Update app.py

app.py

@@ -1,63 +1,53 @@
+import google.generativeai as genai
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-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]})
-
-    messages.append({"role": "user", "content": message})
-
-    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)",
-        ),
-    ],
-)
-
-
+import os  # Import the os module for environment variables
+
+# Get the API Key from Hugging Face Secrets
+api_key = os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=api_key)
+
+# Initialize model and chat (outside the function)
+model = genai.GenerativeModel("gemini-pro")
+chat = model.start_chat(history=[])
+
+def get_gemini_response(question):
+    response = chat.send_message(question, stream=True)
+    full_response = ""
+    for chunk in response:
+        full_response += chunk.text
+    return full_response
+
+# Interface using Gradio
+theme = gr.themes.Soft()  
+with gr.Blocks(theme=theme, css=".gradio-container {background-color: #f0f5f9}") as demo:
+    gr.Markdown(
+        """
+        <div style="text-align: center;">
+            <h1 style="color: #007bff;">Debyez Chatbot</h1>
+            <p style="color: #6c757d;">Ask me anything! 💬</p>
+        </div>
+        """
+    )
+
+    chatbot = gr.Chatbot(elem_classes="colorful-chatbot") 
+    msg = gr.Textbox(label="Your Message", placeholder="Type your message here...")
+
+    # Colorful Clear Button
+    clear = gr.ClearButton(
+        [msg, chatbot],
+        value="Clear Conversation",
+        variant="primary",  
+    )
+
+    # Response Function (unchanged)
+    def respond(message, chat_history):
+        bot_message = get_gemini_response(message)
+        chat_history.append((message, bot_message))
+        return "", chat_history
+    
+    # Submit Message & Update Chat
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+
+# Launch the Chat Interface
 if __name__ == "__main__":
     demo.launch()