Upload 2 files

app.py

@@ -47,7 +47,7 @@ css = """
 with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as demo:
     with gr.Column(): 
         with gr.Accordion("Advanced settings", open=False):
-            with gr.Accordion("Recommended Prompt", open=False):
+            with gr.Accordion("Recommended Prompt", open=True):
                 recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
                 with gr.Row():
                     positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
@@ -63,9 +63,9 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as demo:
                 v2_tag_type = gr.Radio(label="Tag Type", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru", visible=False)
                 v2_model = gr.Dropdown(label="Model", choices=list(V2_ALL_MODELS.keys()), value=list(V2_ALL_MODELS.keys())[0])
                 v2_copy = gr.Button(value="Copy to clipboard", size="sm", interactive=False)
-            with gr.Accordion("Model", open=True):
-                model_name = gr.Dropdown(label="Select Model", show_label=False, choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
-                model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_id="model_info")
+        with gr.Accordion("Model", open=True):
+            model_name = gr.Dropdown(label="Select Model", show_label=False, choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
+            model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_id="model_info")
         with gr.Group():
             with gr.Accordion("Prompt from Image File", open=False):
                 tagger_image = gr.Image(label="Input image", type="pil", sources=["upload", "clipboard"], height=256)
@@ -118,9 +118,11 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as demo:
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[results],
         queue=True,
+        trigger_mode="multiple",
+        concurrency_limit=5,
         show_progress="full",
         show_api=True,
-    ).success(save_gallery_images, [results], [results, image_files], queue=False, show_api=False)
+    ).then(save_gallery_images, [results], [results, image_files], queue=False, show_api=False)
     gr.on(
         triggers=[random_button.click],
         fn=infer_multi_random,
@@ -128,9 +130,11 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as demo:
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[results],
         queue=True,
+        trigger_mode="multiple",
+        concurrency_limit=5,
         show_progress="full",
         show_api=True,
-    ).success(save_gallery_images, [results], [results, image_files], queue=False, show_api=False)
+    ).then(save_gallery_images, [results], [results, image_files], queue=False, show_api=False)
     clear_prompt.click(lambda: (None, None, None), None, [prompt, v2_series, v2_character], queue=False, show_api=False)
     clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
     recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],

multit2i.py

@@ -1,6 +1,5 @@
 import gradio as gr
 import asyncio
-import queue
 from threading import RLock
 from pathlib import Path
 
@@ -108,6 +107,8 @@ def save_gallery_images(images, progress=gr.Progress(track_tqdm=True)):
     return gr.update(value=output_images), gr.update(value=output_paths)
 
 
+# https://github.com/gradio-app/gradio/blob/main/gradio/external.py
+# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
 def load_from_model(model_name: str, hf_token: str = None):
     import httpx
     import huggingface_hub
@@ -167,6 +168,7 @@ async def async_load_models(models: list, limit: int=5):
     async def async_load_model(model: str):
         async with sem:
            try:
+               await asyncio.sleep(0.5)
                return await asyncio.to_thread(load_model, model)
            except Exception as e:
                print(e)
@@ -307,7 +309,7 @@ def infer(prompt: str, neg_prompt: str, model_name: str):
     try:
         model = load_model(model_name)
         if not model: return (Image.Image(), None)
-        image_path = model(prompt + seed)
+        image_path = model(prompt + seed, neg_prompt)
         image = Image.open(image_path).convert('RGBA')
     except Exception as e:
         print(e)
@@ -317,35 +319,49 @@ def infer(prompt: str, neg_prompt: str, model_name: str):
 
 async def infer_multi(prompt: str, neg_prompt: str, results: list, image_num: float, model_name: str,
                  pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], progress=gr.Progress(track_tqdm=True)):
-    from tqdm.asyncio import tqdm_asyncio
+    import asyncio
+    progress(0, desc="Start inference.")
     image_num = int(image_num)
     images = results if results else []
+    image_num_offset = len(images)
     prompt, neg_prompt = recom_prompt(prompt, neg_prompt, pos_pre, pos_suf, neg_pre, neg_suf)
     tasks = [asyncio.to_thread(infer, prompt, neg_prompt, model_name) for i in range(image_num)]
-    #results = await asyncio.gather(*tasks, return_exceptions=True)
-    results = await tqdm_asyncio.gather(*tasks)
-    if not results: results = []
-    for result in results:
+    for task in tasks:
+        progress(float(len(images) - image_num_offset) / float(image_num), desc="Running inference.")
+        try:
+            result = await task
+        except Exception as e:
+            print(e)
+            task.cancel()
+            result = None
+            image_num_offset += 1
         with lock:
-            if result and result[1]: images.append(result)
+            if result and len(result) == 2 and result[1]: images.append(result)
+        await asyncio.sleep(0.05)
         yield images
 
 
 async def infer_multi_random(prompt: str, neg_prompt: str, results: list, image_num: float, 
                  pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], progress=gr.Progress(track_tqdm=True)):
-    from tqdm.asyncio import tqdm_asyncio
     import random
+    progress(0, desc="Start inference.")
     image_num = int(image_num)
     images = results if results else []
+    image_num_offset = len(images)
     random.seed()
     model_names = random.choices(list(loaded_models.keys()), k = image_num)
     prompt, neg_prompt = recom_prompt(prompt, neg_prompt, pos_pre, pos_suf, neg_pre, neg_suf)
     tasks = [asyncio.to_thread(infer, prompt, neg_prompt, model_name) for model_name in model_names]
-    #results = await asyncio.gather(*tasks, return_exceptions=True)
-    results = await tqdm_asyncio.gather(*tasks)
-    if not results: results = []
-    for result in results:
+    for task in tasks:
+        progress(float(len(images) - image_num_offset) / float(image_num), desc="Running inference.")
+        try:
+            result = await task
+        except Exception as e:
+            print(e)
+            task.cancel()
+            result = None
+            image_num_offset += 1
         with lock:
-            if result and result[1]: images.append(result)
+            if result and len(result) == 2 and result[1]: images.append(result)
+        await asyncio.sleep(0.05)
         yield images
-