Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_map = {
+    "Tamil": "Harisanth/mbart-chatbot-tamil",
+    "Sinhala": "Harisanth/mbart-chatbot-sinhala",
+    "English": "Harisanth/mbart-chatbot-english",
+    "Tanglish": "Harisanth/mbart-chatbot-tanglish"
+}
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+def chat_fn(text, lang):
+    repo = model_map[lang]
+    tok = AutoTokenizer.from_pretrained(repo)
+    mod = AutoModelForCausalLM.from_pretrained(repo).to(device)
+    tok.src_lang = {'Tamil':'ta_IN','Sinhala':'si_LK','English':'en_XX','Tanglish':'en_XX'}[lang]
+    inp = tok(text, return_tensors="pt").to(device)
+    out = mod.generate(**inp, max_length=100, forced_bos_token_id=tok.lang_code_to_id[tok.src_lang])
+    return tok.decode(out[0], skip_special_tokens=True)
+
+iface = gr.Interface(
+    fn=chat_fn,
+    inputs=["text", gr.Radio(["Tamil","Sinhala","English","Tanglish"], label="Language")],
+    outputs="text",
+    title="Multilingual Chatbot",
+    description="A fine-tuned mBART chatbot by Harisanth"
+)
+
+if __name__ == "__main__":
+    iface.launch()