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README.md

@@ -4,7 +4,7 @@ emoji: 🏆😻
 colorFrom: red
 colorTo: pink
 sdk: gradio
-sdk_version: 4.41.0
+sdk_version: 4.44.1
 app_file: app.py
 pinned: true
 license: mit

app.py

@@ -7,13 +7,17 @@ from live_preview_helpers import flux_pipe_call_that_returns_an_iterable_of_imag
 from diffusers.utils import load_image
 from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel, FluxControlNetImg2ImgPipeline
 from huggingface_hub import HfFileSystem, ModelCard
+import os
+import copy
 import random
 import time
+import requests
+import pandas as pd
 
 from env import models, num_loras, num_cns
 from mod import (clear_cache, get_repo_safetensors, is_repo_name, is_repo_exists, get_model_trigger,
                  description_ui, compose_lora_json, is_valid_lora, fuse_loras, save_image, preprocess_i2i_image,
-                 get_trigger_word, enhance_prompt, deselect_lora, set_control_union_image,
+                 get_trigger_word, enhance_prompt, set_control_union_image,
                  get_control_union_mode, set_control_union_mode, get_control_params, translate_to_en)
 from flux import (search_civitai_lora, select_civitai_lora, search_civitai_lora_json,
                   download_my_lora, get_all_lora_tupled_list, apply_lora_prompt,
@@ -21,6 +25,10 @@ from flux import (search_civitai_lora, select_civitai_lora, search_civitai_lora_
 from tagger.tagger import predict_tags_wd, compose_prompt_to_copy
 from tagger.fl2flux import predict_tags_fl2_flux
 
+#Load prompts for randomization
+df = pd.read_csv('prompts.csv', header=None)
+prompt_values = df.values.flatten()
+
 # Load LoRAs from JSON file
 with open('loras.json', 'r') as f:
     loras = json.load(f)
@@ -99,7 +107,7 @@ class calculateDuration:
     def __enter__(self):
         self.start_time = time.time()
         return self
-    
+
     def __exit__(self, exc_type, exc_value, traceback):
         self.end_time = time.time()
         self.elapsed_time = self.end_time - self.start_time
@@ -108,32 +116,217 @@ class calculateDuration:
         else:
             print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
 
