mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-30 06:00:15 +01:00
418 lines
23 KiB
Python
418 lines
23 KiB
Python
import gc
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import io
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import json
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import re
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import sys
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import time
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import zipfile
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from pathlib import Path
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import gradio as gr
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import torch
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import transformers
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import modules.chat as chat
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import modules.extensions as extensions_module
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import modules.shared as shared
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import modules.ui as ui
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from modules.extensions import extension_state
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from modules.extensions import load_extensions
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from modules.extensions import update_extensions_parameters
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from modules.html_generator import generate_chat_html
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from modules.models import load_model
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from modules.models import load_soft_prompt
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from modules.text_generation import generate_reply
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transformers.logging.set_verbosity_error()
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if (shared.args.chat or shared.args.cai_chat) and not shared.args.no_stream:
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print("Warning: chat mode currently becomes somewhat slower with text streaming on.\nConsider starting the web UI with the --no-stream option.\n")
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shared.settings = {
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'max_new_tokens': 200,
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'max_new_tokens_min': 1,
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'max_new_tokens_max': 2000,
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'preset': 'NovelAI-Sphinx Moth',
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'name1': 'Person 1',
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'name2': 'Person 2',
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'context': 'This is a conversation between two people.',
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'prompt': 'Common sense questions and answers\n\nQuestion: \nFactual answer:',
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'prompt_gpt4chan': '-----\n--- 865467536\nInput text\n--- 865467537\n',
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'stop_at_newline': True,
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'chat_prompt_size': 2048,
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'chat_prompt_size_min': 0,
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'chat_prompt_size_max': 2048,
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'preset_pygmalion': 'Pygmalion',
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'name1_pygmalion': 'You',
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'name2_pygmalion': 'Kawaii',
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'context_pygmalion': "Kawaii's persona: Kawaii is a cheerful person who loves to make others smile. She is an optimist who loves to spread happiness and positivity wherever she goes.\n<START>",
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'stop_at_newline_pygmalion': False,
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}
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if shared.args.settings is not None and Path(shared.args.settings).exists():
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new_settings = json.loads(open(Path(shared.args.settings), 'r').read())
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for item in new_settings:
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shared.settings[item] = new_settings[item]
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def load_model_wrapper(selected_model):
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if selected_model != shared.model_name:
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shared.model_name = selected_model
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shared.model = shared.tokenizer = None
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if not shared.args.cpu:
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gc.collect()
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torch.cuda.empty_cache()
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shared.model, shared.tokenizer = load_model(shared.model_name)
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return selected_model
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def load_preset_values(preset_menu, return_dict=False):
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generate_params = {
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'do_sample': True,
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'temperature': 1,
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'top_p': 1,
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'typical_p': 1,
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'repetition_penalty': 1,
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'top_k': 50,
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'num_beams': 1,
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'penalty_alpha': 0,
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'min_length': 0,
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'length_penalty': 1,
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'no_repeat_ngram_size': 0,
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'early_stopping': False,
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}
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with open(Path(f'presets/{preset_menu}.txt'), 'r') as infile:
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preset = infile.read()
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for i in preset.splitlines():
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i = i.rstrip(',').strip().split('=')
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if len(i) == 2 and i[0].strip() != 'tokens':
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generate_params[i[0].strip()] = eval(i[1].strip())
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generate_params['temperature'] = min(1.99, generate_params['temperature'])
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if return_dict:
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return generate_params
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else:
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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']
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def upload_soft_prompt(file):
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with zipfile.ZipFile(io.BytesIO(file)) as zf:
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zf.extract('meta.json')
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j = json.loads(open('meta.json', 'r').read())
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name = j['name']
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Path('meta.json').unlink()
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with open(Path(f'softprompts/{name}.zip'), 'wb') as f:
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f.write(file)
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return name
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def get_available_models():
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return sorted([item.name for item in list(Path('models/').glob('*')) if not item.name.endswith(('.txt', '-np'))], key=str.lower)
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def get_available_presets():
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return sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('presets').glob('*.txt'))), key=str.lower)
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def get_available_characters():
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return ["None"] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('characters').glob('*.json'))), key=str.lower)
