Upload appTest1.py

appTest1.py

@@ -0,0 +1,672 @@
+import os
+import gradio as gr
+from random import randint
+from operator import itemgetter
+import bisect
+from all_models import tags_plus_models,models,models_plus_tags
+from datetime import datetime
+from externalmod import gr_Interface_load
+import asyncio
+import os
+from threading import RLock
+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.
+
+
+now2 = 0
+inference_timeout = 300
+MAX_SEED = 2**32-1
+
+
+nb_rep=2
+nb_mod_dif=20
+nb_models=nb_mod_dif*nb_rep
+
+cache_image={}
+cache_image_actu={}
+
+def split_models(models,nb_models):
+    models_temp=[]
+    models_lis_temp=[]
+    i=0
+    for m in models:
+        models_temp.append(m)
+        i=i+1
+        if i%nb_models==0:
+            models_lis_temp.append(models_temp)
+            models_temp=[]
+    if len(models_temp)>1:
+        models_lis_temp.append(models_temp)
+    return models_lis_temp
+
+def split_models_axb(models,a,b):
+    models_temp=[]
+    models_lis_temp=[]
+    i=0
+    nb_models=b
+    for m in models:
+        for j in range(a):
+            models_temp.append(m)
+        i=i+1
+        if i%nb_models==0:
+            models_lis_temp.append(models_temp)
+            models_temp=[]
+    if len(models_temp)>1:
+        models_lis_temp.append(models_temp)
+    return models_lis_temp 
+
+def split_models_8x3(models,nb_models):
+    models_temp=[]
+    models_lis_temp=[]
+    i=0
+    nb_models_x3=8
+    for m in models:
+        models_temp.append(m)
+        i=i+1
+        if i%nb_models_x3==0:
+            models_lis_temp.append(models_temp+models_temp+models_temp)
+            models_temp=[]
+    if len(models_temp)>1:
+        models_lis_temp.append(models_temp+models_temp+models_temp)
+    return models_lis_temp
+
+def construct_list_models(tags_plus_models,nb_rep,nb_mod_dif):
+    list_temp=[]
+    output=[]
+    for tag_plus_models in tags_plus_models:
+        list_temp=split_models_axb(tag_plus_models[2],nb_rep,nb_mod_dif)
+        list_temp2=[]
+        i=0
+        for elem in list_temp:
+            list_temp2.append([f"{tag_plus_models[0]}_{i+1}/{len(list_temp)} ({len(elem)}) : {elem[0]} - {elem[len(elem)-1]}" ,elem])
+            i+=1
+        output.append([f"{tag_plus_models[0]} ({tag_plus_models[1]})",list_temp2])
+        tag_plus_models[0]=f"{tag_plus_models[0]} ({tag_plus_models[1]})"
+    return output
+
+models_test = []
+models_test = construct_list_models(tags_plus_models,nb_rep,nb_mod_dif)
+
+def get_current_time():
+    now = datetime.now()
+    now2 = now
+    current_time = now2.strftime("%Y-%m-%d %H:%M:%S")
+    kii = "" # ?
