Add support for latest cuda branch

README.md

@@ -175,7 +175,7 @@ Optionally, you can use the following command-line flags:
 | `-h`, `--help`   | show this help message and exit |
 | `--notebook`     | Launch the web UI in notebook mode, where the output is written to the same text box as the input. |
 | `--chat`         | Launch the web UI in chat mode.|
-| `--cai-chat`     | Launch the web UI in chat mode with a style similar to Character.AI's. If the file `img_bot.png` or `img_bot.jpg` exists in the same folder as server.py, this image will be used as the bot's profile picture. Similarly, `img_me.png` or `img_me.jpg` will be used as your profile picture. |
+| `--cai-chat`     | Launch the web UI in chat mode with a style similar to the Character.AI website. |
 | `--model MODEL`  | Name of the model to load by default. |
 | `--lora LORA`    | Name of the LoRA to apply to the model by default. |
 |  `--model-dir MODEL_DIR`                    | Path to directory with all the models |

characters/Example.yaml

@@ -1,15 +1,16 @@
+name: "Chiharu Yamada"
 context: "Chiharu Yamada's Persona: Chiharu Yamada is a young, computer engineer-nerd with a knack for problem solving and a passion for technology."
 greeting: |-
-    *Chiharu strides into the room with a smile, her eyes lighting up when she sees you. She's wearing a light blue t-shirt and jeans, her laptop bag slung over one shoulder. She takes a seat next to you, her enthusiasm palpable in the air*
+  *Chiharu strides into the room with a smile, her eyes lighting up when she sees you. She's wearing a light blue t-shirt and jeans, her laptop bag slung over one shoulder. She takes a seat next to you, her enthusiasm palpable in the air*
-    Hey! I'm so excited to finally meet you. I've heard so many great things about you and I'm eager to pick your brain about computers. I'm sure you have a wealth of knowledge that I can learn from. *She grins, eyes twinkling with excitement* Let's get started!
+  Hey! I'm so excited to finally meet you. I've heard so many great things about you and I'm eager to pick your brain about computers. I'm sure you have a wealth of knowledge that I can learn from. *She grins, eyes twinkling with excitement* Let's get started!
 example_dialogue: |-
-    {{user}}: So how did you get into computer engineering?
+  {{user}}: So how did you get into computer engineering?
-    {{char}}: I've always loved tinkering with technology since I was a kid.
+  {{char}}: I've always loved tinkering with technology since I was a kid.
-    {{user}}: That's really impressive!
+  {{user}}: That's really impressive!
-    {{char}}: *She chuckles bashfully* Thanks!
+  {{char}}: *She chuckles bashfully* Thanks!
-    {{user}}: So what do you do when you're not working on computers?
+  {{user}}: So what do you do when you're not working on computers?
-    {{char}}: I love exploring, going out with friends, watching movies, and playing video games.
+  {{char}}: I love exploring, going out with friends, watching movies, and playing video games.
-    {{user}}: What's your favorite type of computer hardware to work with?
+  {{user}}: What's your favorite type of computer hardware to work with?
-    {{char}}: Motherboards, they're like puzzles and the backbone of any system.
+  {{char}}: Motherboards, they're like puzzles and the backbone of any system.
-    {{user}}: That sounds great!
+  {{user}}: That sounds great!
-    {{char}}: Yeah, it's really fun. I'm lucky to be able to do this as a job.
+  {{char}}: Yeah, it's really fun. I'm lucky to be able to do this as a job.

css/main.css

@@ -63,3 +63,7 @@ span.math.inline {
   font-size: 27px;
   vertical-align: baseline !important;
 }
+
+div.svelte-15lo0d8 > *, div.svelte-15lo0d8 > .form > * {
+  flex-wrap: nowrap;
+}

extensions/gallery/script.py

@@ -2,9 +2,8 @@ from pathlib import Path
 
 import gradio as gr
 
-from modules.chat import load_character
 from modules.html_generator import get_image_cache
-from modules.shared import gradio, settings
+from modules.shared import gradio
 
