Create server.py

server.py

@@ -0,0 +1,31 @@
+import os
+import torch
+from transformers import AutoProcessor, SeamlessM4TForTextToText
+import gradio as gr
+
+MODEL_NAME = "facebook/hf-seamless-m4t-medium"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+processor = AutoProcessor.from_pretrained(MODEL_NAME)
+model     = SeamlessM4TForTextToText.from_pretrained(MODEL_NAME).to(device).eval()
+
+def translate(text, sourceLang, targetLang, auto_detect):
+    src = None if auto_detect else sourceLang
+    inputs = processor(text=text, src_lang=src, return_tensors="pt").to(device)
+    tokens = model.generate(**inputs, tgt_lang=targetLang)
+    return processor.decode(tokens[0].tolist(), skip_special_tokens=True)
+
+iface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Textbox(label="Text to translate"),
+        gr.Textbox(label="Source Language (e.g. eng)"),
+        gr.Textbox(label="Target Language (e.g. fra)"),
+        gr.Checkbox(label="Auto-detect source")
+    ],
+    outputs=gr.Textbox(label="Translated Text"),
+    title="iVoice Translate"
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))