+    ki = f'{kii} {current_time}'
+    return ki
+
+def load_fn_original(models):
+    global models_load
+    global num_models
+    global default_models
+    models_load = {}
+    num_models = len(models)
+    if num_models!=0:
+        default_models = models[:num_models]
+    else:
+        default_models = {}
+    for model in models:
+        if model not in models_load.keys():
+            try:
+                m = gr.load(f'models/{model}')
+            except Exception as error:
+                m = gr.Interface(lambda txt: None, ['text'], ['image'])
+                print(error)
+            models_load.update({model: m})
+
+def load_fn(models):
+    global models_load
+    global num_models
+    global default_models
+    models_load = {}
+    num_models = len(models)
+    i=0
+    if num_models!=0:
+        default_models = models[:num_models]
+    else:
+        default_models = {}
+    for model in models:
+        i+=1
+        if i%50==0:
+            print("\n\n\n-------"+str(i)+'/'+str(len(models))+"-------\n\n\n")
+        if model not in models_load.keys():
+            try:
+                m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
+            except Exception as error:
+                m = gr.Interface(lambda txt: None, ['text'], ['image'])
+                print(error)
+            models_load.update({model: m})
+
+
+"""models = models_test[1]"""
+#load_fn_original
+load_fn(models)
+"""models = {}
+load_fn(models)"""
+    
+
+def extend_choices(choices):
+    return choices + (nb_models - len(choices)) * ['NA']
+    """return choices + (num_models - len(choices)) * ['NA']"""
+
+def extend_choices_b(choices):
+    choices_plus = extend_choices(choices)
+    return [gr.Textbox(m, visible=False) for m in choices_plus]
+
+def update_imgbox(choices):
+    choices_plus = extend_choices(choices)
+    return [gr.Image(None, label=m,interactive=False, visible=(m != 'NA'),show_share_button=False) for m in choices_plus]
+
+def choice_group_a(group_model_choice):
+    return group_model_choice
+
+def choice_group_b(group_model_choice):
+    choiceTemp =choice_group_a(group_model_choice)
+    choiceTemp = extend_choices(choiceTemp)
+    """return [gr.Image(label=m, min_width=170, height=170) for m in choice]"""
+    return [gr.Image(None, label=m,interactive=False, visible=(m != 'NA'),show_share_button=False) for m in choiceTemp]
+
+def choice_group_c(group_model_choice):
+    choiceTemp=choice_group_a(group_model_choice)
+    choiceTemp = extend_choices(choiceTemp)
+    return [gr.Textbox(m) for m in choiceTemp]
+    
+def choice_group_d(group_model_choice):
+    choiceTemp=choice_group_a(group_model_choice)
+    choiceTemp = extend_choices(choiceTemp)
+    return [gr.Textbox(choiceTemp[i*nb_rep], visible=(choiceTemp[i*nb_rep] != 'NA'),show_label=False) for i in range(nb_mod_dif)]
+def choice_group_e(group_model_choice):
+    choiceTemp=choice_group_a(group_model_choice)
+    choiceTemp = extend_choices(choiceTemp)
+    return [gr.Column(visible=(choiceTemp[i*nb_rep] != 'NA')) for i in range(nb_mod_dif)]
+
+def cutStrg(longStrg,start,end):
+    shortStrg=''
+    for i in range(end-start):
+        shortStrg+=longStrg[start+i]
+    return shortStrg
+    
+def aff_models_perso(txt_list_perso,nb_models=nb_models,models=models):
+    list_perso=[]
+    t1=True
+    start=txt_list_perso.find('\"')
+    if start!=-1:
+        while t1:
+            start+=1
+            end=txt_list_perso.find('\"',start)
+            if end != -1:
+                txtTemp=cutStrg(txt_list_perso,start,end)
+                if txtTemp in models:
+                    list_perso.append(cutStrg(txt_list_perso,start,end))
+            else :
+                t1=False
+            start=txt_list_perso.find('\"',end+1)
+            if start==-1:
+                t1=False
+            if len(list_perso)>=nb_models:
+                t1=False
+    return list_perso
+
+def aff_models_perso_b(txt_list_perso):
+    return choice_group_b(aff_models_perso(txt_list_perso))
+
+def aff_models_perso_c(txt_list_perso):
+    return choice_group_c(aff_models_perso(txt_list_perso))
+            
+            
+def tag_choice(group_tag_choice):
+    return gr.Dropdown(label="List of Models with the chosen Tag", show_label=True, choices=list(group_tag_choice) , interactive = True , filterable = False)
