{name2}
'
+ output += f''
@@ -208,135 +110,39 @@ def get_image_cache(path):
return image_cache[path][1]
+def load_html_image(paths):
+ for str_path in paths:
+ path = Path(str_path)
+ if path.exists():
+ return f'})
'
+ return ''
+
def generate_chat_html(history, name1, name2, character):
- css = """
- .chat {
- margin-left: auto;
- margin-right: auto;
- max-width: 800px;
- height: 66.67vh;
- overflow-y: auto;
- padding-right: 20px;
- display: flex;
- flex-direction: column-reverse;
- }
-
- .message {
- display: grid;
- grid-template-columns: 60px 1fr;
- padding-bottom: 25px;
- font-size: 15px;
- font-family: Helvetica, Arial, sans-serif;
- line-height: 1.428571429;
- }
-
- .circle-you {
- width: 50px;
- height: 50px;
- background-color: rgb(238, 78, 59);
- border-radius: 50%;
- }
-
- .circle-bot {
- width: 50px;
- height: 50px;
- background-color: rgb(59, 78, 244);
- border-radius: 50%;
- }
-
- .circle-bot img, .circle-you img {
- border-radius: 50%;
- width: 100%;
- height: 100%;
- object-fit: cover;
- }
-
- .text {
- }
-
- .text p {
- margin-top: 5px;
- }
-
- .username {
- font-weight: bold;
- }
-
- .message-body {
- }
-
- .message-body img {
- max-width: 300px;
- max-height: 300px;
- border-radius: 20px;
- }
-
- .message-body p {
- margin-bottom: 0 !important;
- font-size: 15px !important;
- line-height: 1.428571429 !important;
- }
-
- .dark .message-body p em {
- color: rgb(138, 138, 138) !important;
- }
-
- .message-body p em {
- color: rgb(110, 110, 110) !important;
- }
-
- """
-
- output = ''
- output += f'
'
for post in posts:
output += post
output += '
'
- img = ''
-
- for i in [
- f"characters/{character}.png",
- f"characters/{character}.jpg",
- f"characters/{character}.jpeg",
- "img_bot.png",
- "img_bot.jpg",
- "img_bot.jpeg"
- ]:
-
- path = Path(i)
- if path.exists():
- img = f''
- break
-
- img_me = ''
- for i in ["img_me.png", "img_me.jpg", "img_me.jpeg"]:
- path = Path(i)
- if path.exists():
- img_me = f''
- break
+ output = f'
'
+
+ img_bot = load_html_image([f"characters/{character}.{ext}" for ext in ['png', 'jpg', 'jpeg']] + ["img_bot.png","img_bot.jpg","img_bot.jpeg"])
+ img_me = load_html_image(["img_me.png", "img_me.jpg", "img_me.jpeg"])
for i,_row in enumerate(history[::-1]):
- row = _row.copy()
- row[0] = re.sub(r"(\*\*)([^\*\n]*)(\*\*)", r"\2", row[0])
- row[1] = re.sub(r"(\*\*)([^\*\n]*)(\*\*)", r"\2", row[1])
- row[0] = re.sub(r"(\*)([^\*\n]*)(\*)", r"\2", row[0])
- row[1] = re.sub(r"(\*)([^\*\n]*)(\*)", r"\2", row[1])
- p = '\n'.join([f"
diff --git a/modules/models.py b/modules/models.py
index f4bb11fd..f07e738b 100644
--- a/modules/models.py
+++ b/modules/models.py
@@ -7,7 +7,9 @@ from pathlib import Path
import numpy as np
import torch
import transformers
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from accelerate import infer_auto_device_map, init_empty_weights
+from transformers import (AutoConfig, AutoModelForCausalLM, AutoTokenizer,
+ BitsAndBytesConfig)
import modules.shared as shared
@@ -16,8 +18,7 @@ transformers.logging.set_verbosity_error()
local_rank = None
if shared.args.flexgen:
- from flexgen.flex_opt import (CompressionConfig, ExecutionEnv, OptLM,
- Policy, str2bool)
+ from flexgen.flex_opt import CompressionConfig, ExecutionEnv, OptLM, Policy
if shared.args.deepspeed:
import deepspeed
@@ -46,7 +47,12 @@ def load_model(model_name):
if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')):
model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
else:
- model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), low_cpu_mem_usage=True, torch_dtype=torch.bfloat16 if shared.args.bf16 else torch.float16).cuda()
+ model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), low_cpu_mem_usage=True, torch_dtype=torch.bfloat16 if shared.args.bf16 else torch.float16)
+ if torch.has_mps:
+ device = torch.device('mps')
+ model = model.to(device)
+ else:
+ model = model.cuda()
# FlexGen
elif shared.args.flexgen:
@@ -95,39 +101,60 @@ def load_model(model_name):
# Custom
else:
- command = "AutoModelForCausalLM.from_pretrained"
- params = ["low_cpu_mem_usage=True"]
- if not shared.args.cpu and not torch.cuda.is_available():
- print("Warning: no GPU has been detected.\nFalling back to CPU mode.\n")
+ params = {"low_cpu_mem_usage": True}
+ if not any((shared.args.cpu, torch.cuda.is_available(), torch.has_mps)):
+ print("Warning: torch.cuda.is_available() returned False.\nThis means that no GPU has been detected.\nFalling back to CPU mode.\n")
shared.args.cpu = True
if shared.args.cpu:
- params.append("low_cpu_mem_usage=True")
- params.append("torch_dtype=torch.float32")