 
 def generate_css():
@@ -64,7 +63,7 @@ def generate_html():
     for file in sorted(Path("characters").glob("*")):
         if file.suffix in [".json", ".yml", ".yaml"]:
             character = file.stem
-            container_html = f'<div class="character-container">'
+            container_html = '<div class="character-container">'
             image_html = "<div class='placeholder'></div>"
 
             for i in [
@@ -75,11 +74,8 @@ def generate_html():
 
                 path = Path(i)
                 if path.exists():
-                    try:
+                    image_html = f'<img src="file/{get_image_cache(path)}">'
-                        image_html = f'<img src="file/{get_image_cache(path)}">'
+                    break
-                        break
-                    except:
-                        continue
 
             container_html += f'{image_html} <span class="character-name">{character}</span>'
             container_html += "</div>"

modules/GPTQ_loader.py

@@ -15,7 +15,7 @@ from modelutils import find_layers
 from quant import make_quant
 
 
-def _load_quant(model, checkpoint, wbits, groupsize=-1, faster_kernel=False, exclude_layers=['lm_head'], kernel_switch_threshold=128):
+def _load_quant(model, checkpoint, wbits, groupsize=-1, exclude_layers=['lm_head']):
     config = AutoConfig.from_pretrained(model)
     def noop(*args, **kwargs):
         pass
@@ -33,16 +33,16 @@ def _load_quant(model, checkpoint, wbits, groupsize=-1, faster_kernel=False, exc
     for name in exclude_layers:
         if name in layers:
             del layers[name]
-    make_quant(model, layers, wbits, groupsize, faster=faster_kernel, kernel_switch_threshold=kernel_switch_threshold)
+    make_quant(model, layers, wbits, groupsize)
 
     del layers
 
     print('Loading model ...')
     if checkpoint.endswith('.safetensors'):
         from safetensors.torch import load_file as safe_load
-        model.load_state_dict(safe_load(checkpoint))
+        model.load_state_dict(safe_load(checkpoint), strict = False)
     else:
-        model.load_state_dict(torch.load(checkpoint))
+        model.load_state_dict(torch.load(checkpoint), strict = False)
     model.seqlen = 2048
     print('Done.')
 
@@ -52,7 +52,7 @@ def load_quantized(model_name):
     if not shared.args.model_type:
         # Try to determine model type from model name
         name = model_name.lower()
-        if any((k in name for k in ['llama', 'alpaca'])):
+        if any((k in name for k in ['llama', 'alpaca', 'vicuna'])):
             model_type = 'llama'
         elif any((k in name for k in ['opt-', 'galactica'])):
             model_type = 'opt'
@@ -74,7 +74,7 @@ def load_quantized(model_name):
         exit()
 
     # Now we are going to try to locate the quantized model file.
-    path_to_model = Path(f'models/{model_name}')
+    path_to_model = Path(f'{shared.args.model_dir}/{model_name}')
     found_pts = list(path_to_model.glob("*.pt"))
     found_safetensors = list(path_to_model.glob("*.safetensors"))
     pt_path = None
@@ -95,8 +95,8 @@ def load_quantized(model_name):
         else:
             pt_model = f'{model_name}-{shared.args.wbits}bit'
 
-        # Try to find the .safetensors or .pt both in models/ and in the subfolder
+        # Try to find the .safetensors or .pt both in the model dir and in the subfolder
-        for path in [Path(p+ext) for ext in ['.safetensors', '.pt'] for p in [f"models/{pt_model}", f"{path_to_model}/{pt_model}"]]:
+        for path in [Path(p+ext) for ext in ['.safetensors', '.pt'] for p in [f"{shared.args.model_dir}/{pt_model}", f"{path_to_model}/{pt_model}"]]:
             if path.exists():
                 print(f"Found {path}")
                 pt_path = path
@@ -110,8 +110,7 @@ def load_quantized(model_name):
     if shared.args.pre_layer:
         model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits, shared.args.groupsize, shared.args.pre_layer)
     else:
-        threshold = False if model_type == 'gptj' else 128
+        model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits, shared.args.groupsize)
-        model = load_quant(str(path_to_model), str(pt_path), shared.args.wbits, shared.args.groupsize, kernel_switch_threshold=threshold)
 