+
+def test_pass(test):
+    if test==os.getenv('p'):
+        print("ok")
+        return gr.Dropdown(label="Lists Tags", show_label=True, choices=list(models_test) , interactive = True)
+    else:
+        print("nop")
+        return gr.Dropdown(label="Lists Tags", show_label=True, choices=list([]) , interactive = True)
+
+def test_pass_aff(test):
+    if test==os.getenv('p'):
+        return gr.Accordion( open=True, visible=True) ,gr.Row(visible=False)
+    else:
+        return gr.Accordion( open=True, visible=False) , gr.Row()
+
+
+# https://huggingface.co/docs/api-inference/detailed_parameters
+# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
+async def infer(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1, timeout=inference_timeout):
+    from pathlib import Path
+    kwargs = {}
+    if height is not None and height >= 256: kwargs["height"] = height
+    if width is not None and width >= 256: kwargs["width"] = width
+    if steps is not None and steps >= 1: kwargs["num_inference_steps"] = steps
+    if cfg is not None and cfg > 0: cfg = kwargs["guidance_scale"] = cfg
+    noise = ""
+    if seed >= 0: kwargs["seed"] = seed
+    else:
+        rand = randint(1, 500)
+        for i in range(rand):
+            noise += " "
+    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn,
+                               prompt=f'{prompt} {noise}', negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
+    await asyncio.sleep(0)
+    try:
+        result = await asyncio.wait_for(task, timeout=timeout)
+    except (Exception, asyncio.TimeoutError) as e:
+        print(e)
+        print(f"Task timed out: {model_str}")
+        if not task.done(): task.cancel()
+        result = None
+    if task.done() and result is not None:
+        with lock:
+            png_path = "image.png"
+            result.save(png_path)
+            image = str(Path(png_path).resolve())
+        return image
+    return None
+
+def gen_fn(model_str, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1):
+    if model_str == 'NA':
+        return None
+    try:
+        loop = asyncio.new_event_loop()
+        result = loop.run_until_complete(infer(model_str, prompt, nprompt,
+                                         height, width, steps, cfg, seed, inference_timeout))
+    except (Exception, asyncio.CancelledError) as e:
+        print(e)
+        print(f"Task aborted: {model_str}")
+        result = None
+    finally:
+        loop.close()
+    return result
+
+def gen_fn_original(model_str, prompt):
+    if model_str == 'NA':
+        return None
+    noise = str(randint(0, 9999))
+    try :
+        m=models_load[model_str](f'{prompt} {noise}')
+    except Exception as error : 
+        print("error : " + model_str)
+        print(error)
+        m=False
+    
+    return m
+
+   
+def add_gallery(image, model_str, gallery):
+    if gallery is None: gallery = []
+    #with lock:
+    if image is not None: gallery.append((image, model_str))
+    return gallery
+
+def reset_gallery(gallery):
+    return add_gallery(None,"",[])
+
+def load_gallery(gallery,id):
+    gallery = reset_gallery(gallery)
+    for c in cache_image[f"{id}"]:
+        gallery=add_gallery(c[0],c[1],gallery)
+    return gallery
+def load_gallery_sorted(gallery,id):
+    gallery = reset_gallery(gallery)
+    for c in sorted(cache_image[f"{id}"], key=itemgetter(1)):
+        gallery=add_gallery(c[0],c[1],gallery)
+    return gallery
+def load_gallery_actu(gallery,id):
+    gallery = reset_gallery(gallery)
+    for c in cache_image_actu[f"{id}"]:
+        gallery=add_gallery(c[0],c[1],gallery)
+    return gallery
+
+def add_cache_image(image, model_str,id,cache_image=cache_image):
+    if image is not None:
+        cache_image[f"{id}"].append((image,model_str))
+    #cache_image=sorted(cache_image, key=itemgetter(1))
+    return 
+def add_cache_image_actu(image, model_str,id,cache_image_actu=cache_image_actu):
+    if image is not None:
+        bisect.insort(cache_image_actu[f"{id}"],(image, model_str), key=itemgetter(1))
+    #cache_image_actu=sorted(cache_image_actu, key=itemgetter(1))
+    return
+def reset_cache_image(id,cache_image=cache_image):
+    cache_image[f"{id}"].clear()
+    return 
+def reset_cache_image_actu(id,cache_image_actu=cache_image_actu):