-def update_selection(evt: gr.SelectData, width, height):
-    selected_lora = loras[evt.index]
-    new_placeholder = f"Type a prompt for {selected_lora['title']}"
-    lora_repo = selected_lora["repo"]
-    updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✨"
-    if "aspect" in selected_lora:
-        if selected_lora["aspect"] == "portrait":
-            width = 768
-            height = 1024
-        elif selected_lora["aspect"] == "landscape":
-            width = 1024
-            height = 768
+def download_file(url, directory=None):
+    if directory is None:
+        directory = os.getcwd()  # Use current working directory if not specified
+    
+    # Get the filename from the URL
+    filename = url.split('/')[-1]
+    
+    # Full path for the downloaded file
+    filepath = os.path.join(directory, filename)
+    
+    # Download the file
+    response = requests.get(url)
+    response.raise_for_status()  # Raise an exception for bad status codes
+    
+    # Write the content to the file
+    with open(filepath, 'wb') as file:
+        file.write(response.content)
+    
+    return filepath
+            
+def update_selection(evt: gr.SelectData, selected_indices, loras_state, width, height):
+    selected_index = evt.index
+    selected_indices = selected_indices or []
+    if selected_index in selected_indices:
+        selected_indices.remove(selected_index)
+    else:
+        if len(selected_indices) < 2:
+            selected_indices.append(selected_index)
         else:
-            width = 1024
-            height = 1024
+            gr.Warning("You can select up to 2 LoRAs, remove one to select a new one.")
+            return gr.update(), gr.update(), gr.update(), selected_indices, gr.update(), gr.update(), width, height, gr.update(), gr.update()
+
+    selected_info_1 = "Select a LoRA 1"
+    selected_info_2 = "Select a LoRA 2"
+    lora_scale_1 = 1.15
+    lora_scale_2 = 1.15
+    lora_image_1 = None
+    lora_image_2 = None
+    if len(selected_indices) >= 1:
+        lora1 = loras_state[selected_indices[0]]
+        selected_info_1 = f"### LoRA 1 Selected: [{lora1['title']}](https://huggingface.co/{lora1['repo']}) ✨"
+        lora_image_1 = lora1['image']
+    if len(selected_indices) >= 2:
+        lora2 = loras_state[selected_indices[1]]
+        selected_info_2 = f"### LoRA 2 Selected: [{lora2['title']}](https://huggingface.co/{lora2['repo']}) ✨"
+        lora_image_2 = lora2['image']
+
+    if selected_indices:
+        last_selected_lora = loras_state[selected_indices[-1]]
+        new_placeholder = f"Type a prompt for {last_selected_lora['title']}"
+    else:
+        new_placeholder = "Type a prompt"
+
+    return gr.update(placeholder=new_placeholder), selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, width, height, lora_image_1, lora_image_2
+
+def remove_lora_1(selected_indices, loras_state):
+    if len(selected_indices) >= 1:
+        selected_indices.pop(0)
+    selected_info_1 = "Select a LoRA 1"
+    selected_info_2 = "Select a LoRA 2"
+    lora_scale_1 = 1.15
+    lora_scale_2 = 1.15
+    lora_image_1 = None
+    lora_image_2 = None
+    if len(selected_indices) >= 1:
+        lora1 = loras_state[selected_indices[0]]
+        selected_info_1 = f"### LoRA 1 Selected: [{lora1['title']}]({lora1['repo']}) ✨"
+        lora_image_1 = lora1['image']
+    if len(selected_indices) >= 2:
+        lora2 = loras_state[selected_indices[1]]
+        selected_info_2 = f"### LoRA 2 Selected: [{lora2['title']}]({lora2['repo']}) ✨"
+        lora_image_2 = lora2['image']
+    return selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2
+
+def remove_lora_2(selected_indices, loras_state):
+    if len(selected_indices) >= 2:
+        selected_indices.pop(1)
+    selected_info_1 = "Select a LoRA 1"
+    selected_info_2 = "Select a LoRA 2"
+    lora_scale_1 = 1.15
+    lora_scale_2 = 1.15
+    lora_image_1 = None
+    lora_image_2 = None
+    if len(selected_indices) >= 1:
+        lora1 = loras_state[selected_indices[0]]
+        selected_info_1 = f"### LoRA 1 Selected: [{lora1['title']}]({lora1['repo']}) ✨"
+        lora_image_1 = lora1['image']
+    if len(selected_indices) >= 2:
+        lora2 = loras_state[selected_indices[1]]
+        selected_info_2 = f"### LoRA 2 Selected: [{lora2['title']}]({lora2['repo']}) ✨"
+        lora_image_2 = lora2['image']
+    return selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2
+
+def randomize_loras(selected_indices, loras_state):
+    if len(loras_state) < 2:
+        raise gr.Error("Not enough LoRAs to randomize.")
+    selected_indices = random.sample(range(len(loras_state)), 2)
+    lora1 = loras_state[selected_indices[0]]
+    lora2 = loras_state[selected_indices[1]]
+    selected_info_1 = f"### LoRA 1 Selected: [{lora1['title']}](https://huggingface.co/{lora1['repo']}) ✨"
+    selected_info_2 = f"### LoRA 2 Selected: [{lora2['title']}](https://huggingface.co/{lora2['repo']}) ✨"
+    lora_scale_1 = 1.15
+    lora_scale_2 = 1.15
+    lora_image_1 = lora1['image']
+    lora_image_2 = lora2['image']
+    random_prompt = random.choice(prompt_values)
+    return selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2, random_prompt
+
+def add_custom_lora(custom_lora, selected_indices, current_loras):
+    if custom_lora:
+        try:
+            title, repo, path, trigger_word, image = check_custom_model(custom_lora)
+            print(f"Loaded custom LoRA: {repo}")
+            existing_item_index = next((index for (index, item) in enumerate(current_loras) if item['repo'] == repo), None)
+            if existing_item_index is None:
+                if repo.endswith(".safetensors") and repo.startswith("http"):
+                    repo = download_file(repo)
+                new_item = {
+                    "image": image if image else "/home/user/app/custom.png",
+                    "title": title,
+                    "repo": repo,
+                    "weights": path,
+                    "trigger_word": trigger_word
+                }
+                print(f"New LoRA: {new_item}")
+                existing_item_index = len(current_loras)
+                current_loras.append(new_item)
+            
+            # Update gallery
+            gallery_items = [(item["image"], item["title"]) for item in current_loras]
+            # Update selected_indices if there's room
+            if len(selected_indices) < 2:
+                selected_indices.append(existing_item_index)
+            else:
+                gr.Warning("You can select up to 2 LoRAs, remove one to select a new one.")
+
+            # Update selected_info and images
+            selected_info_1 = "Select a LoRA 1"
+            selected_info_2 = "Select a LoRA 2"
+            lora_scale_1 = 1.15
+            lora_scale_2 = 1.15
+            lora_image_1 = None
+            lora_image_2 = None
+            if len(selected_indices) >= 1:
+                lora1 = current_loras[selected_indices[0]]
+                selected_info_1 = f"### LoRA 1 Selected: {lora1['title']} ✨"
+                lora_image_1 = lora1['image'] if lora1['image'] else None
+            if len(selected_indices) >= 2:
+                lora2 = current_loras[selected_indices[1]]
+                selected_info_2 = f"### LoRA 2 Selected: {lora2['title']} ✨"
+                lora_image_2 = lora2['image'] if lora2['image'] else None
+            print("Finished adding custom LoRA")
+            return (
+                current_loras,
+                gr.update(value=gallery_items),
+                selected_info_1, 
+                selected_info_2,
+                selected_indices,
+                lora_scale_1,
+                lora_scale_2,
+                lora_image_1,
+                lora_image_2
+            )
+        except Exception as e:
+            print(e)
+            gr.Warning(str(e))
+            return current_loras, gr.update(), gr.update(), gr.update(), selected_indices, gr.update(), gr.update(), gr.update(), gr.update()
+    else:
+        return current_loras, gr.update(), gr.update(), gr.update(), selected_indices, gr.update(), gr.update(), gr.update(), gr.update()
+
+def remove_custom_lora(selected_indices, current_loras):
+    if current_loras:
+        custom_lora_repo = current_loras[-1]['repo']
+        # Remove from loras list
+        current_loras = current_loras[:-1]
+        # Remove from selected_indices if selected
+        custom_lora_index = len(current_loras)
+        if custom_lora_index in selected_indices:
+            selected_indices.remove(custom_lora_index)
+    # Update gallery
+    gallery_items = [(item["image"], item["title"]) for item in current_loras]
+    # Update selected_info and images
+    selected_info_1 = "Select a LoRA 1"
+    selected_info_2 = "Select a LoRA 2"
+    lora_scale_1 = 1.15
+    lora_scale_2 = 1.15
+    lora_image_1 = None
+    lora_image_2 = None
+    if len(selected_indices) >= 1:
+        lora1 = current_loras[selected_indices[0]]
+        selected_info_1 = f"### LoRA 1 Selected: [{lora1['title']}]({lora1['repo']}) ✨"
+        lora_image_1 = lora1['image']
+    if len(selected_indices) >= 2:
+        lora2 = current_loras[selected_indices[1]]
+        selected_info_2 = f"### LoRA 2 Selected: [{lora2['title']}]({lora2['repo']}) ✨"
+        lora_image_2 = lora2['image']
     return (
-        gr.update(placeholder=new_placeholder),
-        updated_text,
-        evt.index,
-        width,
-        height,
+        current_loras,
+        gr.update(value=gallery_items),
+        selected_info_1,
+        selected_info_2,
+        selected_indices,
+        lora_scale_1,
+        lora_scale_2,
+        lora_image_1,
+        lora_image_2
     )
 
 @spaces.GPU(duration=70)
 @torch.inference_mode()
-def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, cn_on, progress=gr.Progress(track_tqdm=True)):
+def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, cn_on, progress=gr.Progress(track_tqdm=True)):
     global pipe, taef1, good_vae, controlnet, controlnet_union
     try:
         good_vae.to("cuda")
@@ -155,7 +348,7 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
                     width=width,
                     height=height,
                     generator=generator,
-                    joint_attention_kwargs={"scale": lora_scale},
+                    joint_attention_kwargs={"scale": 1.0},
                     output_type="pil",
                     good_vae=good_vae,
                 ):
@@ -177,7 +370,7 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
                     height=height,
                     controlnet_conditioning_scale=scales,
                     generator=generator,
-                    joint_attention_kwargs={"scale": lora_scale},
+                    joint_attention_kwargs={"scale": 1.0},
                 ).images:
                     yield img
     except Exception as e:
@@ -186,7 +379,7 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
 
 @spaces.GPU(duration=70)
 @torch.inference_mode()
-def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, lora_scale, seed, cn_on, progress=gr.Progress(track_tqdm=True)):
+def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, seed, cn_on, progress=gr.Progress(track_tqdm=True)):
     global pipe_i2i, good_vae, controlnet, controlnet_union
     try:
         good_vae.to("cuda")
@@ -210,7 +403,7 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
                     width=width,
                     height=height,
                     generator=generator,
-                    joint_attention_kwargs={"scale": lora_scale},
+                    joint_attention_kwargs={"scale": 1.0},
                     output_type="pil",
                 ).images[0]
                 return final_image 
@@ -234,7 +427,7 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
                     height=height,
                     controlnet_conditioning_scale=scales,
                     generator=generator,
-                    joint_attention_kwargs={"scale": lora_scale},
+                    joint_attention_kwargs={"scale": 1.0},
                     output_type="pil",
                 ).images[0]
                 return final_image
@@ -242,73 +435,99 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
         print(e)
         raise gr.Error(f"I2I Inference Error: {e}") from e
 
