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Merge pull request #123 from oobabooga/refactor_gradio
Create new extensions engine
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oobabooga
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3ef0f2ea7e
@ -134,7 +134,6 @@ Optionally, you can use the following command-line flags:
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| `--notebook` | Launch the web UI in notebook mode, where the output is written to the same text box as the input. |
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| `--chat` | Launch the web UI in chat mode.|
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| `--cai-chat` | Launch the web UI in chat mode with a style similar to Character.AI's. If the file `img_bot.png` or `img_bot.jpg` exists in the same folder as server.py, this image will be used as the bot's profile picture. Similarly, `img_me.png` or `img_me.jpg` will be used as your profile picture. |
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| `--picture` | Adds an ability to send pictures in chat UI modes. Captions are generated by BLIP. |
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| `--cpu` | Use the CPU to generate text.|
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| `--load-in-8bit` | Load the model with 8-bit precision.|
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| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
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@ -41,7 +41,6 @@ response = requests.post(f"http://{server}:7860/run/textgen", json={
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prompt,
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params['max_new_tokens'],
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params['do_sample'],
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params['max_new_tokens'],
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params['temperature'],
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params['top_p'],
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params['typical_p'],
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@ -1,3 +1,5 @@
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import gradio as gr
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params = {
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"bias string": " *I speak in an annoyingly cute way*",
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}
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@ -25,3 +27,10 @@ def bot_prefix_modifier(string):
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"""
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return f'{string} {params["bias string"].strip()} '
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def ui():
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# Gradio elements
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string = gr.Textbox(value=params["bias string"], label='Character bias')
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# Event functions to update the parameters in the backend
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string.change(lambda x: params.update({"bias string": x}), string, None)
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@ -1,9 +1,12 @@
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import gradio as gr
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from deep_translator import GoogleTranslator
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params = {
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"language string": "ja",
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}
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language_codes = {'Afrikaans': 'af', 'Albanian': 'sq', 'Amharic': 'am', 'Arabic': 'ar', 'Armenian': 'hy', 'Azerbaijani': 'az', 'Basque': 'eu', 'Belarusian': 'be', 'Bengali': 'bn', 'Bosnian': 'bs', 'Bulgarian': 'bg', 'Catalan': 'ca', 'Cebuano': 'ceb', 'Chinese (Simplified)': 'zh-CN', 'Chinese (Traditional)': 'zh-TW', 'Corsican': 'co', 'Croatian': 'hr', 'Czech': 'cs', 'Danish': 'da', 'Dutch': 'nl', 'English': 'en', 'Esperanto': 'eo', 'Estonian': 'et', 'Finnish': 'fi', 'French': 'fr', 'Frisian': 'fy', 'Galician': 'gl', 'Georgian': 'ka', 'German': 'de', 'Greek': 'el', 'Gujarati': 'gu', 'Haitian Creole': 'ht', 'Hausa': 'ha', 'Hawaiian': 'haw', 'Hebrew': 'iw', 'Hindi': 'hi', 'Hmong': 'hmn', 'Hungarian': 'hu', 'Icelandic': 'is', 'Igbo': 'ig', 'Indonesian': 'id', 'Irish': 'ga', 'Italian': 'it', 'Japanese': 'ja', 'Javanese': 'jw', 'Kannada': 'kn', 'Kazakh': 'kk', 'Khmer': 'km', 'Korean': 'ko', 'Kurdish': 'ku', 'Kyrgyz': 'ky', 'Lao': 'lo', 'Latin': 'la', 'Latvian': 'lv', 'Lithuanian': 'lt', 'Luxembourgish': 'lb', 'Macedonian': 'mk', 'Malagasy': 'mg', 'Malay': 'ms', 'Malayalam': 'ml', 'Maltese': 'mt', 'Maori': 'mi', 'Marathi': 'mr', 'Mongolian': 'mn', 'Myanmar (Burmese)': 'my', 'Nepali': 'ne', 'Norwegian': 'no', 'Nyanja (Chichewa)': 'ny', 'Pashto': 'ps', 'Persian': 'fa', 'Polish': 'pl', 'Portuguese (Portugal, Brazil)': 'pt', 'Punjabi': 'pa', 'Romanian': 'ro', 'Russian': 'ru', 'Samoan': 'sm', 'Scots Gaelic': 'gd', 'Serbian': 'sr', 'Sesotho': 'st', 'Shona': 'sn', 'Sindhi': 'sd', 'Sinhala (Sinhalese)': 'si', 'Slovak': 'sk', 'Slovenian': 'sl', 'Somali': 'so', 'Spanish': 'es', 'Sundanese': 'su', 'Swahili': 'sw', 'Swedish': 'sv', 'Tagalog (Filipino)': 'tl', 'Tajik': 'tg', 'Tamil': 'ta', 'Telugu': 'te', 'Thai': 'th', 'Turkish': 'tr', 'Ukrainian': 'uk', 'Urdu': 'ur', 'Uzbek': 'uz', 'Vietnamese': 'vi', 'Welsh': 'cy', 'Xhosa': 'xh', 'Yiddish': 'yi', 'Yoruba': 'yo', 'Zulu': 'zu'}
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def input_modifier(string):
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"""
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This function is applied to your text inputs before
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@ -27,3 +30,13 @@ def bot_prefix_modifier(string):
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"""
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return string
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def ui():
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# Finding the language name from the language code to use as the default value
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language_name = list(language_codes.keys())[list(language_codes.values()).index(params['language string'])]
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# Gradio elements
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language = gr.Dropdown(value=language_name, choices=[k for k in language_codes], label='Language')
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# Event functions to update the parameters in the backend
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language.change(lambda x: params.update({"language string": language_codes[x]}), language, None)
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60
extensions/send_pictures/script.py
Normal file
60
