Update app.py

app.py

@@ -1,15 +1,13 @@
 import base64
 import os
-import gradio as gr
 from google import genai
 from google.genai import types
+import gradio as gr
 
-def generate_response(user_input):
+def generate_text(user_input):
     try:
-        client = genai.Client(
-            api_key=os.environ.get("GEMINI_API_KEY"),
-        )
-
+        client = genai.Client(api_key=os.environ.get("GEMINI_API_KEY"))
+        
         model = "gemini-2.5-pro-exp-03-25"
         contents = [
             types.Content(
@@ -24,91 +22,27 @@ def generate_response(user_input):
             response_mime_type="text/plain",
         )
 
-        full_response = ""
+        response = []
         for chunk in client.models.generate_content_stream(
             model=model,
             contents=contents,
             config=generate_content_config,
         ):
-            if chunk.text:
-                full_response += chunk.text
-                yield full_response  # Yield intermediate results for streaming effect
-
-        return full_response
+            response.append(chunk.text)
+            
+        return ''.join(response)
+    
     except Exception as e:
-        return f"An error occurred: {str(e)}"
-
-# Custom CSS for better appearance
-css = """
-.gradio-container {
-    max-width: 800px;
-    margin: auto;
-}
-footer {
-    visibility: hidden;
-}
-"""
+        return f"Error: {str(e)}"
 
-# Create the Gradio interface
-with gr.Blocks(css=css, title="Gemini AI Chat") as demo:
-    gr.Markdown("# 🌟 Gemini AI Chat Interface")
-    gr.Markdown("Enter your prompt and get AI-generated responses from Google's Gemini model")
-    
-    with gr.Row():
-        with gr.Column(scale=7):
-            user_input = gr.Textbox(
-                label="Your Prompt",
-                placeholder="Type your message here...",
-                lines=5,
-                max_lines=10,
-                interactive=True,
-                container=False,
-            )
-        with gr.Column(scale=3):
-            temperature = gr.Slider(
-                minimum=0.1,
-                maximum=2.0,
-                value=1.0,
-                step=0.1,
-                label="Creativity (Temperature)",
-                interactive=True,
-            )
-    
-    submit_btn = gr.Button("Generate Response", variant="primary")
-    clear_btn = gr.Button("Clear", variant="secondary")
-    
-    output = gr.Textbox(
-        label="AI Response",
-        placeholder="AI response will appear here...",
-        lines=10,
-        max_lines=20,
-        interactive=False,
-    )
-    
-    examples = gr.Examples(
-        examples=[
-            ["Explain quantum computing in simple terms"],
-            ["Write a short poem about artificial intelligence"],
-            ["What are the latest advancements in renewable energy?"],
-        ],
-        inputs=user_input,
-        label="Example Prompts",
-    )
-    
-    # Event handlers
-    submit_btn.click(
-        fn=generate_response,
-        inputs=user_input,
-        outputs=output,
-        api_name="generate"
-    )
-    
-    clear_btn.click(
-        fn=lambda: ("", ""),
-        inputs=[],
-        outputs=[user_input, output],
-    )
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=gr.Textbox(lines=4, placeholder="Enter your prompt here...", label="Input Text"),
+    outputs=gr.Textbox(label="Generated Text"),
+    title="Gemini 2.5 Pro Text Generator",
+    description="Generate text using the Gemini 2.5 Pro model with streaming support",
+    allow_flagging="never"
+)
 
-# Run the app
 if __name__ == "__main__":
-    demo.queue().launch(server_port=7860, share=False)
+    iface.launch()