Update app.py

app.py

@@ -1,63 +1,27 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import keras
+import keras_nlp
 
-"""
-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")
+import numpy as np
+import pandas as pd
+keras.utils.set_random_seed(42)
 
+gemma_lm = keras_nlp.models.CausalLM.from_preset("hf://soufyane/gemma_2b_instruct_FT_DATA_SCIENCE_lora36_1")
 
-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]})
+def generate_answer(history, question):
+    # Replace this with the actual code to generate the answer using your model
+    answer = gemma_lm.generate(f"You are an AI Agent specialized to answer to questions about Data Science and be greatfull and nice and helpfull\n\nQuestion:\n{question}\n\nAnswer:\n", max_length=1024)
+    history.append((question, answer))
+    return history
 
-    messages.append({"role": "user", "content": message})
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Chatbot")
+    chatbot = gr.Chatbot()
+    with gr.Row():
+        txt = gr.Textbox(show_label=False, placeholder="Enter your question here...")
+        txt.submit(generate_answer, [chatbot, txt], chatbot)
 
-    response = ""
-
-    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
-
-        response += token
-        yield response
-
-"""
-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()
+# Launch the interface
+demo.launch()