+ params["torch_dtype"] = torch.float32
else:
- params.append("device_map='auto'")
- params.append("load_in_8bit=True" if shared.args.load_in_8bit else "torch_dtype=torch.bfloat16" if shared.args.bf16 else "torch_dtype=torch.float16")
+ params["device_map"] = 'auto'
+ if shared.args.load_in_8bit and any((shared.args.auto_devices, shared.args.gpu_memory)):
+ params['quantization_config'] = BitsAndBytesConfig(load_in_8bit=True, llm_int8_enable_fp32_cpu_offload=True)
+ elif shared.args.load_in_8bit:
+ params['quantization_config'] = BitsAndBytesConfig(load_in_8bit=True)
+ elif shared.args.bf16:
+ params["torch_dtype"] = torch.bfloat16
+ else:
+ params["torch_dtype"] = torch.float16
if shared.args.gpu_memory:
memory_map = shared.args.gpu_memory
- max_memory = f"max_memory={{0: '{memory_map[0]}GiB'"
- for i in range(1, len(memory_map)):
- max_memory += (f", {i}: '{memory_map[i]}GiB'")
- max_memory += (f", 'cpu': '{shared.args.cpu_memory or '99'}GiB'}}")
- params.append(max_memory)
- elif not shared.args.load_in_8bit:
- total_mem = (torch.cuda.get_device_properties(0).total_memory/(1024*1024))
- suggestion = round((total_mem-1000)/1000)*1000
- if total_mem-suggestion < 800:
+ max_memory = {}
+ for i in range(len(memory_map)):
+ max_memory[i] = f'{memory_map[i]}GiB'
+ max_memory['cpu'] = f'{shared.args.cpu_memory or 99}GiB'
+ params['max_memory'] = max_memory
+ elif shared.args.auto_devices:
+ total_mem = (torch.cuda.get_device_properties(0).total_memory / (1024*1024))
+ suggestion = round((total_mem-1000) / 1000) * 1000
+ if total_mem - suggestion < 800:
suggestion -= 1000
suggestion = int(round(suggestion/1000))
print(f"\033[1;32;1mAuto-assiging --gpu-memory {suggestion} for your GPU to try to prevent out-of-memory errors.\nYou can manually set other values.\033[0;37;0m")
- params.append(f"max_memory={{0: '{suggestion}GiB', 'cpu': '{shared.args.cpu_memory or '99'}GiB'}}")
- if shared.args.disk:
- params.append(f"offload_folder='{shared.args.disk_cache_dir}'")
+
+ max_memory = {0: f'{suggestion}GiB', 'cpu': f'{shared.args.cpu_memory or 99}GiB'}
+ params['max_memory'] = max_memory
- command = f"{command}(Path(f'models/{shared.model_name}'), {', '.join(set(params))})"
- model = eval(command)
+ if shared.args.disk:
+ params["offload_folder"] = shared.args.disk_cache_dir
+
+ checkpoint = Path(f'models/{shared.model_name}')
+
+ if shared.args.load_in_8bit and params.get('max_memory', None) is not None and params['device_map'] == 'auto':
+ config = AutoConfig.from_pretrained(checkpoint)
+ with init_empty_weights():
+ model = AutoModelForCausalLM.from_config(config)
+ model.tie_weights()
+ params['device_map'] = infer_auto_device_map(
+ model,
+ dtype=torch.int8,
+ max_memory=params['max_memory'],
+ no_split_module_classes = model._no_split_modules
+ )
+
+ model = AutoModelForCausalLM.from_pretrained(checkpoint, **params)
# Loading the tokenizer
if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')) and Path("models/gpt-j-6B/").exists():
diff --git a/modules/shared.py b/modules/shared.py
index ea2eb50b..e3920f22 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -2,7 +2,8 @@ import argparse
model = None
tokenizer = None
-model_name = ""
+model_name = "None"
+lora_name = "None"
soft_prompt_tensor = None
soft_prompt = False
is_RWKV = False
@@ -19,6 +20,9 @@ gradio = {}
# Generation input parameters
input_params = []
+# For restarting the interface
+need_restart = False
+
settings = {
'max_new_tokens': 200,
'max_new_tokens_min': 1,
@@ -26,7 +30,7 @@ settings = {
'name1': 'Person 1',
'name2': 'Person 2',
'context': 'This is a conversation between two people.',
- 'stop_at_newline': True,
+ 'stop_at_newline': False,
'chat_prompt_size': 2048,
'chat_prompt_size_min': 0,
'chat_prompt_size_max': 2048,
@@ -49,6 +53,10 @@ settings = {
'^(gpt4chan|gpt-4chan|4chan)': '-----\n--- 865467536\nInput text\n--- 865467537\n',
'(rosey|chip|joi)_.*_instruct.*': 'User: \n',
'oasst-*': '<|prompter|>Write a story about future of AI development<|endoftext|><|assistant|>'
+ },
+ 'lora_prompts': {
+ 'default': 'Common sense questions and answers\n\nQuestion: \nFactual answer:',
+ '(alpaca-lora-7b|alpaca-lora-13b|alpaca-lora-30b)': "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\nWrite a poem about the transformers Python library. \nMention the word \"large language models\" in that poem.\n### Response:\n"
}
}
@@ -64,6 +72,7 @@ def str2bool(v):
parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog,max_help_position=54))
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('--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.')
