app.py

import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from diffusers import StableDiffusionPipeline

# ---------------- CHAT ----------------
chat_model_id = "Qwen/Qwen2.5-1.5B-Instruct"

tokenizer = AutoTokenizer.from_pretrained(chat_model_id)
chat_model = AutoModelForCausalLM.from_pretrained(
    chat_model_id,
    torch_dtype=torch.float32
)

def chat_fn(message, history):
    messages = [{"role": "user", "content": message}]
    prompt = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
    )

    inputs = tokenizer(prompt, return_tensors="pt")
    output = chat_model.generate(
        **inputs,
        max_new_tokens=200,
        temperature=0.7
    )
    return tokenizer.decode(output[0], skip_special_tokens=True)

# ---------------- IMAGE ----------------
# ---------- IMAGE MODEL ----------
from diffusers import StableDiffusionPipeline

img_pipe = StableDiffusionPipeline.from_pretrained(
    "stabilityai/sdxl-turbo",
    torch_dtype=torch.float32
)

img_pipe = img_pipe.to("cpu")


# ---------------- UI ----------------
with gr.Blocks(
    title="MaindAI",
    theme=gr.themes.Soft(primary_hue="blue")
) as app:

    gr.Image(
        value="Maindai.png",
        show_label=False,
        height=140
    )

    gr.Markdown(
        "<h1 style='text-align:center;color:#4da6ff;'>MaindAI</h1>"
    )

    with gr.Row():
        with gr.Column(scale=1):
            gr.ChatInterface(chat_fn)

        with gr.Column(scale=1):
            prompt = gr.Textbox(label="Görsel açıklaması")
            btn = gr.Button("🎨 Oluştur")
            output = gr.Image()
            btn.click(generate_image, prompt, output)