         # accelerate offload (doesn't work properly)
         if shared.args.gpu_memory:

modules/chat.py

@@ -12,14 +12,15 @@ from PIL import Image
 import modules.extensions as extensions_module
 import modules.shared as shared
 from modules.extensions import apply_extensions
-from modules.html_generator import fix_newlines, generate_chat_html
+from modules.html_generator import (fix_newlines, generate_chat_html,
+                                    make_thumbnail)
 from modules.text_generation import (encode, generate_reply,
                                      get_max_prompt_length)
 
 
-def generate_chat_output(history, name1, name2, character):
+def generate_chat_output(history, name1, name2):
     if shared.args.cai_chat:
-        return generate_chat_html(history, name1, name2, character)
+        return generate_chat_html(history, name1, name2)
     else:
         return history
 
@@ -180,22 +181,22 @@ def impersonate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
 
 def cai_chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, encoder_repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, seed, name1, name2, context, stop_at_newline, chat_prompt_size, chat_generation_attempts=1):
     for history in chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, encoder_repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, seed, name1, name2, context, stop_at_newline, chat_prompt_size, chat_generation_attempts):
-        yield generate_chat_html(history, name1, name2, shared.character)
+        yield generate_chat_html(history, name1, name2)
 
 def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, encoder_repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, seed, name1, name2, context, stop_at_newline, chat_prompt_size, chat_generation_attempts=1):
     if (shared.character != 'None' and len(shared.history['visible']) == 1) or len(shared.history['internal']) == 0:
-        yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+        yield generate_chat_output(shared.history['visible'], name1, name2)
     else:
         last_visible = shared.history['visible'].pop()
         last_internal = shared.history['internal'].pop()
         # Yield '*Is typing...*'
-        yield generate_chat_output(shared.history['visible']+[[last_visible[0], shared.processing_message]], name1, name2, shared.character)
+        yield generate_chat_output(shared.history['visible']+[[last_visible[0], shared.processing_message]], name1, name2)
         for history in chatbot_wrapper(last_internal[0], max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, encoder_repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, seed, name1, name2, context, stop_at_newline, chat_prompt_size, chat_generation_attempts, regenerate=True):
             if shared.args.cai_chat:
                 shared.history['visible'][-1] = [last_visible[0], history[-1][1]]
             else:
                 shared.history['visible'][-1] = (last_visible[0], history[-1][1])
-            yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+            yield generate_chat_output(shared.history['visible'], name1, name2)
 
 def remove_last_message(name1, name2):
     if len(shared.history['visible']) > 0 and shared.history['internal'][-1][0] != '<|BEGIN-VISIBLE-CHAT|>':
@@ -205,7 +206,7 @@ def remove_last_message(name1, name2):
         last = ['', '']
 
     if shared.args.cai_chat:
-        return generate_chat_html(shared.history['visible'], name1, name2, shared.character), last[0]
+        return generate_chat_html(shared.history['visible'], name1, name2), last[0]
     else:
         return shared.history['visible'], last[0]
 
@@ -223,10 +224,10 @@ def replace_last_reply(text, name1, name2):
             shared.history['visible'][-1] = (shared.history['visible'][-1][0], text)
         shared.history['internal'][-1][1] = apply_extensions(text, "input")
 
-    return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+    return generate_chat_output(shared.history['visible'], name1, name2)
 
 def clear_html():
-    return generate_chat_html([], "", "", shared.character)
+    return generate_chat_html([], "", "")
 
 def clear_chat_log(name1, name2, greeting):
     shared.history['visible'] = []
@@ -236,10 +237,10 @@ def clear_chat_log(name1, name2, greeting):
         shared.history['internal'] += [['<|BEGIN-VISIBLE-CHAT|>', greeting]]
         shared.history['visible'] += [['', apply_extensions(greeting, "output")]]
 
-    return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+    return generate_chat_output(shared.history['visible'], name1, name2)
 
 def redraw_html(name1, name2):
-    return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
+    return generate_chat_html(shared.history['visible'], name1, name2)
 
 def tokenize_dialogue(dialogue, name1, name2):
     history = []
@@ -326,13 +327,31 @@ def build_pygmalion_style_context(data):
     context = f"{context.strip()}\n<START>\n"
     return context
 