-def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height,
-              lora_scale, lora_json, cn_on, translate_on, progress=gr.Progress(track_tqdm=True)):
-    global pipe
-    if selected_index is None and not is_valid_lora(lora_json):
+def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2,
+             randomize_seed, seed, width, height, loras_state,
+             lora_json, cn_on, translate_on, progress=gr.Progress(track_tqdm=True)):
+    global pipe, pipe_i2i
+    if not selected_indices and not is_valid_lora(lora_json):
         gr.Info("LoRA isn't selected.")
     #    raise gr.Error("You must select a LoRA before proceeding.")
     progress(0, desc="Preparing Inference.")
 
+    selected_loras = [loras_state[idx] for idx in selected_indices]
+
+    if translate_on: prompt = translate_to_en(prompt)
+
+    # Build the prompt with trigger words
+    prepends = []
+    appends = []
+    for lora in selected_loras:
+        trigger_word = lora.get('trigger_word', '')
+        if trigger_word:
+            if lora.get("trigger_position") == "prepend":
+                prepends.append(trigger_word)
+            else:
+                appends.append(trigger_word)
+    prompt_mash = " ".join(prepends + [prompt] + appends)
+    print("Prompt Mash: ", prompt_mash) #
+
+    # Unload previous LoRA weights
     with calculateDuration("Unloading LoRA"):
         try:
-            pipe.unfuse_lora()
+            #pipe.unfuse_lora()
             pipe.unload_lora_weights()
-            pipe_i2i.unfuse_lora()
+            #pipe_i2i.unfuse_lora()
             pipe_i2i.unload_lora_weights()
         except Exception as e:
             print(e)
-    
-    clear_cache() #
 
-    if translate_on: prompt = translate_to_en(prompt)
+    print(pipe.get_active_adapters()) #
+    print(pipe_i2i.get_active_adapters()) #
+
+    clear_cache() #
 
-    prompt_mash = prompt + get_model_trigger(last_model)
-    if is_valid_lora(lora_json):
-        # Load External LoRA weights
+    # Build the prompt for External LoRAs
+    prompt_mash = prompt_mash + get_model_trigger(last_model)
+    lora_names = []
+    lora_weights = []
+    if is_valid_lora(lora_json): # Load External LoRA weights
         with calculateDuration("Loading External LoRA weights"):
-            fuse_loras(pipe, lora_json)
-            fuse_loras(pipe_i2i, lora_json)
+            if image_input is not None: lora_names, lora_weights = fuse_loras(pipe_i2i, lora_json)
+            else: lora_names, lora_weights = fuse_loras(pipe, lora_json)
             trigger_word = get_trigger_word(lora_json)
-            prompt_mash = f"{prompt} {trigger_word}"
-    if selected_index is not None:
-        selected_lora = loras[selected_index]
-        lora_path = selected_lora["repo"]
-        trigger_word = selected_lora["trigger_word"]
-        if(trigger_word):
-            if "trigger_position" in selected_lora:
-                if selected_lora["trigger_position"] == "prepend":
-                    prompt_mash = f"{trigger_word} {prompt_mash}"
-                else:
-                    prompt_mash = f"{prompt_mash} {trigger_word}"
-            else:
-                prompt_mash = f"{trigger_word} {prompt_mash}"
-        else:
-            prompt_mash = prompt_mash
-        # Load LoRA weights
-        with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
-            if(image_input is not None):
-                if "weights" in selected_lora:
-                    pipe_i2i.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
+            prompt_mash = f"{prompt_mash} {trigger_word}"
+    print("Prompt Mash: ", prompt_mash) #
+
+    # Load LoRA weights with respective scales
+    with calculateDuration("Loading LoRA weights"):
+        for idx, lora in enumerate(selected_loras):
+            lora_name = f"lora_{idx}"
+            lora_names.append(lora_name)
+            lora_weights.append(lora_scale_1 if idx == 0 else lora_scale_2)
+            lora_path = lora['repo']
+            weight_name = lora.get("weights")
+            print(f"Lora Path: {lora_path}")
+            if image_input is not None:
+                if weight_name:
+                    pipe_i2i.load_lora_weights(lora_path, weight_name=weight_name, low_cpu_mem_usage=True, adapter_name=lora_name)
                 else:
-                    pipe_i2i.load_lora_weights(lora_path)
+                    pipe_i2i.load_lora_weights(lora_path, low_cpu_mem_usage=True, adapter_name=lora_name)
             else:
-                if "weights" in selected_lora:
-                    pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
+                if weight_name:
+                    pipe.load_lora_weights(lora_path, weight_name=weight_name, low_cpu_mem_usage=True, adapter_name=lora_name)
                 else:
-                    pipe.load_lora_weights(lora_path)
-        
+                    pipe.load_lora_weights(lora_path, low_cpu_mem_usage=True, adapter_name=lora_name)
+        print("Loaded LoRAs:", lora_names)
+        if image_input is not None:
+            pipe_i2i.set_adapters(lora_names, adapter_weights=lora_weights)
+        else:
+            pipe.set_adapters(lora_names, adapter_weights=lora_weights)
+
+    print(pipe.get_active_adapters()) #
+    print(pipe_i2i.get_active_adapters()) #
+
     # Set random seed for reproducibility
     with calculateDuration("Randomizing seed"):
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
     
+    # Generate image
     progress(0, desc="Running Inference.")
     if(image_input is not None):
-        final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, lora_scale, seed, cn_on, progress)
+        final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, seed, cn_on)
         yield save_image(final_image, None, last_model, prompt_mash, height, width, steps, cfg_scale, seed), seed, gr.update(visible=False)
     else:
-        image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, cn_on, progress)
+        image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, cn_on)
         # Consume the generator to get the final image
         final_image = None
         step_counter = 0
@@ -319,90 +538,65 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
             yield image, seed, gr.update(value=progress_bar, visible=True)
         yield save_image(final_image, None, last_model, prompt_mash, height, width, steps, cfg_scale, seed), seed, gr.update(value=progress_bar, visible=False)
 