extensions/send_pictures/script.py
Normal file
@ -0,0 +1,60 @@
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import base64
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from io import BytesIO
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import gradio as gr
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import modules.chat as chat
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import modules.shared as shared
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from modules.bot_picture import caption_image
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params = {
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}
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# If 'state' is 'temporary' or 'permanent', will hijack the next
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# chatbot wrapper call with a custom input text and optionally
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# custom output text
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input_hijack = {
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'state': 'off',
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'value': ["", ""]
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}
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def generate_chat_picture(picture, name1, name2):
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text = f'*{name1} sends {name2} a picture that contains the following: "{caption_image(picture)}"*'
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buffer = BytesIO()
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picture.save(buffer, format="JPEG")
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img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
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visible_text = f'<img src="data:image/jpeg;base64,{img_str}">'
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return text, visible_text
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def input_modifier(string):
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"""
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This function is applied to your text inputs before
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they are fed into the model.
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"""
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return string
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def output_modifier(string):
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"""
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This function is applied to the model outputs.
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"""
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return string
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def bot_prefix_modifier(string):
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"""
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This function is only applied in chat mode. It modifies
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the prefix text for the Bot and can be used to bias its
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behavior.
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"""
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return string
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def ui():
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picture_select = gr.Image(label='Send a picture', type='pil')
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function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
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picture_select.upload(lambda picture, name1, name2: input_hijack.update({"state": True, "value": generate_chat_picture(picture, name1, name2)}), [picture_select, shared.gradio['name1'], shared.gradio['name2']], None)
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picture_select.upload(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream)
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picture_select.upload(lambda : None, [], [picture_select], show_progress=False)
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#parser.add_argument('--picture', action='store_true', help='Adds an ability to send pictures in chat UI modes. Captions are generated by BLIP.')
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@ -1,6 +1,7 @@
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import asyncio
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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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torch._C._jit_set_profiling_mode(False)
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@ -81,3 +82,12 @@ def bot_prefix_modifier(string):
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"""
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return string
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def ui():
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# Gradio elements
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activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
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voice = gr.Dropdown(value=params['speaker'], choices=[f'en_{i}' for i in range(1, 118)], label='TTS voice')
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# Event functions to update the parameters in the backend
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activate.change(lambda x: params.update({"activate": x}), activate, None)
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voice.change(lambda x: params.update({"speaker": x}), voice, None)
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@ -4,19 +4,16 @@ import io
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import json
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import re
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from datetime import datetime
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from io import BytesIO
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from pathlib import Path
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from PIL import Image
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import modules.shared as shared
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import modules.extensions as extensions_module
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from modules.extensions import apply_extensions
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from modules.html_generator import generate_chat_html
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from modules.text_generation import encode, generate_reply, get_max_prompt_length
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if shared.args.picture and (shared.args.cai_chat or shared.args.chat):
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import modules.bot_picture as bot_picture
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# This gets the new line characters right.