diff --git a/modules/text_generation.py b/modules/text_generation.py
index 70a51d91..1d11de12 100644
--- a/modules/text_generation.py
+++ b/modules/text_generation.py
@@ -33,12 +33,15 @@ def encode(prompt, tokens_to_generate=0, add_special_tokens=True):
return input_ids.numpy()
elif shared.args.deepspeed:
return input_ids.to(device=local_rank)
+ elif torch.has_mps:
+ device = torch.device('mps')
+ return input_ids.to(device)
else:
return input_ids.cuda()
def decode(output_ids):
# Open Assistant relies on special tokens like <|endoftext|>
- if re.match('oasst-*', shared.model_name.lower()):
+ if re.match('(oasst|galactica)-*', shared.model_name.lower()):
return shared.tokenizer.decode(output_ids, skip_special_tokens=False)
else:
reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
@@ -89,7 +92,7 @@ def clear_torch_cache():
if not shared.args.cpu:
torch.cuda.empty_cache()
-def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=None, stopping_string=None):
+def generate_reply(question, 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, eos_token=None, stopping_string=None):
clear_torch_cache()
t0 = time.time()
@@ -101,7 +104,8 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
reply = shared.model.generate(context=question, token_count=max_new_tokens, temperature=temperature, top_p=top_p, top_k=top_k)
yield formatted_outputs(reply, shared.model_name)
else:
- yield formatted_outputs(question, shared.model_name)
+ if not (shared.args.chat or shared.args.cai_chat):
+ yield formatted_outputs(question, shared.model_name)
# RWKV has proper streaming, which is very nice.
# No need to generate 8 tokens at a time.
for reply in shared.model.generate_with_streaming(context=question, token_count=max_new_tokens, temperature=temperature, top_p=top_p, top_k=top_k):
@@ -143,6 +147,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
"top_p": top_p,
"typical_p": typical_p,
"repetition_penalty": repetition_penalty,
+ "encoder_repetition_penalty": encoder_repetition_penalty,
"top_k": top_k,
"min_length": min_length if shared.args.no_stream else 0,
"no_repeat_ngram_size": no_repeat_ngram_size,
@@ -196,7 +201,8 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
def generate_with_streaming(**kwargs):
return Iteratorize(generate_with_callback, kwargs, callback=None)
- yield formatted_outputs(original_question, shared.model_name)
+ if not (shared.args.chat or shared.args.cai_chat):
+ yield formatted_outputs(original_question, shared.model_name)
with generate_with_streaming(**generate_params) as generator:
for output in generator:
if shared.soft_prompt:
diff --git a/modules/ui.py b/modules/ui.py
index bb193e35..80bd7c1c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1,68 +1,17 @@
+from pathlib import Path
+
import gradio as gr
refresh_symbol = '\U0001f504' # 🔄
-css = """
-.tabs.svelte-710i53 {
- margin-top: 0
-}
-.py-6 {
- padding-top: 2.5rem
-}
-.dark #refresh-button {
- background-color: #ffffff1f;
-}
-#refresh-button {
- flex: none;
- margin: 0;
- padding: 0;
- min-width: 50px;
- border: none;
- box-shadow: none;
- border-radius: 10px;
- background-color: #0000000d;
-}
-#download-label, #upload-label {
- min-height: 0
-}
-#accordion {
-}
-.dark svg {
- fill: white;
-}
-svg {
- display: unset !important;
- vertical-align: middle !important;
- margin: 5px;
-}
-ol li p, ul li p {
- display: inline-block;
-}
-"""
-
-chat_css = """
-.h-\[40vh\], .wrap.svelte-byatnx.svelte-byatnx.svelte-byatnx {
- height: 66.67vh
-}
-.gradio-container {
- max-width: 800px !important;
- margin-left: auto !important;
- margin-right: auto !important;
-}
-.w-screen {
- width: unset
-}
-div.svelte-362y77>*, div.svelte-362y77>.form>* {
- flex-wrap: nowrap
-}
-/* fixes the API documentation in chat mode */
-.api-docs.svelte-1iguv9h.svelte-1iguv9h.svelte-1iguv9h {
- display: grid;
-}
-.pending.svelte-1ed2p3z {
- opacity: 1;
-}
-"""
+with open(Path(__file__).resolve().parent / '../css/main.css', 'r') as f:
+ css = f.read()
+with open(Path(__file__).resolve().parent / '../css/chat.css', 'r') as f:
+ chat_css = f.read()
+with open(Path(__file__).resolve().parent / '../css/main.js', 'r') as f:
+ main_js = f.read()
+with open(Path(__file__).resolve().parent / '../css/chat.js', 'r') as f:
+ chat_js = f.read()
class ToolButton(gr.Button, gr.components.FormComponent):
"""Small button with single emoji as text, fits inside gradio forms"""
diff --git a/presets/Default.txt b/presets/Default.txt
index 9f0983ec..d5283836 100644
--- a/presets/Default.txt
+++ b/presets/Default.txt
@@ -1,12 +1,7 @@
do_sample=True
-temperature=1
-top_p=1
-typical_p=1
-repetition_penalty=1
-top_k=50
-num_beams=1
-penalty_alpha=0
-min_length=0
-length_penalty=1
-no_repeat_ngram_size=0
+top_p=0.5
+top_k=40
+temperature=0.7
+repetition_penalty=1.2
+typical_p=1.0
early_stopping=False
diff --git a/presets/Individual Today.txt b/presets/Individual Today.txt
deleted file mode 100644
index f40b879c..00000000
--- a/presets/Individual Today.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-do_sample=True
-top_p=0.9
-top_k=50
-temperature=1.39
-repetition_penalty=1.08
-typical_p=0.2
diff --git a/requirements.txt b/requirements.txt
index 9bb2b74f..e5b3de69 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,10 +2,12 @@ accelerate==0.17.1
bitsandbytes==0.37.1
flexgen==0.1.7
gradio==3.18.0
+markdown
numpy
+peft==0.2.0
requests
-rwkv==0.4.2
+rwkv==0.7.0
safetensors==0.3.0
sentencepiece
tqdm
-git+https://github.com/zphang/transformers.git@68d640f7c368bcaaaecfc678f11908ebbd3d6176
+git+https://github.com/huggingface/transformers
