app.py

import os
import gradio as gr
import torch
from openai import OpenAI

from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler

# ----------------- CHAT (HF Router) -----------------
HF_TOKEN = os.getenv("HF_TOKEN")

client = OpenAI(
    base_url="https://router.huggingface.co/v1",
    api_key=HF_TOKEN,
)

CHAT_MODEL = "HuggingFaceTB/SmolLM3-3B:hf-inference"
SYSTEM = "Sen MAIND AI'sin. Kısa, net ve yardımcı cevap ver."

def llm_reply(user_text: str) -> str:
    resp = client.chat.completions.create(
        model=CHAT_MODEL,
        messages=[
            {"role": "system", "content": SYSTEM},
            {"role": "user", "content": user_text},
        ],
        temperature=0.7,
        max_tokens=300,
    )
    return (resp.choices[0].message.content or "").strip()

def chat_fn(message, history):
    history = history or []
    history.append({"role": "user", "content": message})
    try:
        reply = llm_reply(message)
    except Exception as e:
        reply = f"⚠️ Chat hata: {e}"
    history.append({"role": "assistant", "content": reply})
    return history, ""

# ----------------- IMAGE (LOCAL in Space, CPU) -----------------
IMG_MODEL = "segmind/tiny-sd"  # küçük ve Space için uygun :contentReference[oaicite:1]{index=1}
img_pipe = None

def get_pipe():
    global img_pipe
    if img_pipe is None:
        pipe = StableDiffusionPipeline.from_pretrained(
            IMG_MODEL,
            torch_dtype=torch.float32,
        )
        pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
        pipe.enable_attention_slicing()   # RAM azaltır
        pipe = pipe.to("cpu")
        img_pipe = pipe
    return img_pipe

def gen_image(prompt: str, steps: int, size: int):
    if not prompt or not prompt.strip():
        raise gr.Error("Prompt boş.")
    pipe = get_pipe()
    with torch.inference_mode():
        out = pipe(
            prompt=prompt,
            num_inference_steps=int(steps),
            guidance_scale=6.5,
            height=int(size),
            width=int(size),
        )
    return out.images[0]

# ----------------- UI (mavi neon) -----------------
CSS = """
:root{--bg:#050b1a;--panel:#0a1636;--stroke:rgba(56,189,248,.25);--txt:#e6f1ff;--muted:#93c5fd;}
body,.gradio-container{background:radial-gradient(1200px 800px at 20% 0%, rgba(56,189,248,.18), transparent 55%),var(--bg)!important;color:var(--txt)!important;}
#wrap{max-width:1100px;margin:0 auto;}
#topbar{display:flex;align-items:center;gap:14px;padding:14px 16px;background:rgba(10,22,54,.75);border:1px solid var(--stroke);border-radius:16px;}
#card{margin-top:14px;padding:14px;background:rgba(10,22,54,.55);border:1px solid var(--stroke);border-radius:18px;}
button{border-radius:14px!important;}
textarea,input{background:rgba(5,11,26,.55)!important;border:1px solid rgba(56,189,248,.22)!important;color:var(--txt)!important;}
"""

with gr.Blocks(css=CSS, title="MaindAI") as demo:
    with gr.Column(elem_id="wrap"):
        with gr.Row(elem_id="topbar"):
            gr.Image("logo.png", show_label=False, height=58, width=58, container=False)
            gr.Markdown("## 💙 MAIND AI\n<small style='color:#93c5fd'>Chat + Görsel (HF Space CPU)</small>")

        with gr.Row(elem_id="card"):
            # SOL: Chat
            with gr.Column(scale=6):
                gr.Markdown("### 💬 Chat")
                chatbot = gr.Chatbot(value=[], height=420)
                msg = gr.Textbox(placeholder="Bir şey sor…", show_label=False)
                send = gr.Button("Gönder")
                send.click(chat_fn, [msg, chatbot], [chatbot, msg])
                msg.submit(chat_fn, [msg, chatbot], [chatbot, msg])

            # SAĞ: Image
            with gr.Column(scale=5):
                gr.Markdown("### 🎨 Görsel Üret")
                img_prompt = gr.Textbox(placeholder="Örn: neon mavi cyberpunk şehir, yağmur, gece", show_label=False)
                with gr.Row():
                    steps = gr.Slider(2, 12, value=6, step=1, label="Steps (hız)")
                    size = gr.Slider(256, 512, value=384, step=64, label="Boyut")
                img_btn = gr.Button("Görsel Oluştur")
                img_out = gr.Image(height=420)
                img_btn.click(gen_image, [img_prompt, steps, size], img_out)

demo.launch()