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def clean_chat_message(text):
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text = text.replace('\n', '\n\n')
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@ -24,16 +21,16 @@ def clean_chat_message(text):
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text = text.strip()
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return text
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def generate_chat_prompt(user_input, tokens, name1, name2, context, chat_prompt_size, impersonate=False):
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def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=False):
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user_input = clean_chat_message(user_input)
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rows = [f"{context.strip()}\n"]
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if shared.soft_prompt:
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chat_prompt_size -= shared.soft_prompt_tensor.shape[1]
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max_length = min(get_max_prompt_length(tokens), chat_prompt_size)
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max_length = min(get_max_prompt_length(max_new_tokens), chat_prompt_size)
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i = len(shared.history['internal'])-1
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while i >= 0 and len(encode(''.join(rows), tokens)[0]) < max_length:
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while i >= 0 and len(encode(''.join(rows), max_new_tokens)[0]) < max_length:
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rows.insert(1, f"{name2}: {shared.history['internal'][i][1].strip()}\n")
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if not (shared.history['internal'][i][0] == '<|BEGIN-VISIBLE-CHAT|>'):
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rows.insert(1, f"{name1}: {shared.history['internal'][i][0].strip()}\n")
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@ -47,7 +44,7 @@ def generate_chat_prompt(user_input, tokens, name1, name2, context, chat_prompt_
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rows.append(f"{name1}:")
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limit = 2
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while len(rows) > limit and len(encode(''.join(rows), tokens)[0]) >= max_length:
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while len(rows) > limit and len(encode(''.join(rows), max_new_tokens)[0]) >= max_length:
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rows.pop(1)
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prompt = ''.join(rows)
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@ -84,36 +81,40 @@ def extract_message_from_reply(question, reply, current, other, check, extension
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return reply, next_character_found, substring_found
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def generate_chat_picture(picture, name1, name2):
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text = f'*{name1} sends {name2} a picture that contains the following: "{bot_picture.caption_image(picture)}"*'
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buffer = BytesIO()
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picture.save(buffer, format="JPEG")
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img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
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visible_text = f'<img src="data:image/jpeg;base64,{img_str}">'
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return text, visible_text
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def stop_everything_event():
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shared.stop_everything = True
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def chatbot_wrapper(text, 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, picture=None):
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def chatbot_wrapper(text, 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, chat_generation_attempts=1):
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shared.stop_everything = False
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just_started = True
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eos_token = '\n' if check else None
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if 'pygmalion' in shared.model_name.lower():
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name1 = "You"
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if shared.args.picture and picture is not None:
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text, visible_text = generate_chat_picture(picture, name1, name2)
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else:
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# Check if any extension wants to hijack this function call
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visible_text = None
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custom_prompt_generator = None
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for extension, _ in extensions_module.iterator():
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if hasattr(extension, 'input_hijack') and extension.input_hijack['state'] == True:
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text, visible_text = extension.input_hijack['value']
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if custom_prompt_generator is None and hasattr(extension, 'custom_prompt_generator'):
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custom_prompt_generator = extension.custom_prompt_generator
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if visible_text is None:
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visible_text = text
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if shared.args.chat:
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visible_text = visible_text.replace('\n', '<br>')
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text = apply_extensions(text, "input")
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prompt = generate_chat_prompt(text, tokens, name1, name2, context, chat_prompt_size)
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if custom_prompt_generator is None:
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prompt = generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size)
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else:
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prompt = custom_prompt_generator(text, max_new_tokens, name1, name2, context, chat_prompt_size)
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# Generate
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for reply in generate_reply(prompt, 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, eos_token=eos_token, stopping_string=f"\n{name1}:"):
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reply = ' '