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def get_available_extensions():
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return sorted(set(map(lambda x : x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower)
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def get_available_softprompts():
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return ["None"] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower)
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def create_extensions_block():
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extensions_ui_elements = []
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default_values = []
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if not (shared.args.chat or shared.args.cai_chat):
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gr.Markdown('## Extensions parameters')
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for ext in sorted(extension_state, key=lambda x : extension_state[x][1]):
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if extension_state[ext][0] == True:
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params = extensions_module.get_params(ext)
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for param in params:
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_id = f"{ext}-{param}"
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default_value = shared.settings[_id] if _id in shared.settings else params[param]
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default_values.append(default_value)
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if type(params[param]) == str:
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extensions_ui_elements.append(gr.Textbox(value=default_value, label=f"{ext}-{param}"))
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elif type(params[param]) in [int, float]:
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extensions_ui_elements.append(gr.Number(value=default_value, label=f"{ext}-{param}"))
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elif type(params[param]) == bool:
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extensions_ui_elements.append(gr.Checkbox(value=default_value, label=f"{ext}-{param}"))
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update_extensions_parameters(*default_values)
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btn_extensions = gr.Button("Apply")
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btn_extensions.click(update_extensions_parameters, [*extensions_ui_elements], [])
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def create_settings_menus():
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generate_params = load_preset_values(shared.settings[f'preset{suffix}'] if not shared.args.flexgen else 'Naive', return_dict=True)
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with gr.Row():
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with gr.Column():
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with gr.Row():
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model_menu = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model')
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ui.create_refresh_button(model_menu, lambda : None, lambda : {"choices": get_available_models()}, "refresh-button")
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with gr.Column():
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with gr.Row():
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preset_menu = gr.Dropdown(choices=available_presets, value=shared.settings[f'preset{suffix}'] if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
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ui.create_refresh_button(preset_menu, lambda : None, lambda : {"choices": get_available_presets()}, "refresh-button")
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with gr.Accordion("Custom generation parameters", open=False, elem_id="accordion"):
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with gr.Row():
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do_sample = gr.Checkbox(value=generate_params['do_sample'], label="do_sample")
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temperature = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label="temperature")
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with gr.Row():
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top_k = gr.Slider(0,200,value=generate_params['top_k'],step=1,label="top_k")
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top_p = gr.Slider(0.0,1.0,value=generate_params['top_p'],step=0.01,label="top_p")
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with gr.Row():
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repetition_penalty = gr.Slider(1.0,4.99,value=generate_params['repetition_penalty'],step=0.01,label="repetition_penalty")
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no_repeat_ngram_size = gr.Slider(0, 20, step=1, value=generate_params["no_repeat_ngram_size"], label="no_repeat_ngram_size")
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with gr.Row():
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typical_p = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label="typical_p")
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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)
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gr.Markdown("Contrastive search:")
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penalty_alpha = gr.Slider(0, 5, value=generate_params["penalty_alpha"], label="penalty_alpha")
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gr.Markdown("Beam search (uses a lot of VRAM):")
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with gr.Row():
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num_beams = gr.Slider(1, 20, step=1, value=generate_params["num_beams"], label="num_beams")
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length_penalty = gr.Slider(-5, 5, value=generate_params["length_penalty"], label="length_penalty")
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early_stopping = gr.Checkbox(value=generate_params["early_stopping"], label="early_stopping")
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with gr.Accordion("Soft prompt", open=False, elem_id="accordion"):
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with gr.Row():
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softprompts_menu = gr.Dropdown(choices=available_softprompts, value="None", label='Soft prompt')
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ui.create_refresh_button(softprompts_menu, lambda : None, lambda : {"choices": get_available_softprompts()}, "refresh-button")
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gr.Markdown('Upload a soft prompt (.zip format):')
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with gr.Row():
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upload_softprompt = gr.File(type='binary', file_types=[".zip"])
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model_menu.change(load_model_wrapper, [model_menu], [model_menu], show_progress=True)
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preset_menu.change(load_preset_values, [preset_menu], [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])
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softprompts_menu.change(load_soft_prompt, [softprompts_menu], [softprompts_menu], show_progress=True)
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upload_softprompt.upload(upload_soft_prompt, [upload_softprompt], [softprompts_menu])
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return preset_menu, 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
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# Global variables
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available_models = get_available_models()
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available_presets = get_available_presets()
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available_characters = get_available_characters()
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available_softprompts = get_available_softprompts()
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extensions_module.available_extensions = get_available_extensions()
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if shared.args.extensions is not None:
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load_extensions()
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# Choosing the default model
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if shared.args.model is not None:
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shared.model_name = shared.args.model
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else:
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if len(available_models) == 0:
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print("No models are available! Please download at least one.")
