Update app.py

app.py

@@ -1,8 +1,14 @@
+import os
 import torch
 from PIL import Image
 from transformers import Blip2Processor, Blip2ForConditionalGeneration
 import gradio as gr
 
+# ---------------------------------------------------------
+# ENV FIX (OPSİYONEL AMA TEMİZ)
+# ---------------------------------------------------------
+os.environ["OMP_NUM_THREADS"] = "1"
+
 # ---------------------------------------------------------
 # DEVICE
 # ---------------------------------------------------------
@@ -15,10 +21,16 @@ print(f"🚀 Device: {device} | dtype: {dtype}")
 # MODEL
 # ---------------------------------------------------------
 MODEL_NAME = "Salesforce/blip2-flan-t5-xl"
+# Space çok çöküyorsa şuna düş:
+# MODEL_NAME = "Salesforce/blip2-flan-t5-base"
 
 print("⏳ Model yükleniyor...")
 
-processor = Blip2Processor.from_pretrained(MODEL_NAME)
+processor = Blip2Processor.from_pretrained(
+    MODEL_NAME,
+    use_fast=True
+)
+
 model = Blip2ForConditionalGeneration.from_pretrained(
     MODEL_NAME,
     torch_dtype=dtype,
@@ -55,14 +67,19 @@ def generate_caption(image: Image.Image):
     return caption
 
 # ---------------------------------------------------------
-# GRADIO UI
+# GRADIO UI + API
 # ---------------------------------------------------------
 demo = gr.Interface(
     fn=generate_caption,
     inputs=gr.Image(type="pil", label="📷 Görsel Yükle"),
     outputs=gr.Textbox(label="📝 Üretilen Açıklama"),
+    api_name="generate_caption",  # 🔴 API İSMİ
     title="BLIP-2 Image Captioning",
-    description="BLIP-2 FLAN-T5-XL ile fotoğraftan metin üretme (GPU)"
+    description="BLIP-2 FLAN-T5 ile Image → Text"
 )
 
-demo.launch()
+demo.launch(
+    server_name="0.0.0.0",
+    server_port=7860,
+    show_error=True
+)