+    cache_image_actu[f"{id}"].clear()
+    return 
+def reset_cache_image_all_sessions(cache_image=cache_image,cache_image_actu=cache_image_actu):
+    for key, listT in cache_image.items():
+        listT.clear()
+    for key, listT in cache_image_actu.items():
+        listT.clear()
+    return 
+    
+def set_session(id):
+    if id==0:
+        randTemp=randint(1,MAX_SEED)
+        cache_image[f"{randTemp}"]=[]
+        cache_image_actu[f"{randTemp}"]=[]
+        return gr.Number(visible=False,value=randTemp)
+    else :
+        return id
+def print_info_sessions():
+    lenTot=0
+    print("###################################")
+    print("number of sessions : "+str(len(cache_image)))
+    for key, listT in cache_image.items():
+        print("session "+key+" : "+str(len(listT)))
+        lenTot+=len(listT)
+    print("images total = "+str(lenTot))
+    print("###################################")
+    return
+
+def disp_models(group_model_choice,nb_rep=nb_rep):
+    listTemp=[]
+    strTemp='\n'
+    i=0
+    for m in group_model_choice:
+        if m not in listTemp:
+            listTemp.append(m)
+    for m in listTemp:
+        i+=1
+        strTemp+="\"" + m + "\",\n"
+        if i%(8/nb_rep)==0:
+            strTemp+="\n"
+    return gr.Textbox(label="models",value=strTemp)
+
+def search_models(str_search,tags_plus_models=tags_plus_models):
+    output1="\n"
+    output2=""
+    for m in tags_plus_models[0][2]:
+        if m.find(str_search)!=-1:
+            output1+="\"" + m + "\",\n"
+    outputPlus="\n From tags : \n\n"
+    for tag_plus_models in tags_plus_models:
+        if str_search.lower() == tag_plus_models[0].lower() and str_search!="":
+            for m in tag_plus_models[2]:
+                output2+="\"" + m + "\",\n"
+    if output2 != "":
+        output=output1+outputPlus+output2
+    else :
+        output=output1
+    return gr.Textbox(label="out",value=output)
+
+def search_info(txt_search_info,models_plus_tags=models_plus_tags):
+    outputList=[]
+    if txt_search_info.find("\"")!=-1:
+        start=txt_search_info.find("\"")+1
+        end=txt_search_info.find("\"",start)
+        m_name=cutStrg(txt_search_info,start,end)
+    else :
+        m_name = txt_search_info
+    for m in models_plus_tags:
+        if m_name == m[0]:
+            outputList=m[1]
+    if len(outputList)==0:
+        outputList.append("Model Not Find")
+    return gr.Textbox(label="out",value=outputList)
+
+def add_in_blacklist(bl,model):
+    return gr.Textbox(bl+(f"\"{model}\",\n"))
+def add_in_fav(fav,model):
+    return gr.Textbox(fav+(f"\"{model}\",\n"))
+def rand_from_all_all_models():
+    if len(tags_plus_models[0][2])<nb_mod_dif:
+        return choice_group_c(tags_plus_models[0][2])
+    else:
+        result=[]
+        list_index_temp=[]
+        for i in range(len(tags_plus_models[0][2])):
+            list_index_temp.append(i)
+        for i in range(nb_mod_dif):
+            index_temp=randint(1,len(list_index_temp))-1
+            for j in range(nb_rep):
+                result.append(gr.Textbox(tags_plus_models[0][2][list_index_temp[index_temp]]))
+            list_index_temp.remove(list_index_temp[index_temp])
+        return result
+def rand_from_tag_all_models(index):
+    if len(tags_plus_models[index][2])<nb_mod_dif:
+        return choice_group_c(models_test[index][1][0][1])
+    else:
+        result=[]
+        list_index_temp=[]
+        for i in range(len(tags_plus_models[index][2])):
+            list_index_temp.append(i)
+        for i in range(nb_mod_dif):
+            index_temp=randint(1,len(list_index_temp))-1
+            for j in range(nb_rep):
+                result.append(gr.Textbox(tags_plus_models[index][2][list_index_temp[index_temp]]))
+            list_index_temp.remove(list_index_temp[index_temp])
+        return result
+        
+def find_index_tag(group_tag_choice):
+    for i in (range(len(models_test)-1)):
+        if models_test[i][1]==group_tag_choice:
+            return gr.Number(i)
+    return gr.Number(0)
+
+def ratio_chosen(choice_ratio,width,height):
+    if choice_ratio == [None,None]:
+        return width , height
+    else :
+        return gr.Slider(label="Width", info="If 0, the default value is used.", maximum=2024, step=32, value=choice_ratio[0]), gr.Slider(label="Height", info="If 0, the default value is used.", maximum=2024, step=32, value=choice_ratio[1])
