Create app.py

app.py

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+import spaces
+import gradio as gr
+from transformers import pipeline
+import torch
+
+# Initialize the pipeline
+pipe = pipeline(
+    "text-generation",
+    model="sarvamai/sarvam-translate",
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+)
+
+@spaces.GPU
+def generate_response(tgt_lang, user_prompt):
+    messages = [
+        {"role": "system", "content": f"Translate the following sentence into {tgt_lang}."},
+        {"role": "user", "content": user_prompt},
+    ]
+    
+    output = pipe(messages, max_new_tokens=2048)
+    return output[0]["generated_text"][-1]["content"]
+
+# Create Gradio UI
+demo = gr.Interface(
+    fn=generate_response,
+    inputs=[
+        gr.Radio(["Hindi", "Bengali", "Marathi", "Telugu", "Tamil", "Gujarati", "Urdu", "Kannada", "Odia", "Malayalam", "Punjabi", "Assamese", "Maithili", "Santali", "Kashmiri", "Nepali", "Sindhi", "Dogri", "Konkani", "Manipuri (Meitei)", "Bodo", "Sanskrit"], label="Target Language", value="Hindi"),
+        gr.Textbox(label="Input Text", value="Be the change you wish to see in the world."),
+    ],
+    outputs=gr.Textbox(label="Translation"),
+    title="SARVAM - TRANSLATE",
+    description="Now supporting 22 Indian languages and structured long-form text"
+)
+
+# Launch the app
+demo.launch()