+def generate_pfp_cache(character):
+    cache_folder = Path("cache")
+    if not cache_folder.exists():
+        cache_folder.mkdir()
+
+    for path in [Path(f"characters/{character}.{extension}") for extension in ['png', 'jpg', 'jpeg']]:
+        if path.exists():
+            img = make_thumbnail(Image.open(path))
+            img.save(Path('cache/pfp_character.png'), format='PNG')
+            return img
+    return None
+
 def load_character(character, name1, name2):
     shared.character = character
     shared.history['internal'] = []
     shared.history['visible'] = []
     greeting = ""
+    picture = None
+
+    # Deleting the profile picture cache, if any
+    if Path("cache/pfp_character.png").exists():
+        Path("cache/pfp_character.png").unlink()
 
     if character != 'None':
+        picture = generate_pfp_cache(character)
         for extension in ["yml", "yaml", "json"]:
             filepath = Path(f'characters/{character}.{extension}')
             if filepath.exists():
@@ -371,9 +390,9 @@ def load_character(character, name1, name2):
         shared.history['visible'] += [['', apply_extensions(greeting, "output")]]
 
     if shared.args.cai_chat:
-        return name1, name2, greeting, context, generate_chat_html(shared.history['visible'], name1, name2, shared.character)
+        return name1, name2, picture, greeting, context, generate_chat_html(shared.history['visible'], name1, name2, reset_cache=True)
     else:
-        return name1, name2, greeting, context, shared.history['visible']
+        return name1, name2, picture, greeting, context, shared.history['visible']
 
 def load_default_history(name1, name2):
     load_character("None", name1, name2)
@@ -404,7 +423,20 @@ def upload_tavern_character(img, name1, name2):
     _json = {"char_name": _json['name'], "char_persona": _json['description'], "char_greeting": _json["first_mes"], "example_dialogue": _json['mes_example'], "world_scenario": _json['scenario']}
     return upload_character(json.dumps(_json), img, tavern=True)
 
-def upload_your_profile_picture(img):
+def upload_your_profile_picture(img, name1, name2):
-    img = Image.open(io.BytesIO(img))
+    cache_folder = Path("cache")
-    img.save(Path('img_me.png'))
+    if not cache_folder.exists():
-    print('Profile picture saved to "img_me.png"')
+        cache_folder.mkdir()
+
+    if img == None:
+        if Path("cache/pfp_me.png").exists():
+            Path("cache/pfp_me.png").unlink()
+    else:
+        img = make_thumbnail(img)
+        img.save(Path('cache/pfp_me.png'))
+        print('Profile picture saved to "cache/pfp_me.png"')
+
+    if shared.args.cai_chat:
+        return generate_chat_html(shared.history['visible'], name1, name2, reset_cache=True)
+    else:
+        return shared.history['visible']

modules/html_generator.py

@@ -6,10 +6,11 @@ This is a library for formatting text outputs as nice HTML.
 
 import os
 import re
+import time
 from pathlib import Path
 
 import markdown
-from PIL import Image
+from PIL import Image, ImageOps
 
 # This is to store the paths to the thumbnails of the profile pictures
 image_cache = {}
@@ -95,6 +96,13 @@ def generate_4chan_html(f):
 
     return output
 
+def make_thumbnail(image):
+    image = image.resize((350, round(image.size[1]/image.size[0]*350)), Image.Resampling.LANCZOS)
+    if image.size[1] > 470:
+        image = ImageOps.fit(image, (350, 470), Image.ANTIALIAS)
+
+    return image
+
 def get_image_cache(path):
     cache_folder = Path("cache")
     if not cache_folder.exists():
@@ -102,26 +110,20 @@ def get_image_cache(path):
 
     mtime = os.stat(path).st_mtime
     if (path in image_cache and mtime != image_cache[path][0]) or (path not in image_cache):
-        img = Image.open(path)
+        img = make_thumbnail(Image.open(path))
-        img.thumbnail((200, 200))
         output_file = Path(f'cache/{path.name}_cache.png')
         img.convert('RGB').save(output_file, format='PNG')
         image_cache[path] = [mtime, output_file.as_posix()]
 
     return image_cache[path][1]
 
