playgound with openai dependency 2

args_manager.py

@@ -37,6 +37,7 @@ args_parser.parser.add_argument("--always-download-new-model", action='store_tru
 args_parser.parser.set_defaults(
     disable_cuda_malloc=True,
     in_browser=True,
+    api_mode=False,
     port=None
 )
 

dummy_inference.py

@@ -0,0 +1,32 @@
+from openai import OpenAI
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+openai_key = os.getenv("OPENAI_KEY")
+
+if openai_key == "<YOUR_OPENAI_KEY>":
+    openai_key = ""
+
+if openai_key == "":
+    sys.exit("Please Provide Your OpenAI API Key")
+
+def infer_stable_diffusion(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
+    return "dummy_image"
+
+def infer_dall_e(text, model, quality, size):
+    try:
+        client = OpenAI(api_key=openai_key)
+
+        response = client.images.generate(
+            prompt=text,
+            model=model,
+            quality=quality,
+            size=size,
+            n=1,
+        )
+    except Exception as error:
+        print(str(error))
+        raise gr.Error("An error occurred while generating image.")
+
+    return response.data[0].url

inference.py

@@ -0,0 +1,65 @@
+import numpy as np
+import random
+from diffusers import DiffusionPipeline
+import torch
+from openai import OpenAI
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+openai_key = os.getenv("OPENAI_KEY")
+
+if openai_key == "<YOUR_OPENAI_KEY>":
+    openai_key = ""
+
+if openai_key == "":
+    sys.exit("Please Provide Your OpenAI API Key")
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+if torch.cuda.is_available():
+    torch.cuda.max_memory_allocated(device=device)
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    pipe.enable_xformers_memory_efficient_attention()
+    pipe = pipe.to(device)
+else: 
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
+    pipe = pipe.to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
+
+def infer_stable_diffusion(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+        
+    generator = torch.Generator().manual_seed(seed)
+    
+    image = pipe(
+        prompt = prompt, 
+        negative_prompt = negative_prompt,
+        guidance_scale = guidance_scale, 
+        num_inference_steps = num_inference_steps, 
+        width = width, 
+        height = height,
+        generator = generator
+    ).images[0] 
+    
+    return image
+
+def infer_dall_e(text, model, quality, size):
+    try:
+        client = OpenAI(api_key=openai_key)
+
+        response = client.images.generate(
+            prompt=text,
+            model=model,
+            quality=quality,
+            size=size,
+            n=1,
+        )
+    except Exception as error:
+        print(str(error))
+        raise gr.Error("An error occurred while generating image.")
+
+    return response.data[0].url

launch.py

@@ -27,6 +27,7 @@ TRY_INSTALL_XFORMERS = False
 
 
 def prepare_environment():
+
     torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu121")
     torch_command = os.environ.get('TORCH_COMMAND',
                                    f"pip install torch==2.1.0 torchvision==0.16.0 --extra-index-url {torch_index_url}")
@@ -71,10 +72,12 @@ def ini_args():
     from args_manager import args
     return args
 
-
-prepare_environment()
-build_launcher()
 args = ini_args()
+if not args.api_mode:
+    prepare_environment()
+    build_launcher()
+    args = ini_args()
+
 
 if args.gpu_device_id is not None:
    os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id)
@@ -128,9 +131,9 @@ def download_models(default_model, previous_default_models, checkpoint_downloads
 
     return default_model, checkpoint_downloads
 
-
-config.default_base_model_name, config.checkpoint_downloads = download_models(
-    config.default_base_model_name, config.previous_default_models, config.checkpoint_downloads,
-   config.embeddings_downloads, config.lora_downloads)
+if not args.api_mode:
+    config.default_base_model_name, config.checkpoint_downloads = download_models(
+        config.default_base_model_name, config.previous_default_models, config.checkpoint_downloads,
+    config.embeddings_downloads, config.lora_downloads)
 
 from webui import *

webui.py

@@ -16,6 +16,7 @@ import modules.meta_parser
 import args_manager
 import copy
 import launch
+import torch
 
 from modules.sdxl_styles import legal_style_names
 from modules.private_logger import get_current_html_path
@@ -23,6 +24,15 @@ from modules.ui_gradio_extensions import reload_javascript
 from modules.auth import auth_enabled, check_auth
 from modules.util import is_json
 
+def ini_args():
+    from args_manager import args
+    return args
+
+if ini_args().api_mode:
+    import dummy_inference as inf
+else:
+    import inference as inf
+
 def get_task(*args):
     args = list(args)
     args.pop(0)