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for i in range(chat_generation_attempts):
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for reply in generate_reply(prompt+reply, 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=eos_token, stopping_string=f"\n{name1}:"):
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# Extracting the reply
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reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name2, name1, check, extensions=True)
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@ -138,15 +139,17 @@ def chatbot_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top_p,
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break
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yield shared.history['visible']
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def impersonate_wrapper(text, 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, picture=None):
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def impersonate_wrapper(text, 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, generation_attempts=1):
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eos_token = '\n' if check else None
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if 'pygmalion' in shared.model_name.lower():
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name1 = "You"
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prompt = generate_chat_prompt(text, tokens, name1, name2, context, chat_prompt_size, impersonate=True)
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prompt = generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=True)
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for reply in generate_reply(prompt, 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, eos_token=eos_token, stopping_string=f"\n{name2}:"):
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reply = ' '
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for i in range(generation_attempts):
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for reply in generate_reply(prompt+reply, 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=eos_token, stopping_string=f"\n{name2}:"):
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reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name1, name2, check, extensions=False)
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if not substring_found:
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yield reply
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@ -154,11 +157,11 @@ def impersonate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, to
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break
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yield reply
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def cai_chatbot_wrapper(text, 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, picture=None):
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for _history in chatbot_wrapper(text, 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, picture):
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def cai_chatbot_wrapper(text, 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, chat_generation_attempts=1):
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for _history in chatbot_wrapper(text, 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, chat_generation_attempts):
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yield generate_chat_html(_history, name1, name2, shared.character)
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def regenerate_wrapper(text, 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, picture=None):
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def regenerate_wrapper(text, 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, chat_generation_attempts=1):
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if shared.character != 'None' and len(shared.history['visible']) == 1:
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if shared.args.cai_chat:
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yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
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@ -168,7 +171,7 @@ def regenerate_wrapper(text, tokens, do_sample, max_new_tokens, temperature, top
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last_visible = shared.history['visible'].pop()
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last_internal = shared.history['internal'].pop()
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for _history in chatbot_wrapper(last_internal[0], 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, picture):
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for _history in chatbot_wrapper(last_internal[0], 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, chat_generation_attempts):
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if shared.args.cai_chat:
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shared.history['visible'][-1] = [last_visible[0], _history[-1][1]]
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yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
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@ -253,7 +256,7 @@ def tokenize_dialogue(dialogue, name1, name2):
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_history.append(entry)
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entry = ['', '']
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print(f"\033[1;32;1m\nDialogue tokenized to:\033[0;37;0m\n", end='')
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print("\033[1;32;1m\nDialogue tokenized to:\033[0;37;0m\n", end='')
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for row in _history:
|
||||
for column in row:
|
||||
print("\n")
|
||||
@ -301,8 +304,8 @@ def load_history(file, name1, name2):
|
||||
shared.history['visible'] = copy.deepcopy(shared.history['internal'])
|
||||
|
||||
def load_default_history(name1, name2):
|
||||
if Path(f'logs/persistent.json').exists():
|
||||
load_history(open(Path(f'logs/persistent.json'), 'rb').read(), name1, name2)
|
||||
if Path('logs/persistent.json').exists():
|
||||
load_history(open(Path('logs/persistent.json'), 'rb').read(), name1, name2)
|
||||
else:
|
||||
shared.history['internal'] = []
|
||||
shared.history['visible'] = []
|
||||
@ -370,5 +373,5 @@ def upload_tavern_character(img, name1, name2):
|
||||
|
||||
def upload_your_profile_picture(img):
|
||||
img = Image.open(io.BytesIO(img))
|
||||
img.save(Path(f'img_me.png'))
|
||||
print(f'Profile picture saved to "img_me.png"')
|
||||
img.save(Path('img_me.png'))
|
||||
print('Profile picture saved to "img_me.png"')
|
||||
|
||||
@ -1,5 +1,3 @@
|
||||
import gradio as gr
|
||||
|
||||
import extensions
|
||||
import modules.shared as shared
|
||||
|
||||
@ -13,7 +11,7 @@ def load_extensions():
|
||||
print(f'Loading the extension "{name}"... ', end='')
|
||||
exec(f"import extensions.{name}.script")
|
||||
state[name] = [True, i]
|
||||
print(f'Ok.')
|
||||
print('Ok.')
