Update app.py

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 from all_models import models
-from externalmod import gr_Interface_load, save_image, randomize_seed
+# from externalmod import gr_Interface_load, save_image, randomize_seed
 import asyncio
 import os
 from threading import RLock
@@ -11,7 +11,54 @@ negPreSetPrompt = "[deformed | disfigured], poorly drawn, [bad : wrong] anatomy,
 
 lock = RLock()
 
-HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary.
+HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
+
+num_models = 12
+max_images = 12
+inference_timeout = 400
+default_models = models[:num_models]
+MAX_SEED = 2**32-1
+
+load_fn(models)
+
+def gr_Interface_load(
+    name: str,
+    src: str | None = None,
+    hf_token: str | None = None,
+    alias: str | None = None,
+    **kwargs, # ignore
+) -> Blocks:
+    try:
+        return load_blocks_from_repo(name, src, hf_token, alias)
+    except Exception as e:
+        print(e)
+        return gradio.Interface(lambda: None, ['text'], ['image'])
+
+
+def save_image(image, savefile, modelname, prompt, nprompt, height=0, width=0, steps=0, cfg=0, seed=-1):
+    from PIL import Image, PngImagePlugin
+    import json
+    try:
+        metadata = {"prompt": prompt, "negative_prompt": nprompt, "Model": {"Model": modelname.split("/")[-1]}}
+        if steps > 0: metadata["num_inference_steps"] = steps
+        if cfg > 0: metadata["guidance_scale"] = cfg
+        if seed != -1: metadata["seed"] = seed
+        if width > 0 and height > 0: metadata["resolution"] = f"{width} x {height}"
+        metadata_str = json.dumps(metadata)
+        info = PngImagePlugin.PngInfo()
+        info.add_text("metadata", metadata_str)
+        image.save(savefile, "PNG", pnginfo=info)
+        return str(Path(savefile).resolve())
+    except Exception as e:
+        print(f"Failed to save image file: {e}")
+        raise Exception(f"Failed to save image file:") from e
+
+def randomize_seed():
+    from random import seed, randint
+    MAX_SEED = 2**32-1
+    seed()
+    rseed = randint(0, MAX_SEED)
+    return rseed
 
 def get_current_time():
     now = datetime.now()
@@ -31,31 +78,18 @@ def load_fn(models):
                 m = gr.Interface(lambda: None, ['text'], ['image'])
             models_load.update({model: m})
 
-
-load_fn(models)
-
-num_models = 12
-max_images = 12
-inference_timeout = 400
-default_models = models[:num_models]
-MAX_SEED = 2**32-1
-
-
 def extend_choices(choices):
     return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA']
 
-
 def update_imgbox(choices):
     choices_plus = extend_choices(choices[:num_models])
     return [gr.Image(None, label=m, visible=(m!='NA')) for m in choices_plus]
 
-
 def random_choices():
     import random
     random.seed()
     return random.choices(models, k=num_models)
 
-
 async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout):
     kwargs = {}
     if height > 0: kwargs["height"] = height
@@ -105,7 +139,6 @@ def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, see
         loop.close()
     return result
 
-
 def add_gallery(image, model_str, gallery):
     if gallery is None: gallery = []
     with lock: