app.py

import base64
import os
import gradio as gr
from google import genai
from google.genai import types

def generate_response(user_input):
    try:
        client = genai.Client(
            api_key=os.environ.get("GEMINI_API_KEY"),
        )

        model = "gemini-2.5-pro-exp-03-25"
        contents = [
            types.Content(
                role="user",
                parts=[
                    types.Part.from_text(text=user_input),
                ],
            ),
        ]
        generate_content_config = types.GenerateContentConfig(
            temperature=2,
            response_mime_type="text/plain",
        )

        full_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
    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;
}
"""

# 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],
    )

# Run the app
if __name__ == "__main__":
    demo.queue().launch(server_port=7860, share=False)