+run_lora.zerogpu = True
+
 def get_huggingface_safetensors(link):
-  split_link = link.split("/")
-  if(len(split_link) == 2):
-            model_card = ModelCard.load(link)
-            base_model = model_card.data.get("base_model")
-            print(base_model)
-            if((base_model != "black-forest-labs/FLUX.1-dev") and (base_model != "black-forest-labs/FLUX.1-schnell")):
-                raise Exception("Not a FLUX LoRA!")
-            image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
-            trigger_word = model_card.data.get("instance_prompt", "")
-            image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None
-            fs = HfFileSystem()
-            try:
-                list_of_files = fs.ls(link, detail=False)
-                for file in list_of_files:
-                    if(file.endswith(".safetensors")):
-                        safetensors_name = file.split("/")[-1]
-                    if (not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp"))):
-                      image_elements = file.split("/")
-                      image_url = f"https://huggingface.co/{link}/resolve/main/{image_elements[-1]}"
-            except Exception as e:
-              print(e)
-              gr.Warning(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA")
-              raise Exception(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA")
-            return split_link[1], link, safetensors_name, trigger_word, image_url
+    split_link = link.split("/")
+    if len(split_link) == 2:
+        model_card = ModelCard.load(link)
+        base_model = model_card.data.get("base_model")
+        print(f"Base model: {base_model}")
+        if base_model not in ["black-forest-labs/FLUX.1-dev", "black-forest-labs/FLUX.1-schnell"]:
+            raise Exception("Not a FLUX LoRA!")
+        image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
+        trigger_word = model_card.data.get("instance_prompt", "")
+        image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None
+        fs = HfFileSystem()
+        safetensors_name = None
+        try:
+            list_of_files = fs.ls(link, detail=False)
+            for file in list_of_files:
+                if file.endswith(".safetensors"):
+                    safetensors_name = file.split("/")[-1]
+                if not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp")):
+                    image_elements = file.split("/")
+                    image_url = f"https://huggingface.co/{link}/resolve/main/{image_elements[-1]}"
+        except Exception as e:
+            print(e)
+            raise gr.Error("Invalid Hugging Face repository with a *.safetensors LoRA")
+        if not safetensors_name:
+            raise gr.Error("No *.safetensors file found in the repository")
+        return split_link[1], link, safetensors_name, trigger_word, image_url
+    else:
+        raise gr.Error("Invalid Hugging Face repository link")
 
 def check_custom_model(link):
-    if(link.startswith("https://")):
-        if(link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co")):
+    if link.endswith(".safetensors"):
+        # Treat as direct link to the LoRA weights
+        title = os.path.basename(link)
+        repo = link
+        path = None  # No specific weight name
+        trigger_word = ""
+        image_url = None
+        return title, repo, path, trigger_word, image_url
+    elif link.startswith("https://"):
+        if "huggingface.co" in link:
             link_split = link.split("huggingface.co/")
             return get_huggingface_safetensors(link_split[1])
-    else: 
-        return get_huggingface_safetensors(link)
-
-def add_custom_lora(custom_lora):
-    global loras
-    if(custom_lora):
-        try:
-            title, repo, path, trigger_word, image = check_custom_model(custom_lora)
-            print(f"Loaded custom LoRA: {repo}")
-            card = f'''
-            <div class="custom_lora_card">
-              <span>Loaded custom LoRA:</span>
-              <div class="card_internal">
-                <img src="{image}" />
-                <div>
-                    <h3>{title}</h3>
-                    <small>{"Using: <code><b>"+trigger_word+"</code></b> as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}<br></small>
-                </div>
-              </div>
-            </div>
-            '''
-            existing_item_index = next((index for (index, item) in enumerate(loras) if item['repo'] == repo), None)
-            if(not existing_item_index):
-                new_item = {
-                    "image": image,
-                    "title": title,
-                    "repo": repo,
-                    "weights": path,
-                    "trigger_word": trigger_word
-                }
-                print(new_item)
-                existing_item_index = len(loras)
-                loras.append(new_item)
-        
-            return gr.update(visible=True, value=card), gr.update(visible=True), gr.Gallery(selected_index=None), f"Custom: {path}", existing_item_index, trigger_word
-        except Exception as e:
-            gr.Warning(f"Invalid LoRA: either you entered an invalid link, or a non-FLUX LoRA")
-            return gr.update(visible=True, value=f"Invalid LoRA: either you entered an invalid link, a non-FLUX LoRA"), gr.update(visible=True), gr.update(), "", None, ""
+        else:
+            raise Exception("Unsupported URL")
     else:
-        return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
-
-def remove_custom_lora():
-    return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
-
-run_lora.zerogpu = True
+        # Assume it's a Hugging Face model path
+        return get_huggingface_safetensors(link)
 