|
||||
|
||||
# This iterator returns the extensions in the order specified in the command-line
|
||||
def iterator():
|
||||
@ -32,31 +30,15 @@ def apply_extensions(text, typ):
|
||||
text = extension.bot_prefix_modifier(text)
|
||||
return text
|
||||
|
||||
def update_extensions_parameters(*args):
|
||||
i = 0
|
||||
for extension, _ in iterator():
|
||||
for param in extension.params:
|
||||
if len(args) >= i+1:
|
||||
extension.params[param] = eval(f"args[{i}]")
|
||||
i += 1
|
||||
|
||||
def create_extensions_block():
|
||||
extensions_ui_elements = []
|
||||
default_values = []
|
||||
if not (shared.args.chat or shared.args.cai_chat):
|
||||
gr.Markdown('## Extensions parameters')
|
||||
# Updating the default values
|
||||
for extension, name in iterator():
|
||||
for param in extension.params:
|
||||
_id = f"{name}-{param}"
|
||||
default_value = shared.settings[_id] if _id in shared.settings else extension.params[param]
|
||||
default_values.append(default_value)
|
||||
if type(extension.params[param]) == str:
|
||||
extensions_ui_elements.append(gr.Textbox(value=default_value, label=f"{name}-{param}"))
|
||||
elif type(extension.params[param]) in [int, float]:
|
||||
extensions_ui_elements.append(gr.Number(value=default_value, label=f"{name}-{param}"))
|
||||
elif type(extension.params[param]) == bool:
|
||||
extensions_ui_elements.append(gr.Checkbox(value=default_value, label=f"{name}-{param}"))
|
||||
if _id in shared.settings:
|
||||
extension.params[param] = shared.settings[_id]
|
||||
|
||||
update_extensions_parameters(*default_values)
|
||||
btn_extensions = gr.Button("Apply")
|
||||
btn_extensions.click(update_extensions_parameters, [*extensions_ui_elements], [])
|
||||
# Creating the extension ui elements
|
||||
for extension, name in iterator():
|
||||
if hasattr(extension, "ui"):
|
||||
extension.ui()
|
||||
|
||||
@ -117,7 +117,7 @@ def load_model(model_name):
|
||||
model = eval(command)
|
||||
|
||||
# Loading the tokenizer
|
||||
if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')) and Path(f"models/gpt-j-6B/").exists():
|
||||
if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')) and Path("models/gpt-j-6B/").exists():
|
||||
tokenizer = AutoTokenizer.from_pretrained(Path("models/gpt-j-6B/"))
|
||||
else:
|
||||
tokenizer = AutoTokenizer.from_pretrained(Path(f"models/{shared.model_name}/"))
|
||||
|
||||
@ -11,6 +11,12 @@ history = {'internal': [], 'visible': []}
|
||||
character = 'None'
|
||||
stop_everything = False
|
||||
|
||||
# UI elements (buttons, sliders, HTML, etc)
|
||||
gradio = {}
|
||||
|
||||
# Generation input parameters
|
||||
input_params = []
|
||||
|
||||
settings = {
|
||||
'max_new_tokens': 200,
|
||||
'max_new_tokens_min': 1,
|
||||
@ -25,6 +31,9 @@ settings = {
|
||||
'chat_prompt_size': 2048,
|
||||
'chat_prompt_size_min': 0,
|
||||
'chat_prompt_size_max': 2048,
|
||||
'chat_generation_attempts': 1,
|
||||
'chat_generation_attempts_min': 1,
|
||||
'chat_generation_attempts_max': 5,
|
||||
'preset_pygmalion': 'Pygmalion',
|
||||
'name1_pygmalion': 'You',
|
||||
'name2_pygmalion': 'Kawaii',
|
||||
@ -37,7 +46,6 @@ parser.add_argument('--model', type=str, help='Name of the model to load by defa
|
||||
parser.add_argument('--notebook', action='store_true', help='Launch the web UI in notebook mode, where the output is written to the same text box as the input.')
|
||||
parser.add_argument('--chat', action='store_true', help='Launch the web UI in chat mode.')
|
||||
parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI in chat mode with a style similar to Character.AI\'s. If the file img_bot.png or img_bot.jpg exists in the same folder as server.py, this image will be used as the bot\'s profile picture. Similarly, img_me.png or img_me.jpg will be used as your profile picture.')
|
||||
parser.add_argument('--picture', action='store_true', help='Adds an ability to send pictures in chat UI modes. Captions are generated by BLIP.')
|
||||
parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.')
|
||||
parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.')
