video(
-                    "./demo.mp4" if LANG else "./src/tutorial.mp4",
+                    "./demo.mp4" if EN_US else "./src/tutorial.mp4",
                     label=_L("Video demo"),
                     show_download_button=False,
                     show_share_button=False,

utils.py

@@ -9,10 +9,10 @@ import huggingface_hub
 from tqdm import tqdm
 
 TEMP_DIR = "./__pycache__"
-LANG = os.getenv("language")
+EN_US = os.getenv("LANG") != "zh_CN.UTF-8"
 WEIGHTS_DIR = (
     huggingface_hub.snapshot_download("monetjoe/EMelodyGen", cache_dir=TEMP_DIR)
-    if LANG
+    if EN_US
     else modelscope.snapshot_download("monetjoe/EMelodyGen", cache_dir=TEMP_DIR)
 )
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")