diff --git a/server.py b/server.py
index a54e3b62..060f09d5 100644
--- a/server.py
+++ b/server.py
@@ -15,6 +15,7 @@ import modules.extensions as extensions_module
import modules.shared as shared
import modules.ui as ui
from modules.html_generator import generate_chat_html
+from modules.LoRA import add_lora_to_model
from modules.models import load_model, load_soft_prompt
from modules.text_generation import generate_reply
@@ -34,7 +35,7 @@ def get_available_models():
if shared.args.flexgen:
return sorted([re.sub('-np$', '', item.name) for item in list(Path('models/').glob('*')) if item.name.endswith('-np')], key=str.lower)
else:
- return sorted([item.name for item in list(Path('models/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt'))], key=str.lower)
+ return sorted([re.sub('.pth$', '', item.name) for item in list(Path('models/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
def get_available_presets():
return sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('presets').glob('*.txt'))), key=str.lower)
@@ -48,6 +49,9 @@ def get_available_extensions():
def get_available_softprompts():
return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower)
+def get_available_loras():
+ return ['None'] + sorted([item.name for item in list(Path('loras/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
+
def load_model_wrapper(selected_model):
if selected_model != shared.model_name:
shared.model_name = selected_model
@@ -59,6 +63,17 @@ def load_model_wrapper(selected_model):
return selected_model
+def load_lora_wrapper(selected_lora):
+ shared.lora_name = selected_lora
+ default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
+
+ if not shared.args.cpu:
+ gc.collect()
+ torch.cuda.empty_cache()
+ add_lora_to_model(selected_lora)
+
+ return selected_lora, default_text
+
def load_preset_values(preset_menu, return_dict=False):
generate_params = {
'do_sample': True,
@@ -66,6 +81,7 @@ def load_preset_values(preset_menu, return_dict=False):
'top_p': 1,
'typical_p': 1,
'repetition_penalty': 1,
+ 'encoder_repetition_penalty': 1,
'top_k': 50,
'num_beams': 1,
'penalty_alpha': 0,
@@ -86,7 +102,7 @@ def load_preset_values(preset_menu, return_dict=False):
if return_dict:
return generate_params
else:
- return generate_params['do_sample'], generate_params['temperature'], generate_params['top_p'], generate_params['typical_p'], generate_params['repetition_penalty'], generate_params['top_k'], generate_params['min_length'], generate_params['no_repeat_ngram_size'], generate_params['num_beams'], generate_params['penalty_alpha'], generate_params['length_penalty'], generate_params['early_stopping']
+ return preset_menu, generate_params['do_sample'], generate_params['temperature'], generate_params['top_p'], generate_params['typical_p'], generate_params['repetition_penalty'], generate_params['encoder_repetition_penalty'], generate_params['top_k'], generate_params['min_length'], generate_params['no_repeat_ngram_size'], generate_params['num_beams'], generate_params['penalty_alpha'], generate_params['length_penalty'], generate_params['early_stopping']
def upload_soft_prompt(file):
with zipfile.ZipFile(io.BytesIO(file)) as zf:
@@ -100,9 +116,7 @@ def upload_soft_prompt(file):
return name
-def create_settings_menus(default_preset):
- generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True)
-
+def create_model_and_preset_menus():
with gr.Row():
with gr.Column():
with gr.Row():
@@ -113,31 +127,48 @@ def create_settings_menus(default_preset):
shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
ui.create_refresh_button(shared.gradio['preset_menu'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')
- with gr.Accordion('Custom generation parameters', open=False, elem_id='accordion'):
- with gr.Row():
- with gr.Column():
- shared.gradio['temperature'] = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label='temperature')
- shared.gradio['repetition_penalty'] = gr.Slider(1.0, 2.99, value=generate_params['repetition_penalty'],step=0.01,label='repetition_penalty')
- shared.gradio['top_k'] = gr.Slider(0,200,value=generate_params['top_k'],step=1,label='top_k')
- shared.gradio['top_p'] = gr.Slider(0.0,1.0,value=generate_params['top_p'],step=0.01,label='top_p')
- with gr.Column():
+def create_settings_menus(default_preset):
+ generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', return_dict=True)
+
+ with gr.Row():
+ shared.gradio['preset_menu_mirror'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
+ ui.create_refresh_button(shared.gradio['preset_menu_mirror'], lambda : None, lambda : {'choices': get_available_presets()}, 'refresh-button')
+
+ with gr.Row():
+ with gr.Column():
+ with gr.Box():
+ gr.Markdown('Custom generation parameters ([reference](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig))')
+ with gr.Row():
+ with gr.Column():
+ shared.gradio['temperature'] = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label='temperature')
+ shared.gradio['top_p'] = gr.Slider(0.0,1.0,value=generate_params['top_p'],step=0.01,label='top_p')
+ shared.gradio['top_k'] = gr.Slider(0,200,value=generate_params['top_k'],step=1,label='top_k')
+ shared.gradio['typical_p'] = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label='typical_p')
+ with gr.Column():
+ shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'],step=0.01,label='repetition_penalty')
+ shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'],step=0.01,label='encoder_repetition_penalty')
+ shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size')
+ shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'] if shared.args.no_stream else 0, label='min_length', interactive=shared.args.no_stream)
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
- shared.gradio['typical_p'] = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label='typical_p')
- shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size')
- shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'] if shared.args.no_stream else 0, label='min_length', interactive=shared.args.no_stream)
+ with gr.Column():
+ with gr.Box():
+ gr.Markdown('Contrastive search')
+ shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')
- gr.Markdown('Contrastive search:')
- shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')
+ with gr.Box():
+ gr.Markdown('Beam search (uses a lot of VRAM)')
+ with gr.Row():
+ with gr.Column():
+ shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
+ with gr.Column():
+ shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
+ shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
- gr.Markdown('Beam search (uses a lot of VRAM):')
- with gr.Row():
- with gr.Column():
- shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
- with gr.Column():
- shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
- shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
+ with gr.Row():
+ shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA')
+ ui.create_refresh_button(shared.gradio['lora_menu'], lambda : None, lambda : {'choices': get_available_loras()}, 'refresh-button')
- with gr.Accordion('Soft prompt', open=False, elem_id='accordion'):
+ with gr.Accordion('Soft prompt', open=False):
with gr.Row():
shared.gradio['softprompts_menu'] = gr.Dropdown(choices=available_softprompts, value='None', label='Soft prompt')
ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda : None, lambda : {'choices': get_available_softprompts()}, 'refresh-button')
@@ -147,14 +178,35 @@ def create_settings_menus(default_preset):
shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True)
- shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio['do_sample'], shared.gradio['temperature'], shared.gradio['top_p'], shared.gradio['typical_p'], shared.gradio['repetition_penalty'], shared.gradio['top_k'], shared.gradio['min_length'], shared.gradio['no_repeat_ngram_size'], shared.gradio['num_beams'], shared.gradio['penalty_alpha'], shared.gradio['length_penalty'], shared.gradio['early_stopping']])
+ shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio[k] for k in ['preset_menu_mirror', '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']])
+ shared.gradio['preset_menu_mirror'].change(load_preset_values, [shared.gradio['preset_menu_mirror']], [shared.gradio[k] for k in ['preset_menu', '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']])
+ shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True)
shared.gradio['softprompts_menu'].change(load_soft_prompt, [shared.gradio['softprompts_menu']], [shared.gradio['softprompts_menu']], show_progress=True)
shared.gradio['upload_softprompt'].upload(upload_soft_prompt, [shared.gradio['upload_softprompt']], [shared.gradio['softprompts_menu']])
+def set_interface_arguments(interface_mode, extensions, cmd_active):
+ modes = ["default", "notebook", "chat", "cai_chat"]
+ cmd_list = vars(shared.args)
+ cmd_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes]
+
+ shared.args.extensions = extensions
+ for k in modes[1:]:
+ exec(f"shared.args.{k} = False")
+ if interface_mode != "default":
+ exec(f"shared.args.{interface_mode} = True")
+
+ for k in cmd_list:
+ exec(f"shared.args.{k} = False")
+ for k in cmd_active:
+ exec(f"shared.args.{k} = True")
+
+ shared.need_restart = True
+
available_models = get_available_models()
available_presets = get_available_presets()
available_characters = get_available_characters()
available_softprompts = get_available_softprompts()
+available_loras = get_available_loras()
# Default extensions
extensions_module.available_extensions = get_available_extensions()
@@ -168,8 +220,6 @@ else:
shared.args.extensions = shared.args.extensions or []
if extension not in shared.args.extensions:
shared.args.extensions.append(extension)
-if shared.args.extensions is not None and len(shared.args.extensions) > 0:
- extensions_module.load_extensions()
# Default model
if shared.args.model is not None:
@@ -189,191 +239,235 @@ else:
print()
shared.model_name = available_models[i]
shared.model, shared.tokenizer = load_model(shared.model_name)
+if shared.args.lora:
+ print(shared.args.lora)
+ shared.lora_name = shared.args.lora
+ add_lora_to_model(shared.lora_name)
# Default UI settings
-gen_events = []
default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
-default_text = shared.settings['prompts'][next((k for k in shared.settings['prompts'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
+default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
+if default_text == '':
+ default_text = shared.settings['prompts'][next((k for k in shared.settings['prompts'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
title ='Text generation web UI'
description = '\n\n# Text generation lab\nGenerate text using Large Language Models.\n'
suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''
-if shared.args.chat or shared.args.cai_chat:
- with gr.Blocks(css=ui.css+ui.chat_css, analytics_enabled=False, title=title) as shared.gradio['interface']:
- if shared.args.cai_chat:
- shared.gradio['display'] = gr.HTML(value=generate_chat_html(shared.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}'], shared.character))
