import gradio as gr
from transformers import pipeline, set_seed

generator = pipeline('text-generation', model='google/palm-2-large-uncased', device=0)

def generate_text(prompt, length=50, temperature=0.7, seed=42):
    set_seed(seed)
    output = generator(prompt, max_length=length, do_sample=True, temperature=temperature)
    return output[0]['generated_text']

import gradio as gr
from transformers import pipeline, set_seed
import logging

logging.basicConfig(level=logging.INFO)

def generate_text(prompt, length=50, temperature=0.7, seed=42):
    try:
        set_seed(seed)
        generator = pipeline('text-generation', model='google/palm-2-large-uncased', device=0)
        output = generator(prompt, max_length=length, do_sample=True, temperature=temperature)
        return output[0]['generated_text']
    except Exception as e:
        logging.error(f"Error generating text: {e}")
        return "Error generating text. Please try again later."

inputs = gr.inputs.Textbox(lines=5, label="Prompt")
outputs = gr.outputs.Textbox(label="Output Text")
temperature_slider = gr.inputs.Slider(minimum=0.1, maximum=1.5, default=0.7, label="Temperature")
length_slider = gr.inputs.Slider(minimum=10, maximum=200, default=50, label="Length")
seed_input = gr.inputs.Number(default=42, label="Seed")

title = "Generative AI"
description = "Use PaLM 2 to generate text based on a prompt."
examples = [["The quick brown fox", 50, 0.7, 42]]

iface = gr.Interface(fn=generate_text, inputs=[inputs, length_slider, temperature_slider, seed_input], outputs=outputs, title=title, description=description, examples=examples)

iface.launch(inbrowser=True, share=True)