Create app.py

app.py

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+import os, gradio as gr
+from openai import OpenAI
+
+MODEL = "gpt-4o-mini"  # multilingual, great for Hindi/Bangla
+SYSTEM_HI = "तुम एक सहायक हिन्दी सहायक हो। स्पष्ट, संक्षिप्त और सही उत्तर दो।"
+SYSTEM_BN = "তুমি একজন সহায়ক বাংলা সহকারী। সংক্ষিপ্ত, স্পষ্ট এবং সঠিক উত্তর দাও।"
+
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+def chat_fn(history, lang):
+    sys = SYSTEM_BN if lang == "bn" else SYSTEM_HI
+    # convert Gradio history -> OpenAI messages
+    msgs = [{"role": "system", "content": sys}]
+    for user, bot in history:
+        msgs.append({"role": "user", "content": user})
+        if bot:
+            msgs.append({"role": "assistant", "content": bot})
+
+    resp = client.chat.completions.create(model=MODEL, messages=msgs, temperature=0.6, max_tokens=400)
+    return resp.choices[0].message.content
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("### 🇮🇳 Indic Chat — हिंदी / বাংলা")
+    with gr.Row():
+        lang = gr.Radio(choices=[("हिन्दी","hi"), ("বাংলা","bn")], value=("हिन्दी","hi"), label="Language")
+    chat = gr.Chatbot(height=420, type="tuple")
+    txt = gr.Textbox(placeholder="Type in Hindi or Bangla…", autofocus=True)
+    send = gr.Button("Send")
+
+    def user_send(user_text, chat_state):
+        if not user_text.strip(): return gr.update(), chat_state
+        chat_state = chat_state + [(user_text, None)]
+        return "", chat_state
+
+    def bot_reply(chat_state, lang_val):
+        answer = chat_fn(chat_state, lang_val[1])
+        chat_state[-1] = (chat_state[-1][0], answer)
+        return chat_state
+
+    txt.submit(user_send, [txt, chat], [txt, chat]).then(bot_reply, [chat, lang], [chat])
+    send.click(user_send, [txt, chat], [txt, chat]).then(bot_reply, [chat, lang], [chat])
+
+demo.launch()