Update app.py

app.py

@@ -1,7 +1,6 @@
 from fastapi import FastAPI
 from fastapi.responses import PlainTextResponse, FileResponse
-from pydantic import BaseModel
-from diffusers import StableDiffusionPipeline
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 import torch
 import uvicorn
 import threading
@@ -11,56 +10,62 @@ import os
 
 app = FastAPI()
 
-# 🔥 MODEL (small Stable Diffusion)
+# 🔥 CPU оптимизация
+torch.set_num_threads(2)
+
+# 🔥 MODEL
 model_name = "segmind/small-sd"
 
 pipe = StableDiffusionPipeline.from_pretrained(
     model_name,
-    torch_dtype=torch.float16
+    torch_dtype=torch.float32
 )
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = pipe.to(device)
+pipe = pipe.to("cpu")
+
+# 🔥 быстрый scheduler
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
 
-# 🔥 оптимизации
+# 🔥 CPU ускорения
 pipe.enable_attention_slicing()
+pipe.enable_sequential_cpu_offload()
 
-# если доступно
+# 🔥 доп. ускорение
 try:
-    pipe.enable_xformers_memory_efficient_attention()
+    pipe.unet.to(memory_format=torch.channels_last)
 except:
     pass
 
-
 MAX_HISTORY = 40
-NUM_WORKERS = 2  # меньше воркеров для GPU
+NUM_WORKERS = 1  # важно для CPU
 
 db = OrderedDict()
 queue = []
 
-# папка для изображений
 IMG_DIR = "images"
 os.makedirs(IMG_DIR, exist_ok=True)
 
 
-class Message(BaseModel):
-    message: str
-
-
-# 🔥 генерация изображения
+# 🔥 генерация изображения (максимально облегчённая)
 def generate_ai_stream(message: str):
 
     try:
+        start = time.time()
+
         image = pipe(
             message,
-            num_inference_steps=15,
-            guidance_scale=7.5
+            num_inference_steps=4,   # 🔥 минимум
+            guidance_scale=5.0,
+            height=256,
+            width=256
         ).images[0]
 
         filename = f"{IMG_DIR}/img_{int(time.time()*1000)}.png"
         image.save(filename)
 
-        result = filename
+        duration = round(time.time() - start, 2)
+
+        result = f"{filename} | {duration}s"
 
     except Exception as e:
         result = f"error: {str(e)}"
@@ -86,14 +91,13 @@ def worker():
             time.sleep(0.05)
 
 
-# 🔥 запуск воркеров
-for _ in range(NUM_WORKERS):
-    threading.Thread(target=worker, daemon=True).start()
+# 🔥 запуск воркера
+threading.Thread(target=worker, daemon=True).start()
 
 
 @app.get("/")
 async def root():
-    return PlainTextResponse("🎨 Image AI server running (small Stable Diffusion)")
+    return PlainTextResponse("🎨 SD CPU optimized server running")
 
 
 @app.get("/ask")
@@ -129,7 +133,6 @@ async def get(message: str):
     return PlainTextResponse(data["reply"])
 
 
-# 🔥 отдача изображения
 @app.get("/image")
 async def get_image(path: str):
     if not os.path.exists(path):