-def load_html_image(paths):
+def generate_chat_html(history, name1, name2, reset_cache=False):
-    for str_path in paths:
-          path = Path(str_path)
-          if path.exists():
-              return f'<img src="file/{get_image_cache(path)}">'
-    return ''
-
-def generate_chat_html(history, name1, name2, character):
     output = f'<style>{cai_css}</style><div class="chat" id="chat">'
 
-    img_bot = load_html_image([f"characters/{character}.{ext}" for ext in ['png', 'jpg', 'jpeg']] + ["img_bot.png","img_bot.jpg","img_bot.jpeg"])
+    # The time.time() is to prevent the brower from caching the image
-    img_me = load_html_image(["img_me.png", "img_me.jpg", "img_me.jpeg"])
+    suffix = f"?{time.time()}" if reset_cache else ''
+    img_bot = f'<img src="file/cache/pfp_character.png{suffix}">' if Path("cache/pfp_character.png").exists() else ''
+    img_me = f'<img src="file/cache/pfp_me.png{suffix}">' if Path("cache/pfp_me.png").exists() else ''
 
     for i,_row in enumerate(history[::-1]):
         row = [convert_to_markdown(entry) for entry in _row]

modules/models.py

@@ -42,7 +42,7 @@ def load_model(model_name):
     t0 = time.time()
 
     shared.is_RWKV = 'rwkv-' in model_name.lower()
-    shared.is_llamacpp = len(list(Path(f'models/{model_name}').glob('ggml*.bin'))) > 0
+    shared.is_llamacpp = len(list(Path(f'{shared.args.model_dir}/{model_name}').glob('ggml*.bin'))) > 0
 
     # Default settings
     if not any([shared.args.cpu, shared.args.load_in_8bit, shared.args.wbits, shared.args.auto_devices, shared.args.disk, shared.args.gpu_memory is not None, shared.args.cpu_memory is not None, shared.args.deepspeed, shared.args.flexgen, shared.is_RWKV, shared.is_llamacpp]):
@@ -105,7 +105,7 @@ def load_model(model_name):
     elif shared.is_llamacpp:
         from modules.llamacpp_model import LlamaCppModel
 
-        model_file = list(Path(f'models/{model_name}').glob('ggml*.bin'))[0]
+        model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('ggml*.bin'))[0]
         print(f"llama.cpp weights detected: {model_file}\n")
 
         model, tokenizer = LlamaCppModel.from_pretrained(model_file)

modules/shared.py

@@ -74,7 +74,7 @@ parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpForma
 # Basic settings
 parser.add_argument('--notebook', action='store_true', help='Launch the web UI in notebook mode, where the output is written to the same text box as the input.')
 parser.add_argument('--chat', action='store_true', help='Launch the web UI in chat mode.')
-parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI in chat mode with a style similar to Character.AI\'s. If the file img_bot.png or img_bot.jpg exists in the same folder as server.py, this image will be used as the bot\'s profile picture. Similarly, img_me.png or img_me.jpg will be used as your profile picture.')
+parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI in chat mode with a style similar to the Character.AI website.')
 parser.add_argument('--model', type=str, help='Name of the model to load by default.')
 parser.add_argument('--lora', type=str, help='Name of the LoRA to apply to the model by default.')
 parser.add_argument("--model-dir", type=str, default='models/', help="Path to directory with all the models")

requirements.txt

@@ -13,4 +13,4 @@ safetensors==0.3.0
 sentencepiece
 pyyaml
 tqdm
-git+https://github.com/huggingface/transformers
+git+https://github.com/huggingface/transformers@9eae4aa57650c1dbe1becd4e0979f6ad1e572ac0

server.py

@@ -8,6 +8,7 @@ from datetime import datetime
 from pathlib import Path
 
 import gradio as gr
+from PIL import Image
 
 import modules.extensions as extensions_module
 from modules import chat, shared, training, ui
@@ -296,7 +297,7 @@ def create_interface():
             shared.gradio['Chat input'] = gr.State()
             with gr.Tab("Text generation", elem_id="main"):
                 if shared.args.cai_chat:
-                    shared.gradio['display'] = gr.HTML(value=generate_chat_html(shared.history['visible'], shared.settings['name1'], shared.settings['name2'], shared.character))
+                    shared.gradio['display'] = gr.HTML(value=generate_chat_html(shared.history['visible'], shared.settings['name1'], shared.settings['name2']))
                 else:
                     shared.gradio['display'] = gr.Chatbot(value=shared.history['visible'], elem_id="gradio-chatbot")
                 shared.gradio['textbox'] = gr.Textbox(label='Input')
@@ -316,10 +317,15 @@ def create_interface():
                     shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False)
 
