dpe

app.py

@@ -1,45 +1,23 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# -------------------------------
-# CONFIGURATION
-# -------------------------------
-MODEL_NAME = "ai4bharat/indictrans2-m2m-1B"
+# ✅ Use valid model
+MODEL_NAME = "ai4bharat/indictrans2-indic-indic-1B"
 
-# -------------------------------
-# LOAD MODEL & TOKENIZER
-# -------------------------------
-print("📥 Loading model... This may take a moment.")
+# Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
 model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME, trust_remote_code=True)
-print("✅ Model loaded successfully!")
 
-# -------------------------------
-# TRANSLATION FUNCTION
-# -------------------------------
 def translate(text: str, src_lang: str, tgt_lang: str) -> str:
-    """
-    Translate text from `src_lang` to `tgt_lang` using IndicTrans2.
-
-    Args:
-        text (str): Input text to translate.
-        src_lang (str): Source language code (e.g., 'ta', 'en', 'hi').
-        tgt_lang (str): Target language code (e.g., 'en', 'ta', 'fr').
-
-    Returns:
-        str: Translated text or error message.
-    """
+    """Translate text from src_lang to tgt_lang using IndicTrans2."""
     if not text.strip():
         return "⚠️ Please enter some text to translate."
 
-    if not src_lang.strip() or not tgt_lang.strip():
-        return "⚠️ Please provide both source and target language codes."
-
     src_lang = src_lang.strip().lower()
     tgt_lang = tgt_lang.strip().lower()
 
     try:
-        # Format input for IndicTrans2
+        # Format input as required by IndicTrans2
         formatted_text = f"{src_lang}>>{tgt_lang} {text}"
         inputs = tokenizer(formatted_text, return_tensors="pt")
 
@@ -47,45 +25,25 @@ def translate(text: str, src_lang: str, tgt_lang: str) -> str:
         output_tokens = model.generate(**inputs, max_length=512)
         translation = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
 
-        return translation.strip()
-
+        return translation
     except Exception as e:
-        return f"❌ Error during translation: {str(e)}"
+        return f"❌ Error: {str(e)}"
 
-# -------------------------------
-# GRADIO UI
-# -------------------------------
+# Gradio interface
 demo = gr.Interface(
     fn=translate,
     inputs=[
-        gr.Textbox(
-            label="Text",
-            placeholder="Enter your text here...",
-            lines=4
-        ),
-        gr.Textbox(
-            label="Source Language Code (e.g., ta, en, hi)",
-            placeholder="ta"
-        ),
-        gr.Textbox(
-            label="Target Language Code (e.g., en, ta, fr)",
-            placeholder="en"
-        )
+        gr.Textbox(label="Text", placeholder="Enter your text here..."),
+        gr.Textbox(label="Source Language Code (e.g., ta, hi, kn)", placeholder="ta"),
+        gr.Textbox(label="Target Language Code (e.g., en, hi, kn)", placeholder="en")
     ],
-    outputs=gr.Textbox(
-        label="Translated Text",
-        lines=4
-    ),
-    title="🌐 IndicTrans2 Language Translator",
+    outputs=gr.Textbox(label="Translated Text"),
+    title="IndicTrans2 Language Translator",
     description=(
-        "Translate between Indian and international languages using "
-        "[ai4bharat/indictrans2-m2m-1B](https://huggingface.co/ai4bharat/indictrans2-m2m-1B)."
-    ),
-    allow_flagging="never"
+        "🌐 Translate text between Indian languages using "
+        "[ai4bharat/indictrans2-indic-indic-1B](https://huggingface.co/ai4bharat/indictrans2-indic-indic-1B)."
+    )
 )
 
-# -------------------------------
-# RUN APP
-# -------------------------------
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch()

requirements.txt

@@ -1,5 +1,3 @@
-transformers>=4.39.0
-torch>=2.0.0
-sentencepiece
-protobuf
-gradio>=4.0.0
+gradio>=5.0
+transformers>=4.40
+torch>=2.1