app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the Llama 3.1 model and tokenizer
model_name = "decapoda-research/llama-30b-hf"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate an email
def generate_email(business_or_individual, company_details, personal_details, tokens, tone):
    # ... (rest of the generate_email function remains the same)

# Create the Gradio interface with a dark theme
iface = gr.Interface(
    fn=generate_email,
    inputs=[
        gr.Radio(["Business", "Individual"], label="Business or Individual", theme=gr.themes.Monochrome()),
        gr.Group(
            [
                gr.Textbox(label="Company Name", theme=gr.themes.Monochrome()),
                gr.Textbox(label="Industry", theme=gr.themes.Monochrome()),
                gr.Textbox(label="Recipient Role", theme=gr.themes.Monochrome()),
            ], label="Company Details", visible=False, theme=gr.themes.Monochrome()
        ),
        gr.Group(
            [
                gr.Textbox(label="Industry", theme=gr.themes.Monochrome())
            ], label="Personal Details", visible=False, theme=gr.themes.Monochrome()
        ),
        gr.Slider(minimum=200, maximum=1000, step=100, label="Tokens", theme=gr.themes.Monochrome()),
        gr.Radio(["Professional", "Casual", "Cold"], label="Tone", theme=gr.themes.Monochrome())
    ],
    outputs="text",
    title="Email Generator",
    theme=gr.themes.Monochrome()  # Set the overall theme to dark
)

# Launch the Gradio interface
iface.launch()