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sys.exit(0)
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elif len(available_models) == 1:
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i = 0
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else:
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print("The following models are available:\n")
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for i,model in enumerate(available_models):
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print(f"{i+1}. {model}")
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print(f"\nWhich one do you want to load? 1-{len(available_models)}\n")
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i = int(input())-1
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print()
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shared.model_name = available_models[i]
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shared.model, shared.tokenizer = load_model(shared.model_name)
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# UI settings
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if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')):
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default_text = shared.settings['prompt_gpt4chan']
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elif re.match('(rosey|chip|joi)_.*_instruct.*', shared.model_name.lower()) is not None:
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default_text = 'User: \n'
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else:
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default_text = shared.settings['prompt']
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description = f"\n\n# Text generation lab\nGenerate text using Large Language Models.\n"
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suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''
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buttons = {}
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gen_events = []
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if shared.args.chat or shared.args.cai_chat:
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if Path(f'logs/persistent.json').exists():
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chat.load_history(open(Path(f'logs/persistent.json'), 'rb').read(), shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}'])
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with gr.Blocks(css=ui.css+ui.chat_css, analytics_enabled=False) as interface:
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if shared.args.cai_chat:
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display = gr.HTML(value=generate_chat_html(chat.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}'], chat.character))
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else:
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display = gr.Chatbot(value=chat.history['visible'])
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textbox = gr.Textbox(label='Input')
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with gr.Row():
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buttons["Stop"] = gr.Button("Stop")
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buttons["Generate"] = gr.Button("Generate")
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buttons["Regenerate"] = gr.Button("Regenerate")
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with gr.Row():
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buttons["Impersonate"] = gr.Button("Impersonate")
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buttons["Remove last"] = gr.Button("Remove last")
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buttons["Clear history"] = gr.Button("Clear history")
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with gr.Row():
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buttons["Send last reply to input"] = gr.Button("Send last reply to input")
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buttons["Replace last reply"] = gr.Button("Replace last reply")
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if shared.args.picture:
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with gr.Row():
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picture_select = gr.Image(label="Send a picture", type='pil')
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with gr.Tab("Chat settings"):
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name1 = gr.Textbox(value=shared.settings[f'name1{suffix}'], lines=1, label='Your name')
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name2 = gr.Textbox(value=shared.settings[f'name2{suffix}'], lines=1, label='Bot\'s name')
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context = gr.Textbox(value=shared.settings[f'context{suffix}'], lines=2, label='Context')
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with gr.Row():
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character_menu = gr.Dropdown(choices=available_characters, value="None", label='Character')
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ui.create_refresh_button(character_menu, lambda : None, lambda : {"choices": get_available_characters()}, "refresh-button")
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with gr.Row():
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check = gr.Checkbox(value=shared.settings[f'stop_at_newline{suffix}'], label='Stop generating at new line character?')
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with gr.Row():
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with gr.Tab('Chat history'):
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with gr.Row():
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with gr.Column():
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gr.Markdown('Upload')
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upload_chat_history = gr.File(type='binary', file_types=[".json", ".txt"])
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with gr.Column():
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gr.Markdown('Download')
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download = gr.File()
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buttons["Download"] = gr.Button(value="Click me")
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with gr.Tab('Upload character'):
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with gr.Row():
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with gr.Column():
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gr.Markdown('1. Select the JSON file')
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upload_char = gr.File(type='binary', file_types=[".json"])
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with gr.Column():
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gr.Markdown('2. Select your character\'s profile picture (optional)')
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upload_img = gr.File(type='binary', file_types=["image"])
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buttons["Upload character"] = gr.Button(value="Submit")
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with gr.Tab('Upload your profile picture'):
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upload_img_me = gr.File(type='binary', file_types=["image"])
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with gr.Tab('Upload TavernAI Character Card'):
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upload_img_tavern = gr.File(type='binary', file_types=["image"])
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with gr.Tab("Generation settings"):
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with gr.Row():
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with gr.Column():
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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'])
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with gr.Column():
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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'])
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preset_menu, 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 = create_settings_menus()
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if shared.args.extensions is not None:
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with gr.Tab("Extensions"):
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create_extensions_block()
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input_params = [textbox, max_new_tokens, do_sample, max_new_tokens, 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]
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if shared.args.picture:
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input_params.append(picture_select)
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function_call = "chat.cai_chatbot_wrapper" if shared.args.cai_chat else "chat.chatbot_wrapper"