+
+list_ratios=[["None",[None,None]],
+             ["4:1 (2048 x 512)",[2048,512]],
+             ["12:5 (1536 x 640)",[1536,640]],
+             ["~16:9 (1344 x 768)",[1344,768]],
+             ["~3:2 (1216 x 832)",[1216,832]],
+             ["~4:3 (1152 x 896)",[1152,896]],
+             ["1:1 (1024 x 1024)",[1024,1024]],
+             ["~3:4 (896 x 1152)",[896,1152]],
+             ["~2:3 (832 x 1216)",[832,1216]],
+             ["~9:16 (768 x 1344)",[768,1344]],
+             ["5:12 (640 x 1536)",[640,1536]],
+             ["1:4 (512 x 2048)",[512,2048]]]
+
+def make_me():
+   # with gr.Tab('The Dream'): 
+        with gr.Row():
+            #txt_input = gr.Textbox(lines=3, width=300, max_height=100)
+            #txt_input = gr.Textbox(label='Your prompt:', lines=3, width=300, max_height=100)
+            with gr.Column(scale=4):
+                with gr.Group():
+                    txt_input = gr.Textbox(label='Your prompt:', lines=3)
+                    with gr.Accordion("Advanced", open=False, visible=True):
+                        neg_input = gr.Textbox(label='Negative prompt:', lines=1)
+                        with gr.Row():
+                            width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                            height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
+                        with gr.Row():
+                            choice_ratio = gr.Dropdown(label="Ratio Width/Height", 
+                                                info="OverWrite Width and Height (W*H<1024*1024)", 
+                                                show_label=True, choices=list(list_ratios) , interactive = True, value=list_ratios[0][1])
+                            choice_ratio.change(ratio_chosen,[choice_ratio,width,height],[width,height])
+                        with gr.Row():
+                            steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
+                            cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
+                            seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
+                #gen_button = gr.Button('Generate images', width=150, height=30)
+            #stop_button = gr.Button('Stop', variant='secondary', interactive=False, width=150, height=30)
+            gen_button = gr.Button('Generate images', scale=3)
+            stop_button = gr.Button('Stop', variant='secondary', interactive=False, scale=1)
+
+            gen_button.click(lambda: gr.update(interactive=True), None, stop_button)
+            #gr.HTML("""
+            #<div style="text-align: center; max-width: 100%; margin: 0 auto;">
+            #    <body>
+            #    </body>
+            #</div>
+            #""")
+        with gr.Row() as block_images:
+            choices=[models_test[0][1][0][1][0]]
+            output = []
+            current_models = []
+            #text_disp_models = []
+            block_images_liste = []
+            block_images_options_liste = []
+            button_rand_from_tag=[]
+            button_rand_from_all=[]
+            button_rand_from_fav=[]
+            button_blacklisted=[]
+            button_favorites=[]
+            choices_plus = extend_choices(choices)
+            for i in range(nb_mod_dif):
+                with gr.Column(visible=(choices_plus[i*nb_rep] != 'NA')) as block_Temp :
+                    block_images_liste.append(block_Temp)
+                    with gr.Group():
+                        with gr.Row():
+                            for j in range(nb_rep):
+                                output.append(gr.Image(None, label=choices_plus[i*nb_rep+j],interactive=False, 
+                                                       visible=(choices_plus[i*nb_rep+j] != 'NA'),show_label=False,show_share_button=False))
+                        for j in range(nb_rep):
+                            current_models.append(gr.Textbox(choices_plus[i*nb_rep+j], visible=(j==0),show_label=False))
+                        #text_disp_models.append(gr.Textbox(choices_plus[i*nb_rep], visible=(choices_plus[i*nb_rep] != 'NA'),show_label=False))
+                        with gr.Row(visible=False) as block_Temp:
+                            block_images_options_liste.append(block_Temp)
