Update app.py

app.py

@@ -5,14 +5,12 @@ import scipy.io.wavfile
 from transformers import VitsModel, AutoTokenizer
 import re
 
-# Load model
 model = VitsModel.from_pretrained("Somali-tts/somali_tts_model")
 tokenizer = AutoTokenizer.from_pretrained("saleolow/somali-mms-tts")
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 model.eval()
 
-# Number words
 number_words = {
     0: "eber", 1: "koow", 2: "labo", 3: "seddex", 4: "afar", 5: "shan",
     6: "lix", 7: "todobo", 8: "sideed", 9: "sagaal", 10: "toban",
@@ -24,7 +22,6 @@ number_words = {
     100: "boqol", 1000: "kun"
 }
 
-# Number normalization
 def number_to_words(number):
     number = int(number)
     if number < 20:
@@ -77,7 +74,6 @@ def normalize_text(text):
     text = text.replace("ZamZam", "SamSam")
     return text
 
-# Text to Speech
 def tts(text):
     text = normalize_text(text)
     inputs = tokenizer(text, return_tensors="pt").to(device)
@@ -85,14 +81,13 @@ def tts(text):
         waveform = model(**inputs).waveform.squeeze().cpu().numpy()
     filename = "output.wav"
     scipy.io.wavfile.write(filename, rate=model.config.sampling_rate, data=(waveform * 32767).astype(np.int16))
-    return filename  # Let Gradio handle public URL
+    return filename  # let Gradio handle file URL
 
-# Gradio interface
+# ✅ This enables API access!
 gr.Interface(
     fn=tts,
     inputs=gr.Textbox(label="Geli qoraal Soomaali ah"),
     outputs=gr.Audio(type="filepath", label="Codka TTS"),
     title="Somali TTS",
-    description="Ku qor qoraal Soomaaliyeed si aad u maqasho cod dabiici ah."
+    description="Ku qor qoraal Soomaali ah si aad u maqasho codka.",
 ).queue().launch()
-