Update app.py


app.py

@@ -1,64 +1,29 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+# Load Bengali AI model
+bangla_ai = pipeline("text2text-generation", model="csebuetnlp/banglat5")
 
-    messages.append({"role": "user", "content": message})
+# Custom Q&A pairs (edit these!)
+qa_pairs = {
+    "মুক্তিযুদ্ধ কবে শুরু হয়েছিল?": "১৯৭১ সালের ২৬ মার্চ।",
+    "When did the Liberation War begin?": "March 26, 1971."
+}
 
-    response = ""
+def chat(message):
+    # Check if question is in Q&A pairs
+    if message in qa_pairs:
+        return qa_pairs[message]
+    # Else, use BanglaT5
+    return bangla_ai(message, max_length=100)[0]['generated_text']
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+# Create interface
+with gr.Blocks(theme=gr.themes.Soft()) as app:
+    gr.Image("1000003774.png", width=200, label="NOTUNBANGLA")  # Your logo
+    gr.ChatInterface(chat, title="NOTUNBANGLA AI", description="বাংলায় প্রশ্ন করুন")
 
-        response += token
-        yield response
+app.launch()
+  
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+For information on how to customize the