 css = '''
 #gen_btn{height: 100%}
 #title{text-align: center}
 #title h1{font-size: 3em; display:inline-flex; align-items:center}
-#title img{width: 100px; margin-right: 0.5em}
-#gallery .grid-wrap{height: 10vh}
+#title img{width: 100px; margin-right: 0.25em}
+#gallery .grid-wrap{height: 5vh}
 #lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
+.custom_lora_card{margin-bottom: 1em}
 .card_internal{display: flex;height: 100px;margin-top: .5em}
 .card_internal img{margin-right: 1em}
 .styler{--form-gap-width: 0px !important}
@@ -410,15 +604,21 @@ css = '''
 #progress .generating{display:none}
 .progress-container {width: 100%;height: 30px;background-color: #f0f0f0;border-radius: 15px;overflow: hidden;margin-bottom: 20px}
 .progress-bar {height: 100%;background-color: #4f46e5;width: calc(var(--current) / var(--total) * 100%);transition: width 0.5s ease-in-out}
+.button_total{height: 100%}
+#loaded_loras [data-testid="block-info"]{font-size:80%}
+#custom_lora_structure{background: var(--block-background-fill)}
+#custom_lora_btn{margin-top: auto;margin-bottom: 11px}
+#random_btn{font-size: 300%}
 .info {text-align:center; !important}
 '''
 with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache=(60, 3600)) as app:
     with gr.Tab("FLUX LoRA the Explorer"):
         title = gr.HTML(
-            """<h1><img src="https://huggingface.co/spaces/multimodalart/flux-lora-the-explorer/resolve/main/flux_lora.png" alt="LoRA">FLUX LoRA the Explorer Mod</h1>""",
+            """<h1><img src="https://huggingface.co/spaces/John6666/flux-lora-the-explorer/resolve/main/flux_lora.png" alt="LoRA">FLUX LoRA the Explorer Mod</h1>""",
             elem_id="title",
         )
-        selected_index = gr.State(None)
+        loras_state = gr.State(loras)
+        selected_indices = gr.State([])
         with gr.Row():
             with gr.Column(scale=3):
                 with gr.Group():
@@ -438,7 +638,30 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                         prompt_enhance = gr.Button(value="Enhance your prompt", variant="secondary")
                         auto_trans = gr.Checkbox(label="Auto translate to English", value=False, elem_classes="info")
             with gr.Column(scale=1, elem_id="gen_column"):
-                generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
+                generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn", elem_classes=["button_total"])
+        with gr.Row(elem_id="loaded_loras"):
+            with gr.Column(scale=1, min_width=25):
+                randomize_button = gr.Button("🎲", variant="secondary", scale=1, elem_id="random_btn")
+            with gr.Column(scale=8):
+                with gr.Row():
+                    with gr.Column(scale=0, min_width=50):
+                        lora_image_1 = gr.Image(label="LoRA 1 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50)
+                    with gr.Column(scale=3, min_width=100):
+                        selected_info_1 = gr.Markdown("Select a LoRA 1")
+                    with gr.Column(scale=5, min_width=50):
+                        lora_scale_1 = gr.Slider(label="LoRA 1 Scale", minimum=0, maximum=3, step=0.01, value=1.15)
+                with gr.Row():
+                    remove_button_1 = gr.Button("Remove", size="sm")
+            with gr.Column(scale=8):
+                with gr.Row():
+                    with gr.Column(scale=0, min_width=50):
+                        lora_image_2 = gr.Image(label="LoRA 2 Image", interactive=False, min_width=50, width=50, show_label=False, show_share_button=False, show_download_button=False, show_fullscreen_button=False, height=50)
+                    with gr.Column(scale=3, min_width=100):
+                        selected_info_2 = gr.Markdown("Select a LoRA 2")
+                    with gr.Column(scale=5, min_width=50):
+                        lora_scale_2 = gr.Slider(label="LoRA 2 Scale", minimum=0, maximum=3, step=0.01, value=1.15)
+                with gr.Row():
+                    remove_button_2 = gr.Button("Remove", size="sm")
         with gr.Row():
             with gr.Column():
                 selected_info = gr.Markdown("")
@@ -446,15 +669,15 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                     [(item["image"], item["title"]) for item in loras],
                     label="LoRA Gallery",
                     allow_preview=False,
-                    columns=3,
+                    columns=5,
                     elem_id="gallery"
                 )
                 with gr.Group():
-                    custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path", placeholder="multimodalart/vintage-ads-flux")
-                    gr.Markdown("[Check the list of FLUX LoRas](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
-                custom_lora_info = gr.HTML(visible=False)
-                custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
-                deselect_lora_button = gr.Button("Deselect LoRA", variant="secondary")
+                    with gr.Row(elem_id="custom_lora_structure"):
+                        custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path or *.safetensors public URL", placeholder="multimodalart/vintage-ads-flux", scale=3, min_width=150)
+                        add_custom_lora_button = gr.Button("Add Custom LoRA", elem_id="custom_lora_btn", scale=2, min_width=150)
+                    remove_custom_lora_button = gr.Button("Remove Custom LoRA", visible=False)
+                    gr.Markdown("[Check the list of FLUX LoRAs](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
             with gr.Column():
                 progress_bar = gr.Markdown(elem_id="progress",visible=False)
                 result = gr.Image(label="Generated Image", format="png", show_share_button=False)
@@ -470,10 +693,8 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                         input_image_preprocess = gr.Checkbox(True, label="Preprocess Input image")
                 with gr.Column():
                     with gr.Row():
-                        lora_scale = gr.Slider(label="LoRA Scale", minimum=-3, maximum=3, step=0.01, value=0.95)
                         width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
                         height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
-                    with gr.Row():
                         cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
                         steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
                     with gr.Row():
@@ -482,6 +703,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                         disable_model_cache = gr.Checkbox(False, label="Disable model caching")
                     with gr.Accordion("External LoRA", open=True):
                         with gr.Column():
+                            deselect_lora_button = gr.Button("Remove External LoRAs", variant="secondary")
                             lora_repo_json = gr.JSON(value=[{}] * num_loras, visible=False)
                             lora_repo = [None] * num_loras
                             lora_weights = [None] * num_loras
@@ -506,9 +728,9 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                                             lora_num[i] = gr.Number(i, visible=False)
                             with gr.Accordion("From URL", open=True, visible=True):
                                 with gr.Row():
-                                    lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Flux.1 D", "Flux.1 S"], value=["Flux.1 D", "Flux.1 S"])
-                                    lora_search_civitai_sort = gr.Radio(label="Sort", choices=["Highest Rated", "Most Downloaded", "Newest"], value="Highest Rated")
-                                    lora_search_civitai_period = gr.Radio(label="Period", choices=["AllTime", "Year", "Month", "Week", "Day"], value="AllTime")
+                                    lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Flux.1 D", "Flux.1 S"], value=["Flux.1 D"])
+                                    lora_search_civitai_sort = gr.Radio(label="Sort", choices=["Highest Rated", "Most Downloaded", "Newest"], value="Most Downloaded")
+                                    lora_search_civitai_period = gr.Radio(label="Period", choices=["AllTime", "Year", "Month", "Week", "Day"], value="Month")
                                 with gr.Row():
                                     lora_search_civitai_query = gr.Textbox(label="Query", placeholder="flux", lines=1)
                                     lora_search_civitai_tag = gr.Textbox(label="Tag", lines=1)
@@ -545,24 +767,32 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
     
     gallery.select(
         update_selection,
-        inputs=[width, height],
-        outputs=[prompt, selected_info, selected_index, width, height],
-        queue=False,
-        show_api=False,
-        trigger_mode="once",
+        inputs=[selected_indices, loras_state, width, height],
+        outputs=[prompt, selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, width, height, lora_image_1, lora_image_2])
+    remove_button_1.click(
+        remove_lora_1,
+        inputs=[selected_indices, loras_state],
+        outputs=[selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2]
+    )
+    remove_button_2.click(
+        remove_lora_2,
+        inputs=[selected_indices, loras_state],
+        outputs=[selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2]
+    )
+    randomize_button.click(
+        randomize_loras,
+        inputs=[selected_indices, loras_state],
+        outputs=[selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2, prompt]
     )
-    custom_lora.input(
+    add_custom_lora_button.click(
         add_custom_lora,
-        inputs=[custom_lora],
-        outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, prompt],
-        queue=False,
-        show_api=False,
+        inputs=[custom_lora, selected_indices, loras_state],
+        outputs=[loras_state, gallery, selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2]
     )
-    custom_lora_button.click(
+    remove_custom_lora_button.click(
         remove_custom_lora,
-        outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, custom_lora],
-        queue=False,
-        show_api=False,
+        inputs=[selected_indices, loras_state],
+        outputs=[loras_state, gallery, selected_info_1, selected_info_2, selected_indices, lora_scale_1, lora_scale_2, lora_image_1, lora_image_2]
     )
     gr.on(
         triggers=[generate_button.click, prompt.submit],
@@ -574,15 +804,14 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
         trigger_mode="once",
     ).success(
         fn=run_lora,
-        inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height,
-                 lora_scale, lora_repo_json, cn_on, auto_trans], 
+        inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2,
+                randomize_seed, seed, width, height, loras_state, lora_repo_json, cn_on, auto_trans], 
         outputs=[result, seed, progress_bar],
         queue=True,
         show_api=True,
     )
 
     input_image.upload(preprocess_i2i_image, [input_image, input_image_preprocess, height, width], [input_image], queue=False, show_api=False)
-    deselect_lora_button.click(deselect_lora, None, [prompt, selected_info, selected_index, width, height], queue=False, show_api=False)
     gr.on(
         triggers=[model_name.change, cn_on.change],
         fn=get_t2i_model_info,
@@ -800,10 +1029,38 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
             ]
         )
 