- else:
- shared.gradio['display'] = gr.Chatbot(value=shared.history['visible']).style(color_map=("#326efd", "#212528"))
- shared.gradio['textbox'] = gr.Textbox(label='Input')
- with gr.Row():
- shared.gradio['Stop'] = gr.Button('Stop')
- shared.gradio['Generate'] = gr.Button('Generate')
- with gr.Row():
- shared.gradio['Impersonate'] = gr.Button('Impersonate')
- shared.gradio['Regenerate'] = gr.Button('Regenerate')
- with gr.Row():
- shared.gradio['Copy last reply'] = gr.Button('Copy last reply')
- shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
- shared.gradio['Remove last'] = gr.Button('Remove last')
+def create_interface():
- shared.gradio['Clear history'] = gr.Button('Clear history')
- shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant="stop", visible=False)
- shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False)
- with gr.Tab('Chat settings'):
- shared.gradio['name1'] = gr.Textbox(value=shared.settings[f'name1{suffix}'], lines=1, label='Your name')
- shared.gradio['name2'] = gr.Textbox(value=shared.settings[f'name2{suffix}'], lines=1, label='Bot\'s name')
- shared.gradio['context'] = gr.Textbox(value=shared.settings[f'context{suffix}'], lines=5, label='Context')
- 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')
+ gen_events = []
+ if shared.args.extensions is not None and len(shared.args.extensions) > 0:
+ extensions_module.load_extensions()
- with gr.Row():
- shared.gradio['check'] = gr.Checkbox(value=shared.settings[f'stop_at_newline{suffix}'], label='Stop generating at new line character?')
- with gr.Row():
- with gr.Tab('Chat history'):
- with gr.Row():
- with gr.Column():
- gr.Markdown('Upload')
- shared.gradio['upload_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'])
- with gr.Column():
- gr.Markdown('Download')
- shared.gradio['download'] = gr.File()
- shared.gradio['download_button'] = gr.Button(value='Click me')
- with gr.Tab('Upload character'):
- with gr.Row():
- with gr.Column():
- gr.Markdown('1. Select the JSON file')
- shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json'])
- with gr.Column():
- gr.Markdown('2. Select your character\'s profile picture (optional)')
- shared.gradio['upload_img_bot'] = gr.File(type='binary', file_types=['image'])
- shared.gradio['Upload character'] = gr.Button(value='Submit')
- with gr.Tab('Upload your profile picture'):
- shared.gradio['upload_img_me'] = gr.File(type='binary', file_types=['image'])
- with gr.Tab('Upload TavernAI Character Card'):
- shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
-
- with gr.Tab('Generation settings'):
- with gr.Row():
- with gr.Column():
- shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
- with gr.Column():
- shared.gradio['chat_prompt_size_slider'] = gr.Slider(minimum=shared.settings['chat_prompt_size_min'], maximum=shared.settings['chat_prompt_size_max'], step=1, label='Maximum prompt size in tokens', value=shared.settings['chat_prompt_size'])
- shared.gradio['chat_generation_attempts'] = gr.Slider(minimum=shared.settings['chat_generation_attempts_min'], maximum=shared.settings['chat_generation_attempts_max'], value=shared.settings['chat_generation_attempts'], step=1, label='Generation attempts (for longer replies)')
- create_settings_menus(default_preset)
-
- shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'name1', 'name2', 'context', 'check', 'chat_prompt_size_slider', 'chat_generation_attempts']]
- if shared.args.extensions is not None:
- with gr.Tab('Extensions'):
- extensions_module.create_extensions_block()
-
- function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
-
- gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
- gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
- gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
- gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream))
- shared.gradio['Stop'].click(chat.stop_everything_event, [], [], cancels=gen_events)
-
- shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, [], shared.gradio['textbox'], show_progress=shared.args.no_stream)
- shared.gradio['Replace last reply'].click(chat.replace_last_reply, [shared.gradio['textbox'], shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'], show_progress=shared.args.no_stream)
-
- # Clear history with confirmation
- clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
- shared.gradio['Clear history'].click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, clear_arr)
- shared.gradio['Clear history-confirm'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
- shared.gradio['Clear history-confirm'].click(chat.clear_chat_log, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
- shared.gradio['Clear history-cancel'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
-
- shared.gradio['Remove last'].click(chat.remove_last_message, [shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['display'], shared.gradio['textbox']], show_progress=False)
- shared.gradio['download_button'].click(chat.save_history, inputs=[], outputs=[shared.gradio['download']])
- shared.gradio['Upload character'].click(chat.upload_character, [shared.gradio['upload_json'], shared.gradio['upload_img_bot']], [shared.gradio['character_menu']])
-
- # Clearing stuff and saving the history
- for i in ['Generate', 'Regenerate', 'Replace last reply']:
- shared.gradio[i].click(lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False)
- shared.gradio[i].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