             with gr.Tab("Character", elem_id="chat-settings"):
-                shared.gradio['name1'] = gr.Textbox(value=shared.settings['name1'], lines=1, label='Your name')
+                with gr.Row():
-                shared.gradio['name2'] = gr.Textbox(value=shared.settings['name2'], lines=1, label='Character\'s name')
+                    with gr.Column(scale=8):
-                shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=2, label='Greeting')
+                        shared.gradio['name1'] = gr.Textbox(value=shared.settings['name1'], lines=1, label='Your name')
-                shared.gradio['context'] = gr.Textbox(value=shared.settings['context'], lines=8, label='Context')
+                        shared.gradio['name2'] = gr.Textbox(value=shared.settings['name2'], lines=1, label='Character\'s name')
+                        shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=2, label='Greeting')
+                        shared.gradio['context'] = gr.Textbox(value=shared.settings['context'], lines=8, label='Context')
+                    with gr.Column(scale=1):
+                        shared.gradio['character_picture'] = gr.Image(label='Character picture', type="pil")
+                        shared.gradio['your_picture'] = gr.Image(label='Your picture', type="pil", value=Image.open(Path("cache/pfp_me.png")) if Path("cache/pfp_me.png").exists() else None)
                 with gr.Row():
                     shared.gradio['character_menu'] = gr.Dropdown(choices=available_characters, value='None', label='Character', elem_id='character-menu')
                     ui.create_refresh_button(shared.gradio['character_menu'], lambda : None, lambda : {'choices': get_available_characters()}, 'refresh-button')
@@ -347,8 +353,6 @@ def create_interface():
 
                         gr.Markdown("# TavernAI PNG format")
                         shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
-                    with gr.Tab('Upload your profile picture'):
-                        shared.gradio['upload_img_me'] = gr.File(type='binary', file_types=['image'])
 
             with gr.Tab("Parameters", elem_id="parameters"):
                 with gr.Box():
@@ -399,15 +403,14 @@ def create_interface():
             shared.gradio['textbox'].submit(lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False)
             shared.gradio['textbox'].submit(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
 
-            shared.gradio['character_menu'].change(chat.load_character, [shared.gradio[k] for k in ['character_menu', 'name1', 'name2']], [shared.gradio[k] for k in ['name1', 'name2', 'greeting', 'context', 'display']])
+            shared.gradio['character_menu'].change(chat.load_character, [shared.gradio[k] for k in ['character_menu', 'name1', 'name2']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'display']])
             shared.gradio['upload_chat_history'].upload(chat.load_history, [shared.gradio['upload_chat_history'], shared.gradio['name1'], shared.gradio['name2']], [])
             shared.gradio['upload_img_tavern'].upload(chat.upload_tavern_character, [shared.gradio['upload_img_tavern'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['character_menu']])
-            shared.gradio['upload_img_me'].upload(chat.upload_your_profile_picture, [shared.gradio['upload_img_me']], [])
+            shared.gradio['your_picture'].change(chat.upload_your_profile_picture, [shared.gradio[k] for k in ['your_picture', 'name1', 'name2']], shared.gradio['display'])
 
             reload_func = chat.redraw_html if shared.args.cai_chat else lambda : shared.history['visible']
             reload_inputs = [shared.gradio['name1'], shared.gradio['name2']] if shared.args.cai_chat else []
             shared.gradio['upload_chat_history'].upload(reload_func, reload_inputs, [shared.gradio['display']])
-            shared.gradio['upload_img_me'].upload(reload_func, reload_inputs, [shared.gradio['display']])
             shared.gradio['Stop'].click(reload_func, reload_inputs, [shared.gradio['display']])
 
             shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js+ui.chat_js}}}")