+    with gr.Tab("PNG Info"):
+        def extract_exif_data(image):
+            if image is None: return ""
+
+            try:
+                metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
+
+                for key in metadata_keys:
+                    if key in image.info:
+                        return image.info[key]
+
+                return str(image.info)
+
+            except Exception as e:
+                return f"Error extracting metadata: {str(e)}"
+
+        with gr.Row():
+            with gr.Column():
+                image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
+
+            with gr.Column():
+                result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
+
+                image_metadata.change(
+                    fn=extract_exif_data,
+                    inputs=[image_metadata],
+                    outputs=[result_metadata],
+                )
+
     description_ui()
     gr.LoginButton()
     gr.DuplicateButton(value="Duplicate Space for private use (This demo does not work on CPU. Requires GPU Space)")
 
-
 app.queue()
 app.launch()

loras.json

@@ -41,6 +41,12 @@
     "title": "Retro Comic",
     "trigger_position": "prepend"
   },
+  {
+    "image": "https://huggingface.co/glif/l0w-r3z/resolve/main/images/a19d658b-5d4c-45bc-9df6-f2bec54462a5.png",
+    "repo": "glif/l0w-r3z",
+    "trigger_word": ", l0w-r3z",
+    "title": "Low Res 3D"
+  },
   {
     "image": "https://huggingface.co/renderartist/simplevectorflux/resolve/main/images/ComfyUI_09477_.jpeg",
     "title": "Simple Vector",

mod.py

@@ -58,21 +58,6 @@ def clear_cache():
         raise Exception(f"Cache clearing error: {e}") from e
 
 
-def deselect_lora():
-    selected_index = None
-    new_placeholder = "Type a prompt"
-    updated_text = ""
-    width = 1024
-    height = 1024
-    return (
-        gr.update(placeholder=new_placeholder),
-        updated_text,
-        selected_index,
-        width,
-        height,
-    )
-
-
 def get_repo_safetensors(repo_id: str):
     from huggingface_hub import HfApi
     api = HfApi()
@@ -284,7 +269,7 @@ def get_model_trigger(model_name: str):
 # https://github.com/huggingface/diffusers/issues/4919
 def fuse_loras(pipe, lorajson: list[dict]):
     try:
-        if not lorajson or not isinstance(lorajson, list): return
+        if not lorajson or not isinstance(lorajson, list): return [], []
         a_list = []
         w_list = []
         for d in lorajson:
@@ -292,20 +277,21 @@ def fuse_loras(pipe, lorajson: list[dict]):
             k = d["name"]
             if is_repo_name(k) and is_repo_exists(k):
                 a_name = Path(k).stem
-                pipe.load_lora_weights(k, weight_name=d["filename"], adapter_name = a_name)
+                pipe.load_lora_weights(k, weight_name=d["filename"], adapter_name = a_name, low_cpu_mem_usage=True)
             elif not Path(k).exists():
                 print(f"LoRA not found: {k}")
                 continue
             else:
                 w_name = Path(k).name
                 a_name = Path(k).stem
-                pipe.load_lora_weights(k, weight_name = w_name, adapter_name = a_name)
+                pipe.load_lora_weights(k, weight_name = w_name, adapter_name = a_name, low_cpu_mem_usage=True)
             a_list.append(a_name)
             w_list.append(d["scale"])
-        if not a_list: return
-        pipe.set_adapters(a_list, adapter_weights=w_list)
-        pipe.fuse_lora(adapter_names=a_list, lora_scale=1.0)
+        if not a_list: return [], []
+        #pipe.set_adapters(a_list, adapter_weights=w_list)
+        #pipe.fuse_lora(adapter_names=a_list, lora_scale=1.0)
         #pipe.unload_lora_weights()
+        return a_list, w_list
     except Exception as e:
         print(f"External LoRA Error: {e}")
         raise Exception(f"External LoRA Error: {e}") from e
@@ -315,6 +301,7 @@ def description_ui():
     gr.Markdown(
         """
 - Mod of [multimodalart/flux-lora-the-explorer](https://huggingface.co/spaces/multimodalart/flux-lora-the-explorer),
+ [multimodalart/flux-lora-lab](https://huggingface.co/spaces/multimodalart/flux-lora-lab),
  [jiuface/FLUX.1-dev-Controlnet-Union](https://huggingface.co/spaces/jiuface/FLUX.1-dev-Controlnet-Union),
  [DamarJati/FLUX.1-DEV-Canny](https://huggingface.co/spaces/DamarJati/FLUX.1-DEV-Canny),
  [gokaygokay/FLUX-Prompt-Generator](https://huggingface.co/spaces/gokaygokay/FLUX-Prompt-Generator).