- shared.gradio['Clear history-confirm'].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
- 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['character_menu'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['name2'], shared.gradio['context'], shared.gradio['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']], [])
-
- 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(lambda : chat.load_default_history(shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}']), None, None)
- shared.gradio['interface'].load(reload_func, reload_inputs, [shared.gradio['display']], show_progress=True)
-
-elif shared.args.notebook:
- with gr.Blocks(css=ui.css, analytics_enabled=False, title=title) as shared.gradio['interface']:
- gr.Markdown(description)
- with gr.Tab('Raw'):
- shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=23)
- with gr.Tab('Markdown'):
- shared.gradio['markdown'] = gr.Markdown()
- with gr.Tab('HTML'):
- shared.gradio['html'] = gr.HTML()
-
- shared.gradio['Generate'] = gr.Button('Generate')
- shared.gradio['Stop'] = gr.Button('Stop')
- shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
-
- create_settings_menus(default_preset)
- if shared.args.extensions is not None:
- extensions_module.create_extensions_block()
-
- shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]
- output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
- gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
- gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
- shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
-
-else:
- with gr.Blocks(css=ui.css, analytics_enabled=False, title=title) as shared.gradio['interface']:
- gr.Markdown(description)
- with gr.Row():
- with gr.Column():
- shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=15, label='Input')
- shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
- shared.gradio['Generate'] = gr.Button('Generate')
+ with gr.Blocks(css=ui.css if not any((shared.args.chat, shared.args.cai_chat)) else ui.css+ui.chat_css, analytics_enabled=False, title=title) as shared.gradio['interface']:
+ if shared.args.chat or shared.args.cai_chat:
+ 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[f'name1{suffix}'], shared.settings[f'name2{suffix}'], shared.character))
+ else:
+ shared.gradio['display'] = gr.Chatbot(value=shared.history['visible']).style(color_map=("#326efd", "#212528"))
+ shared.gradio['textbox'] = gr.Textbox(label='Input')
with gr.Row():
- with gr.Column():
- shared.gradio['Continue'] = gr.Button('Continue')
- with gr.Column():
- shared.gradio['Stop'] = gr.Button('Stop')
+ shared.gradio['Stop'] = gr.Button('Stop', elem_id="stop")
+ shared.gradio['Generate'] = gr.Button('Generate')
+ with gr.Row():
+ shared.gradio['Impersonate'] = gr.Button('Impersonate')
+ shared.gradio['Regenerate'] = gr.Button('Regenerate')
+ with gr.Row():
+ shared.gradio['Copy last reply'] = gr.Button('Copy last reply')
+ shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
+ shared.gradio['Remove last'] = gr.Button('Remove last')
+
+ shared.gradio['Clear history'] = gr.Button('Clear history')
+ shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant="stop", visible=False)
+ shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False)
+
+ create_model_and_preset_menus()
+
+ with gr.Tab("Character", elem_id="chat-settings"):
+ shared.gradio['name1'] = gr.Textbox(value=shared.settings[f'name1{suffix}'], lines=1, label='Your name')
+ shared.gradio['name2'] = gr.Textbox(value=shared.settings[f'name2{suffix}'], lines=1, label='Bot\'s name')
+ shared.gradio['context'] = gr.Textbox(value=shared.settings[f'context{suffix}'], lines=5, label='Context')
+ 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')
+
+ with gr.Row():
+ with gr.Tab('Chat history'):
+ with gr.Row():
+ with gr.Column():
+ gr.Markdown('Upload')
+ shared.gradio['upload_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'])
+ with gr.Column():
+ gr.Markdown('Download')
+ shared.gradio['download'] = gr.File()
+ shared.gradio['download_button'] = gr.Button(value='Click me')
+ with gr.Tab('Upload character'):
+ with gr.Row():
+ with gr.Column():
+ gr.Markdown('1. Select the JSON file')
+ shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json'])
+ with gr.Column():
+ gr.Markdown('2. Select your character\'s profile picture (optional)')
+ shared.gradio['upload_img_bot'] = gr.File(type='binary', file_types=['image'])
+ shared.gradio['Upload character'] = gr.Button(value='Submit')
+ with gr.Tab('Upload your profile picture'):
+ shared.gradio['upload_img_me'] = gr.File(type='binary', file_types=['image'])
+ with gr.Tab('Upload TavernAI Character Card'):
+ shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
+
+ with gr.Tab("Parameters", elem_id="parameters"):
+ with gr.Box():
+ gr.Markdown("Chat parameters")
+ with gr.Row():
+ with gr.Column():
+ shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
+ shared.gradio['chat_prompt_size_slider'] = gr.Slider(minimum=shared.settings['chat_prompt_size_min'], maximum=shared.settings['chat_prompt_size_max'], step=1, label='Maximum prompt size in tokens', value=shared.settings['chat_prompt_size'])
+ with gr.Column():
+ shared.gradio['chat_generation_attempts'] = gr.Slider(minimum=shared.settings['chat_generation_attempts_min'], maximum=shared.settings['chat_generation_attempts_max'], value=shared.settings['chat_generation_attempts'], step=1, label='Generation attempts (for longer replies)')
+ shared.gradio['check'] = gr.Checkbox(value=shared.settings[f'stop_at_newline{suffix}'], label='Stop generating at new line character?')
