Create yml/generate-midjourney.py

yml/generate-midjourney.py

@@ -0,0 +1,52 @@
+import os, sys, random, requests
+from gradio_client import Client
+
+raw_prompt = os.environ.get('PROMPT', '')
+# اضافه کردن کلمه کلیدی میدجرنی
+final_prompt = f'MJ v6 {raw_prompt}'
+
+width = int(os.environ.get('WIDTH', 1024))
+height = int(os.environ.get('HEIGHT', 1024))
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+print('1. Connecting to LoRA DLC Space...')
+try:
+    client = Client('opera8/FLUX-LoRA-DLC')
+    
+    print('2. Loading Midjourney Model...')
+    # لود کردن مدل میدجرنی
+    client.predict('strangerzonehf/Flux-Midjourney-Mix2-LoRA', api_name='/add_custom_lora')
+    
+    print(f'3. Generating Image... Prompt: {final_prompt[:50]}...')
+    result = client.predict(
+        prompt=final_prompt,
+        image_input=None,
+        cfg_scale=3.5,
+        steps=28,
+        randomize_seed=True,
+        seed=random.randint(1, 2147483647),
+        width=width,
+        height=height,
+        lora_scale=0.8,
+        api_name='/run_lora'
+    )
+    
+    image_path = result[0] if isinstance(result, (tuple, list)) else result
+    
+    print('4. Uploading back to Docker Space...')
+    with open(image_path, 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload', 
+                         data={'run_id': run_id, 'github_run_id': github_run_id}, 
+                         files={'file': f})
+    
+    if res.status_code == 200:
+        print('5. SUCCESS!')
+    else:
+        print(f'Upload Error: {res.text}')
+        sys.exit(1)
+        
+except Exception as e:
+    print(f'CRITICAL ERROR: {e}')
+    sys.exit(1)