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gen_events.append(buttons["Generate"].click(eval(function_call), input_params, display, show_progress=shared.args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(eval(function_call), input_params, display, show_progress=shared.args.no_stream))
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if shared.args.picture:
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picture_select.upload(eval(function_call), input_params, display, show_progress=shared.args.no_stream)
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gen_events.append(buttons["Regenerate"].click(chat.regenerate_wrapper, input_params, display, show_progress=shared.args.no_stream))
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gen_events.append(buttons["Impersonate"].click(chat.impersonate_wrapper, input_params, textbox, show_progress=shared.args.no_stream))
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buttons["Stop"].click(chat.stop_everything_event, [], [], cancels=gen_events)
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buttons["Send last reply to input"].click(chat.send_last_reply_to_input, [], textbox, show_progress=shared.args.no_stream)
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buttons["Replace last reply"].click(chat.replace_last_reply, [textbox, name1, name2], display, show_progress=shared.args.no_stream)
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buttons["Clear history"].click(chat.clear_chat_log, [character_menu, name1, name2], display)
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buttons["Remove last"].click(chat.remove_last_message, [name1, name2], [display, textbox], show_progress=False)
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buttons["Download"].click(chat.save_history, inputs=[], outputs=[download])
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buttons["Upload character"].click(chat.upload_character, [upload_char, upload_img], [character_menu])
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# Clearing stuff and saving the history
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for i in ["Generate", "Regenerate", "Replace last reply"]:
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buttons[i].click(lambda x: "", textbox, textbox, show_progress=False)
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buttons[i].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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buttons["Clear history"].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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textbox.submit(lambda x: "", textbox, textbox, show_progress=False)
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textbox.submit(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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character_menu.change(chat.load_character, [character_menu, name1, name2], [name2, context, display])
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upload_chat_history.upload(chat.load_history, [upload_chat_history, name1, name2], [])
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upload_img_tavern.upload(chat.upload_tavern_character, [upload_img_tavern, name1, name2], [character_menu])
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upload_img_me.upload(chat.upload_your_profile_picture, [upload_img_me], [])
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if shared.args.picture:
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picture_select.upload(lambda : None, [], [picture_select], show_progress=False)
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if shared.args.cai_chat:
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upload_chat_history.upload(chat.redraw_html, [name1, name2], [display])
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upload_img_me.upload(chat.redraw_html, [name1, name2], [display])
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else:
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upload_chat_history.upload(lambda : chat.history['visible'], [], [display])
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upload_img_me.upload(lambda : chat.history['visible'], [], [display])
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elif shared.args.notebook:
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with gr.Blocks(css=ui.css, analytics_enabled=False) as interface:
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gr.Markdown(description)
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with gr.Tab('Raw'):
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textbox = gr.Textbox(value=default_text, lines=23)
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with gr.Tab('Markdown'):
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markdown = gr.Markdown()
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with gr.Tab('HTML'):
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html = gr.HTML()
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buttons["Generate"] = gr.Button("Generate")
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buttons["Stop"] = gr.Button("Stop")
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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'])
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preset_menu, 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 = create_settings_menus()
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if shared.args.extensions is not None:
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create_extensions_block()
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gen_events.append(buttons["Generate"].click(generate_reply, [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping], [textbox, markdown, html], show_progress=shared.args.no_stream, api_name="textgen"))
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gen_events.append(textbox.submit(generate_reply, [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping], [textbox, markdown, html], show_progress=shared.args.no_stream))
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buttons["Stop"].click(None, None, None, cancels=gen_events)
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else:
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with gr.Blocks(css=ui.css, analytics_enabled=False) as interface:
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gr.Markdown(description)
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with gr.Row():
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with gr.Column():
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textbox = gr.Textbox(value=default_text, lines=15, label='Input')
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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'])
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buttons["Generate"] = gr.Button("Generate")
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with gr.Row():
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with gr.Column():
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buttons["Continue"] = gr.Button("Continue")
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with gr.Column():
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buttons["Stop"] = gr.Button("Stop")
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|
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preset_menu, 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 = create_settings_menus()
|
|
if shared.args.extensions is not None:
|
|
create_extensions_block()
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|
|
|
with gr.Column():
|
|
with gr.Tab('Raw'):
|
|
output_textbox = gr.Textbox(lines=15, label='Output')
|
|
with gr.Tab('Markdown'):
|
|
markdown = gr.Markdown()
|
|
with gr.Tab('HTML'):
|
|
html = gr.HTML()
|
|
|
|
gen_events.append(buttons["Generate"].click(generate_reply, [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping], [output_textbox, markdown, html], show_progress=shared.args.no_stream, api_name="textgen"))
|
|
gen_events.append(textbox.submit(generate_reply, [textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping], [output_textbox, markdown, html], show_progress=shared.args.no_stream))
|
|
gen_events.append(buttons["Continue"].click(generate_reply, [output_textbox, max_new_tokens, do_sample, max_new_tokens, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping], [output_textbox, markdown, html], show_progress=shared.args.no_stream))
|
|
buttons["Stop"].click(None, None, None, cancels=gen_events)
|
|
|
|
interface.queue()
|
|
if shared.args.listen:
|
|
interface.launch(prevent_thread_lock=True, share=shared.args.share, server_name="0.0.0.0", server_port=shared.args.listen_port)
|
|
else:
|
|
interface.launch(prevent_thread_lock=True, share=shared.args.share, server_port=shared.args.listen_port)
|
|
|
|
# I think that I will need this later
|
|
while True:
|
|
time.sleep(0.5)
|