+                            button_rand_from_tag.append(gr.Button("Random\nfrom tag"))
+                            button_rand_from_all.append(gr.Button("Random\nfrom all"))
+                            button_rand_from_fav.append(gr.Button("Random\nfrom fav"))
+                            button_blacklisted.append(gr.Button("put in\nblacklist"))
+                            button_favorites.append(gr.Button("put in\nfavorites"))
+                        
+
+            #output = update_imgbox([choices[0]])
+            #current_models = extend_choices_b([choices[0]])
+            
+            for m, o in zip(current_models, output):
+                gen_event = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fn,
+                                inputs=[m, txt_input, neg_input, height, width, steps, cfg, seed], outputs=[o])
+                stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event])
+            
+        with gr.Row() as blockPass:
+            txt_input_p = gr.Textbox(label="Pass", lines=1)
+            test_button = gr.Button(' ')    
+
+        
+        with gr.Accordion( open=True, visible=False) as stuffs:
+            with gr.Accordion("Advanced",open=False):
+                images_options=gr.Checkbox(False,label="Images Options")
+                images_options.change(lambda x:[gr.Row(visible=x) for b in range(nb_mod_dif)],[images_options],block_images_options_liste)
+                blacklist_perso=gr.Textbox(label="Blacklist perso")
+                fav_perso=gr.Textbox(label="Fav perso")
+                button_rand_from_tag_all_models=gr.Button("Random all models from tag")
+                button_rand_from_all_all_models=gr.Button("Random all models from all")
+                button_rand_from_fav_all_models=gr.Button("Random all models from fav")
+                
+                
+            with gr.Accordion("Gallery",open=False):
+                with gr.Row():
+                    #global cache_image
+                    #global cache_image_actu
+                    id_session=gr.Number(visible=False,value=0)
+                    gen_button.click(set_session, id_session, id_session)
+                    cache_image[f"{id_session.value}"]=[]
+                    cache_image_actu[f"{id_session.value}"]=[]
+                    with gr.Column():
+                        b11 = gr.Button('Load Galerry Actu')
+                        b12 = gr.Button('Load Galerry All')
+                        b13 = gr.Button('Load Galerry All (sorted)')
+                    gallery = gr.Gallery(label="Output", show_download_button=True, elem_classes="gallery",
+                                    interactive=False, show_share_button=True, container=True, format="png",
+                                    preview=True, object_fit="cover",columns=4,rows=4) 
+                    with gr.Column():
+                        b21 = gr.Button('Reset Gallery')
+                        b22 = gr.Button('Reset Gallery All')
+                        b23 = gr.Button('Reset All Sessions')
+                        b24 = gr.Button('print info sessions')
+                    b11.click(load_gallery_actu,[gallery,id_session],gallery)
+                    b12.click(load_gallery,[gallery,id_session],gallery)
+                    b13.click(load_gallery_sorted,[gallery,id_session],gallery)
+                    b21.click(reset_gallery,[gallery],gallery)
+                    b22.click(reset_cache_image,[id_session],gallery)
+                    b23.click(reset_cache_image_all_sessions,[],[])
+                    b24.click(print_info_sessions,[],[])
+                    for m, o in zip(current_models, output):
+                        #o.change(add_gallery, [o, m, gallery], [gallery])
+                        o.change(add_cache_image,[o,m,id_session],[])
+                        o.change(add_cache_image_actu,[o,m,id_session],[])
+                gen_button.click(reset_cache_image_actu, [id_session], [])
+                gen_button.click(lambda id:gr.Button('Load Galerry All ('+str(len(cache_image[f"{id}"]))+")"), [id_session], [b12])
+                
+            with gr.Group():
+                with gr.Row():
+                    #group_tag_choice = gr.Dropdown(label="Lists Tags", show_label=True, choices=list([]) , interactive = True)
