Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import torch
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-# Load model
+# --- Load the model ---
 model_path = "itsmeussa/AdabTranslate-Darija"
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -10,6 +10,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_path).to(device).eval()
 
 def translate_darija_to_msa(text):
+    """Takes Darija text and returns MSA translation"""
     with torch.no_grad():
         inputs = tokenizer(text, return_tensors="pt").to(device)
         output_ids = model.generate(
@@ -22,10 +23,16 @@ def translate_darija_to_msa(text):
         )
     return tokenizer.decode(output_ids[0], skip_special_tokens=True)
 
+# --- Build Gradio app ---
 with gr.Blocks() as demo:
-    gr.HTML(open("index.html", encoding="utf-8").read())  # your chat UI
+    # Load your custom HTML file into the interface
+    gr.HTML(open("index.html", encoding="utf-8").read())
+
+    # Invisible components to "link" JS → Python
     user_in = gr.Textbox(visible=False)
     bot_out = gr.Textbox(visible=False)
+
+    # Connect backend function
     user_in.submit(translate_darija_to_msa, inputs=user_in, outputs=bot_out)
 
 demo.launch()