prompts.csv

@@ -0,0 +1,242 @@
+intelligence
+"A raccoon wearing formal clothes, wearing a tophat and holding a cane. The raccoon is holding a garbage bag. Oil painting in the style of traditional Chinese painting."
+a wood cabin
+A tornado made of sharks crashing into a skyscraper. painting in the style of abstract cubism.
+a beach with apartment buildings next to it
+a cat coming through a cat door
+an extreme close-up view of a capybara sitting in a field
+a red cube on top of a blue cube
+weeds in the cracks of a sidewalk
+a smiling man with wavy brown hair and trimmed beard
+A photo of an Athenian vase with a painting of pangolins playing tennis in the style of Egyptian hieroglyphics
+a crowd of people watching fireworks by a park
+a book with the words 'Don't Panic!' written on it
+Portrait of a gecko wearing a train conductor’s hat and holding a flag that has a yin-yang symbol on it. Woodcut.
+a violin next to an apple
+a smiling man
+a cricketer standing next to a wicket
+a thumbnail image of an ice cream cone
+a hamster dragon
+"an old raccoon wearing a top hat and holding an apple, oil painting in the style of van gogh"
+a traffic jam at Times Square
+"a traffic jam at Times Square, with a cat on top of each car"
+a glass of orange juice to the right of a plate with buttered toast on it
+a clock tower
+"Aerial view of downtown Manhattan, but with Millennium Wheel next to the Statue of Liberty. The Great Pyramid is on a sandy island near the buildings."
+a pig in a field
+"the door of knowing, a portal brightly opening the way through darkness. abstract anime landscape oil painting."
+a sticker stuck in the middle of a stop sign
+a cat jumping down from a wall
+a man reading a book with a prism on its cover
+"A DSLR photo of a shiny VW van that has a cityscape painted on it. A smiling sloth stands on grass in front of the van and is wearing a leather jacket, a cowboy hat, a kilt and a bowtie. The sloth is holding a quarterstaff and a big book."
+a wall
+A punk rock frog in a studded leather jacket shouting into a microphone while standing on a boulder
+a red sports car on the road
+A red bus is driving on the road
+A photo of an Athenian vase with a painting of toucans playing tennis in the style of Egyptian hieroglyphics
+a moose by a mountain stream
+a coloring book page of a horse next to a stream
+a coffee mug with an ankh symbol on it
+three green glass bottles
+a blue airplane taxiing on a runway with the sun behind it
+the skyline of New York City
+a present
+a car with no windows
+A tourist is looking at a whale using a binocular
+a white plastic bench with a high arched back
+element
+food
+a book cover
+a series of musical notes
+a large white yacht
+a horse running in a field
+"a statue of Abraham Lincoln wearing an opaque and shiny astronaut's helmet. The statue sits on the moon, with the planet Earth in the sky."
+a volcano erupting near a small town
+an ostrich
+the finale of a fireworks display
+Portrait of a tiger wearing a train conductor's hat and holding a skateboard that has a yin-yang symbol on it. Chinese ink and wash painting
+a giant gorilla at the top of the Empire State Building
+a drawing of the skyline of New York City
+alien history
+a red fire hydrant by a brick wall
+an inflatable rabbit held up in the air by the geyser Old Faithful
+A large city fountain that has milk instead of water. Several cats are leaning into the fountain.
+a mixed media image with a photograph of a woman with long orange hair over a background that is a sketch of a city skyline
+a cat patting a crystal ball with the number 7 written on it in black marker
+Ha Long Bay
+a comic about a friendly car in the city
+a chimpanzee sitting on a wooden bench
+space
+A giraffe walking through a green grass covered field
+"A set of 2x2 emoji icons with happy, angry, surprised and sobbing faces. The emoji icons look like pigs. All of the pigs are wearing crowns."
+a person with arms like a tree branch
+A small house in the wilderness
+a fox
+"Oil painting of a giant robot made of sushi, holding chopsticks."
+a windmill
+"The saying ""BE EXCELLENT TO EACH OTHER"" written in a stained glass window."
+a watermelon chair
+a drawing of a peaceful lakeside landscape
+a thumbnail image of a person skiing
+a nerdy bear wearing glasses and a bowtie
+artificial intelligence
+"a nerdy bear wearing glasses and a bowtie, realistic"
+a green clock in the shape of a pentagon
+a yellow box to the right of a blue sphere
+two chairs
+a woman looking at a house
+an espresso machine
+The trophy doesn't fit into the brown suitcase because it's too small
+a volcano with lava pouring down its slopes
+a laughing woman
+a drawing of a pig face with an eye patch
+a clock with no hands
+a silver fire hydrant next to a sidewalk
+a Tyrannosaurus Rex roaring in front of a palm tree
+A bowl of Pho served with bean sprouts on top
+a pick-up truck
+"A raccoon wearing formal clothes, wearing a tophat and holding a cane. The raccoon is holding a garbage bag. Oil painting in the style of Rembrandt."
+a girl diving into a pool
+a monarch butterfly hatching from its chrysalis
+a ceiling fan with four white blades
+chair
+A portrait of a metal statue of a pharaoh wearing steampunk glasses and a leather jacket over a white t-shirt that has a drawing of a space shuttle on it.
+a horse reading a newspaper
+A photo of a panda made of water.
+three pickup trucks piled on top of each other
+people packed on a double-decker bus
+the grand canyon on a cloudy day
+a pair of headphones on a pumpkin
+A photo of a palm tree made of water.
+view of a clock tower from below
+"a robot painted as graffiti on a brick wall. a sidewalk is in front of the wall, and grass is growing out of cracks in the concrete."
+G I G G L E painted in thick colorful lettering as graffiti on a faded red brick wall with a splotch of exploding white paint.
+Sunset over the sea
+a tiger in a forest
+the city of London on Mars
+the moon with a smiling face
+a sword slicing through pouring milk
+a boy and a tiger
+a comic about a boy and a tiger
+fairy cottage with smoke coming up chimney and a squirrel looking from the window
+a flower with large red petals growing on the moon's surface
+a woman using a sledgehammer to smash an ice sculpture of a goose
+a kangaroo jumping through the park
+a lovestruck cup of boba
+a tennis court with tennis balls scattered all over it
+a family
+a man pouring milk into a coffee cup to make a latte with a beatiful design
+a field with ten massive modern windmills
+a cartoon of a cow jumping over the moon
+the flag of the United Kingdom painted in rusty corrugated iron
+a mouse sitting next to a computer mouse
+a white cat with black ears and markings
+"Two cups of coffee, one with latte art of yin yang symbol. The other has latte art of a heart."
+matching socks with cute cats on them
+"Renaissance portrayals of the Virgin Mary, seated in a loggia. Behind her is a hazy and seemingly isolated landscape imagined by the artist and painted using sfumato."
+a coffee table with a magazine on it
+A heart made of cookie
+a penguin standing on a sidewalk
+"bismuth crystals, intricate fractal pattern"
+"chaotic attractor, multicolored neon"
+"fractal heart pattern, pink blue and white"
+chaotic system interpretation of polyamory
+high dimensional topology of latent spaces
+300 movie titles
+a man with puppet that looks like a king
+a group of skiers are preparing to walk up a sand dune
+a blue t-shirt with a dinosaur on it
+a king salmon
+an Egyptian statue in the desert
+a moose standing over a fox
+A bowl of soup that looks like a monster spray-painted on a wall
+a shih-tzu dog
+a pirate ship
+early bird and night owl
+a taxi
+the eyes of an owl
+graffiti of a rocket ship on a brick wall
+a musical note
+a small airplane flying over rolling hills
+a tiny football in front of three yellow tennis balls
