app.py

import gradio as gr
import requests
import os
import json
import google.generativeai as genai

# Load environment variables
genai.configure(api_key=os.environ["geminiapikey"])
read_key = os.environ.get('HF_TOKEN', None)

custom_css = ".md{height:450px}"

def predict(prompt):
    # Create the model
    generation_config = {
        "temperature": 1,
        "top_p": 0.95,
        "top_k": 40,
        "max_output_tokens": 8192,
        "response_mime_type": "text/plain",
    }

    model = genai.GenerativeModel(
        model_name="gemini-2.0-flash-exp",
        generation_config=generation_config,
    )

    chat_session = model.start_chat(
        history=[
        ]
    )
    
    response = chat_session.send_message(prompt)   
    return response.text

# Create the Gradio interface
with gr.Blocks(css=custom_css) as demo:
    with gr.Row():
        ort_input = gr.Textbox(label="prompt", placeholder="Gib den Namen des Ortes ein")
    with gr.Row():
        details_output = gr.Markdown(label="answer",elem_id="md")        
        #details_output = gr.Textbox(label="Ausgabe", value = f"\n\n\n\n")
        
    with gr.Row():
        clearbutton = gr.Button("Clear")  
        button = gr.Button("Senden")    

    # Connect the button to the function
    button.click(fn=predict, inputs=ort_input, outputs=details_output)
    clearbutton.click(fn=clear, inputs=[], outputs=details_output)

# Launch the Gradio application
demo.launch()