create_settings_menus(default_preset)
- if shared.args.extensions is not None:
- extensions_module.create_extensions_block()
- with gr.Column():
+ function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
+ shared.input_params = [shared.gradio[k] for k in ['textbox', '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', 'name1', 'name2', 'context', 'check', 'chat_prompt_size_slider', 'chat_generation_attempts']]
+
+ gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
+ gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
+ gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
+ gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream))
+ shared.gradio['Stop'].click(chat.stop_everything_event, [], [], cancels=gen_events)
+
+ shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, [], shared.gradio['textbox'], show_progress=shared.args.no_stream)
+ shared.gradio['Replace last reply'].click(chat.replace_last_reply, [shared.gradio['textbox'], shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'], show_progress=shared.args.no_stream)
+
+ # Clear history with confirmation
+ clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
+ shared.gradio['Clear history'].click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, clear_arr)
+ shared.gradio['Clear history-confirm'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
+ shared.gradio['Clear history-confirm'].click(chat.clear_chat_log, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
+ shared.gradio['Clear history-cancel'].click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
+
+ shared.gradio['Remove last'].click(chat.remove_last_message, [shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['display'], shared.gradio['textbox']], show_progress=False)
+ shared.gradio['download_button'].click(chat.save_history, inputs=[], outputs=[shared.gradio['download']])
+ shared.gradio['Upload character'].click(chat.upload_character, [shared.gradio['upload_json'], shared.gradio['upload_img_bot']], [shared.gradio['character_menu']])
+
+ # Clearing stuff and saving the history
+ for i in ['Generate', 'Regenerate', 'Replace last reply']:
+ shared.gradio[i].click(lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False)
+ shared.gradio[i].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
+ shared.gradio['Clear history-confirm'].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
+ 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['character_menu'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['name2'], shared.gradio['context'], shared.gradio['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']], [])
+
+ 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}}}")
+ shared.gradio['interface'].load(lambda : chat.load_default_history(shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}']), None, None)
+ shared.gradio['interface'].load(reload_func, reload_inputs, [shared.gradio['display']], show_progress=True)
+
+ elif shared.args.notebook:
+ with gr.Tab("Text generation", elem_id="main"):
with gr.Tab('Raw'):
- shared.gradio['output_textbox'] = gr.Textbox(lines=15, label='Output')
+ shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=25)
with gr.Tab('Markdown'):
shared.gradio['markdown'] = gr.Markdown()
with gr.Tab('HTML'):
shared.gradio['html'] = gr.HTML()
- shared.input_params = [shared.gradio[k] for k in ['textbox', 'max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]
- output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
- gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
- gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
- gen_events.append(shared.gradio['Continue'].click(generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream))
- shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
+ with gr.Row():
+ shared.gradio['Stop'] = gr.Button('Stop')
+ shared.gradio['Generate'] = gr.Button('Generate')
+ shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
-shared.gradio['interface'].queue()
-if shared.args.listen:
- shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_name='0.0.0.0', server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch)
-else:
- shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch)
+ create_model_and_preset_menus()
+ with gr.Tab("Parameters", elem_id="parameters"):
+ create_settings_menus(default_preset)
+
+ shared.input_params = [shared.gradio[k] for k in ['textbox', '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']]
+ output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
+ gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
+ gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
+ shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
+ shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
+
+ else:
+ with gr.Tab("Text generation", elem_id="main"):
+ with gr.Row():
+ with gr.Column():
+ shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=15, label='Input')
+ shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
+ shared.gradio['Generate'] = gr.Button('Generate')
+ with gr.Row():
+ with gr.Column():
+ shared.gradio['Continue'] = gr.Button('Continue')
+ with gr.Column():
+ shared.gradio['Stop'] = gr.Button('Stop')
+
+ create_model_and_preset_menus()
+
+ with gr.Column():
+ with gr.Tab('Raw'):
+ shared.gradio['output_textbox'] = gr.Textbox(lines=25, label='Output')
+ with gr.Tab('Markdown'):
+ shared.gradio['markdown'] = gr.Markdown()
+ with gr.Tab('HTML'):
+ shared.gradio['html'] = gr.HTML()
+ with gr.Tab("Parameters", elem_id="parameters"):
+ create_settings_menus(default_preset)
+
+ shared.input_params = [shared.gradio[k] for k in ['textbox', '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']]
+ output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
+ gen_events.append(shared.gradio['Generate'].click(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream, api_name='textgen'))
+ gen_events.append(shared.gradio['textbox'].submit(generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream))
+ gen_events.append(shared.gradio['Continue'].click(generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream))
+ shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
+ shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
+
+ with gr.Tab("Interface mode", elem_id="interface-mode"):
+ modes = ["default", "notebook", "chat", "cai_chat"]
+ current_mode = "default"
+ for mode in modes[1:]:
+ if eval(f"shared.args.{mode}"):
+ current_mode = mode
+ break
+ cmd_list = vars(shared.args)
+ cmd_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes]
+ active_cmd_list = [k for k in cmd_list if vars(shared.args)[k]]
+
+ gr.Markdown("*Experimental*")
+ shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode")
+ shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions")
+ shared.gradio['cmd_arguments_menu'] = gr.CheckboxGroup(choices=cmd_list, value=active_cmd_list, label="Boolean command-line flags")
+ shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface", type="primary")
+
+ shared.gradio['reset_interface'].click(set_interface_arguments, [shared.gradio[k] for k in ['interface_modes_menu', 'extensions_menu', 'cmd_arguments_menu']], None)
+ shared.gradio['reset_interface'].click(lambda : None, None, None, _js='() => {document.body.innerHTML=\'{x}
" for x in row[1].split('\n')]) + row = [convert_to_markdown(entry) for entry in _row] + output += f""" """ if not (i == len(history)-1 and len(row[0]) == 0): - p = '\n'.join([f"{x}
" for x in row[0].split('\n')]) output += f"""