+a cute illustration of a horned owl with a graduation cap and diploma
+a teddy bear to the right of a toy car
+a map of Australia
+an eagle
+a roast turkey on the table
+a store front
+a map of Manhattan
+a portrait of a postal worker who has forgotten their mailbag
+The Statue of Liberty with the Manhattan skyline in the background.
+a bottle of beer next to an ashtray with a half-smoked cigarrette
+a monarch butterfly
+a large blue box
+a car with tires that have yellow rims
+A funny Rube Goldberg machine made out of metal
+a photograph of a fiddle next to a basketball on a ping pong table
+A bowl of Chicken Pho
+view of a giraffe and a zebra in the middle of a field
+a sunken submarine at the bottom of the ocean
+two wine bottles
+a turtle upside down and spinning on its shell
+a painting of a fox in the style of starry night
+a poodle wearing a baseball cap holding a dictionary in hand and writing bonez on a chalkboard
+a stained glass window of a panda eating bamboo
+a blue cow is standing next to a tree with red leaves and yellow fruit. the cow is standing in a field with white flowers. impressionistic painting.
+"an ornate, high-backed mahogany chair with a red cushion"
+the hands of a single person holding a basketball
+a snail
+a man with puppet
+a pickup truck with a horse on its left and two dogs on its right
+an airplane flying into a cloud that looks like monster
+7 dogs sitting around a poker table
+a racoon detective using a microscope while riding in a train
+a kids' book cover with an illustration of white dog driving a red pickup truck
+a woman with long hair next to a luminescent bird
+a boat
+a high-quality oil painting of a psychedelic hamster dragon
+age of empires
+Downtown Austin at sunrise. detailed ink wash.
+a pile of cash on a stone floor
+A helicopter flies over the Arches National Park.
+the word 'START' written on a street surface
+a tennis court with three yellow cones on it
+"A rabbit checks its watch, and so does a gecko."
+a close-up of a bloody mary cocktail
+a view of the Kremlin on a sunny day
+The Oriental Pearl in oil painting
+Tibetan priests ringing a bell
+Portrait of a tiger wearing a train conductor's hat and holding a skateboard that has a yin-yang symbol on it. charcoal sketch
+a cat sitting in a car seat
+a selfie of an old man with a white beard
+"A green sign that says ""Very Deep Learning"" and is at the edge of the Grand Canyon."
+an octopus
+a zebra
+"a warrior, golden army"
+a triangle with a smiling face
+"Pop art, bold colors, mass culture, commercial techniques, screen printing, repetition, consumerism imagery, iconic portraits, flat imagery, irony, everyday objects"
+"Minimalist, conceptual, geometric, bold, abstract, systematic, wall drawings, instructions-based, modular forms, repetitive patterns, color-blocks, line variations, innovative, influential"
+"Conceptual, mixed-media, appropriation, text-and-image, irony, photo-collage, bold colors, visual narrative, humorous, minimalist, innovative, montage, semiotics, critique, pop culture, fragmented, juxtaposition"
+"Feminist, avant-garde, body art, performance art, video art, provocative, conceptual, radical, multimedia, body politics, identity exploration, societal critique"
+"In the style of Rembrandt, this portrait on canvas captures a man seated in a dimly lit space, his gaze introspective and laden with experience. His clothing is of a rich, textured fabric, suggesting a life of complexity and depth. The sparse background emphasizes his solitary figure, highlighting the contemplative mood and the dignified simplicity of his demeanor. The overall atmosphere is one of introspection and timeless wisdom."
+"East-West fusion, trans-cultural, dream-like, nature-inspired, ethereal, organic forms, delicate colors, figurative-abstract blend, poetic, intimate, evolving, mystical, feminine perspective"
+"17th century, Rembrandt Harmensz van Rijn, Baroque art, oil on canvas, half-body portrait, solitary woman, neutral expression, indoor scene, warm lighting, detailed drapery, velvet dress, gold embroidery, pearl necklace, lace collar, ornate jewelry, realistic skin tones, fine hair details, soft shadows, meticulous brushwork, classical pose, timeless elegance, artistic mastery, cultural significance, visual narrative."
+"Rembrandt Harmensz van Rijn, 17th century Dutch Golden Age, oil on canvas, half-body portrait, female figure, neutral facial expression, elaborate Renaissance attire, rich velvet dress with intricate embroidery, lace collar, pearl necklace, ornate headdress adorned with jewels, seated pose, hands resting on a table, dark background with soft lighting, realistic style, fine brushwork, attention to detail in textures and fabrics, historical context, cultural significance."
+"Rembrandt Harmensz. van Rijn, oil on canvas, captures a distinguished gentleman in a moment of quiet reflection. He is attired in a sumptuous black velvet cloak with a high white collar, the textures rendered with precise detail to showcase the contrast between the soft velvet and crisp linen. The subtle play of light illuminates his contemplative expression and highlights the gentle grip of his hand on a leather-bound journal, hinting at a life of intellectual pursuits. The background is a soft interplay of shadows, enhancing the intimate and introspective mood of the portrait."
+"Minimalist, large-scale, industrial materials, site-specific, immersive, abstract, sculptural, steel-focused, gravity-based, experiential, curved forms, monumental, spatial exploration, environmental interaction, tactile"
+"Minimalist, conceptual, postmodern, geometric abstraction, color-block, multi-disciplinary, playful irony, spatial intervention, typographic, avant-garde, video art, performance elements"
+"Abstract, minimalism, expressionism, bold colors, geometric shapes, large-scale works, mixed media, architectural elements, contemporary, post-modern, layered textures"
+"Environmental art, large-scale installations, fabric-wrapped structures, public spaces, temporary works, conceptual, immersive experiences, land art, transformative, outdoor"
+"found-object assemblage, Eat Art, Nouveau Réalisme, tableaux traps, everyday objects, collage, three-dimensional, playful, ironic, conceptual, kinetic, interactive, mixed media"
+a submarine floating past a shark
+"Photomontage, feminist, critical, conceptual, socio-political, collage, video art, performance, domestic sphere, anti-war, satire, urban life, activist, multimedia, appropriation"
+"Abstract expressionism, scribbles, calligraphy, graffiti, child-like, spontaneous, emotional, textured, layered, historical references, poetic, minimal color, gestural, large-scale canvases"
+"Contemporary, provocative, conceptual, mixed-media, death-themed, colorful, controversial, pharmaceutical motifs, formaldehyde specimens, spot paintings, spin art, luxury, critique of consumerism, installation art."
+a room
+"minimalism, color fields, abstract, geometric shapes, bold simplicity, hard edges, monochromes, vibrant, non-figurative, spatial relationships, innovative, pure forms"
+"Photographic narrative, African-American experience, critical race exploration, feminism, cultural identity, social justice, mixed media, evocative, poignant, reflective, storytelling, human condition"
+a Harley-Davidson motorcycle with a flame decal
+an ornate jewel-encrusted key
+a woman running on a trail
+a giraffe with a funny face
+square blue apples on a tree with circular yellow leaves

requirements.txt

@@ -1,9 +1,9 @@
-spaces
 torch
-git+https://github.com/huggingface/diffusers@aa73072f1f7014635e3de916cbcf47858f4c37a0
+git+https://github.com/huggingface/diffusers.git@1131e3d04e3131f4c24565257665d75364d696d9
 transformers
-peft
+git+https://github.com/huggingface/peft.git
 sentencepiece
+spaces==0.30.3
 torchvision
 huggingface_hub
 timm