+                    group_tag_choice = gr.Dropdown(label="Lists Tags", show_label=True, choices=list(models_test), interactive = True,value=models_test[0][1])
+                    #group_tag_choice = gr.Dropdown(label="Lists Tags", show_label=True, choices=list(models_test), interactive = True)
+                    index_tag=gr.Number(0,visible=False)
+                    
+                with gr.Row():
+                    group_model_choice = gr.Dropdown(label="List of Models with the chosen Tag", show_label=True, choices=list([]), interactive = True)
+                    group_model_choice.change(choice_group_b,group_model_choice,output)
+                    group_model_choice.change(choice_group_c,group_model_choice,current_models)
+                    #group_model_choice.change(choice_group_d,group_model_choice,text_disp_models)
+                    group_model_choice.change(choice_group_e,group_model_choice,block_images_liste)
+                    group_tag_choice.change(tag_choice,group_tag_choice,group_model_choice)
+                    group_tag_choice.change(find_index_tag,group_tag_choice,index_tag)
+
+            with gr.Accordion("Display/Load Models") :
+                with gr.Row():
+                    txt_list_models=gr.Textbox(label="Models Actu",value="")
+                    group_model_choice.change(disp_models,group_model_choice,txt_list_models)
+                    
+                    with gr.Column():
+                        txt_list_perso = gr.Textbox(label='List Models Perso to Load')
+                    
+                        button_list_perso = gr.Button('Load')
+                        button_list_perso.click(aff_models_perso_b,txt_list_perso,output)
+                        button_list_perso.click(aff_models_perso_c,txt_list_perso,current_models)
+    
+            with gr.Row():
+                txt_search = gr.Textbox(label='Search in')
+                txt_output_search = gr.Textbox(label='Search out')
+                button_search = gr.Button('Research')
+                button_search.click(search_models,txt_search,txt_output_search)
+
+            with gr.Row():
+                txt_search_info = gr.Textbox(label='Search info in')
+                txt_output_search_info = gr.Textbox(label='Search info out')
+                button_search_info = gr.Button('Research info')
+                button_search_info.click(search_info,txt_search_info,txt_output_search_info)
+        
+            
+        with gr.Row():
+            test_button.click(test_pass_aff,txt_input_p,[stuffs,blockPass])
+            #test_button.click(test_pass,txt_input_p,group_tag_choice)
+            
+            #text_disp_models = []
+            #button_rand_from_tag=[]
+            #button_rand_from_all=[]
+            button_rand_from_all_all_models.click(rand_from_all_all_models,[],current_models)
+            button_rand_from_tag_all_models.click(rand_from_tag_all_models,index_tag,current_models)
+            for i in range(nb_mod_dif):
+                #######################################################################################################################
+                #button_rand_from_tag.click()
+                #button_rand_from_all.click()
+                #button_rand_from_fav.click()
+                button_blacklisted[i].click(add_in_blacklist,[blacklist_perso,current_models[i*nb_rep]],blacklist_perso)
+                button_favorites[i].click(add_in_fav,[fav_perso,current_models[i*nb_rep]],fav_perso)
+
+
+
+            gr.HTML("""
+                <div class="footer">
+                <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77 and Omnibus's Maximum Multiplier!
+                </p>
+            """)
+
+js_code = """
+    
+    console.log('ghgh');
+"""
+
+with gr.Blocks(theme="Nymbo/Nymbo_Theme", fill_width=True, css="div.float.svelte-1mwvhlq {    position: absolute;    top: var(--block-label-margin);    left: var(--block-label-margin);    background: none;    border: none;}") as demo: 
+    gr.Markdown("<script>" + js_code + "</script>")
+    make_me()
+
+
+# https://www.gradio.app/guides/setting-up-a-demo-for-maximum-performance
+#demo.queue(concurrency_count=999) # concurrency_count is deprecated in 4.x
+demo.queue(default_concurrency_limit=200, max_size=200)
+demo.launch(max_threads=400)