app.py

import streamlit as st
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer

# Load the Mistral model and tokenizer
model_name = "mistralai/Mistral-7B-Instruct-v0.2"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Initialize the text generation pipeline
generator = pipeline('text-generation', model=model, tokenizer=tokenizer)

# Streamlit UI
st.title("Waifu Character Generator")

# User inputs
name = st.text_input("Name of the Waifu")
hair_color = st.selectbox("Hair Color", ["Blonde", "Brunette", "Red", "Black", "Blue", "Pink"])
personality = st.selectbox("Personality", ["Tsundere", "Yandere", "Kuudere", "Dandere", "Genki", "Normal"])
outfit_style = st.selectbox("Outfit Style", ["School Uniform", "Maid Outfit", "Casual", "Kimono", "Gothic Lolita"])

# Generate button
if st.button("Generate Waifu"):
    # Generate character description
    prompt = f"Create a waifu character named {name} with {hair_color} hair, a {personality} personality, and wearing a {outfit_style}."
    result = generator(prompt, max_length=150, num_return_sequences=1)[0]['generated_text']
    
    # Display the generated character
    st.subheader("Generated Waifu Character")
    st.write(result)