|
||||
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
|
||||
|
||||
@ -72,14 +72,14 @@ def formatted_outputs(reply, model_name):
|
||||
else:
|
||||
return reply
|
||||
|
||||
def generate_reply(question, 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, eos_token=None, stopping_string=None):
|
||||
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):
|
||||
original_question = question
|
||||
if not (shared.args.chat or shared.args.cai_chat):
|
||||
question = apply_extensions(question, "input")
|
||||
if shared.args.verbose:
|
||||
print(f"\n\n{question}\n--------------------\n")
|
||||
|
||||
input_ids = encode(question, tokens)
|
||||
input_ids = encode(question, max_new_tokens)
|
||||
cuda = "" if (shared.args.cpu or shared.args.deepspeed or shared.args.flexgen) else ".cuda()"
|
||||
if not shared.args.flexgen:
|
||||
n = shared.tokenizer.eos_token_id if eos_token is None else shared.tokenizer.encode(eos_token, return_tensors='pt')[0][-1]
|
||||
@ -126,9 +126,9 @@ def generate_reply(question, tokens, do_sample, max_new_tokens, temperature, top
|
||||
if shared.args.deepspeed:
|
||||
generate_params.append("synced_gpus=True")
|
||||
if shared.args.no_stream:
|
||||
generate_params.append(f"max_new_tokens=tokens")
|
||||
generate_params.append("max_new_tokens=max_new_tokens")
|
||||
else:
|
||||
generate_params.append(f"max_new_tokens=8")
|
||||
generate_params.append("max_new_tokens=8")
|
||||
|
||||
if shared.soft_prompt:
|
||||
inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)
|
||||
@ -156,7 +156,7 @@ def generate_reply(question, tokens, do_sample, max_new_tokens, temperature, top
|
||||
# Generate the reply 8 tokens at a time
|
||||
else:
|
||||
yield formatted_outputs(original_question, shared.model_name)
|
||||
for i in tqdm(range(tokens//8+1)):
|
||||
for i in tqdm(range(max_new_tokens//8+1)):
|
||||
with torch.no_grad():
|
||||
output = eval(f"shared.model.generate({', '.join(generate_params)}){cuda}")[0]
|
||||
if shared.soft_prompt:
|
||||
|
||||
267
server.py
267
server.py
@ -19,7 +19,7 @@ from modules.models import load_model, load_soft_prompt
|
||||
from modules.text_generation import generate_reply
|
||||
|
||||
if (shared.args.chat or shared.args.cai_chat) and not shared.args.no_stream:
|
||||
print("Warning: chat mode currently becomes somewhat slower with text streaming on.\nConsider starting the web UI with the --no-stream option.\n")
|
||||
print('Warning: chat mode currently becomes somewhat slower with text streaming on.\nConsider starting the web UI with the --no-stream option.\n')
|
||||
|
||||
# Loading custom settings
|
||||
if shared.args.settings is not None and Path(shared.args.settings).exists():
|
||||
@ -34,13 +34,13 @@ def get_available_presets():
|
||||
return sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('presets').glob('*.txt'))), key=str.lower)
|
||||
|
||||
def get_available_characters():
|
||||
return ["None"] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('characters').glob('*.json'))), key=str.lower)
|
||||
return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('characters').glob('*.json'))), key=str.lower)
|
||||
|
||||
def get_available_extensions():
|
||||
return sorted(set(map(lambda x : x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower)
|
||||
|
||||
def get_available_softprompts():
|
||||
return ["None"] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower)
|
||||
return ['None'] + sorted(set(map(lambda x : '.'.join(str(x.name).split('.')[:-1]), Path('softprompts').glob('*.zip'))), key=str.lower)
|
||||
|
||||
def load_model_wrapper(selected_model):
|
||||
if selected_model != shared.model_name:
|
||||
@ -100,50 +100,49 @@ def create_settings_menus():
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
model_menu = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model')
|
||||
ui.create_refresh_button(model_menu, lambda : None, lambda : {"choices": get_available_models()}, "refresh-button")
|
||||
shared.gradio['model_menu'] = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model')
|
||||
ui.create_refresh_button(shared.gradio['model_menu'], lambda : None, lambda : {'choices': get_available_models()}, 'refresh-button')
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
preset_menu = gr.Dropdown(choices=available_presets, value=shared.settings[f'preset{suffix}'] if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
|
||||
ui.create_refresh_button(preset_menu, lambda : None, lambda : {"choices": get_available_presets()}, "refresh-button")
|
||||
shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=shared.settings[f'preset{suffix}'] 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.Accordion('Custom generation parameters', open=False, elem_id='accordion'):
|
||||
with gr.Row():
|
||||
do_sample = gr.Checkbox(value=generate_params['do_sample'], label="do_sample")
|
||||
temperature = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label="temperature")
|
||||
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
|
||||
shared.gradio['temperature'] = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label='temperature')
|
||||
with gr.Row():
|
||||
top_k = gr.Slider(0,200,value=generate_params['top_k'],step=1,label="top_k")
|
||||
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['top_p'] = gr.Slider(0.0,1.0,value=generate_params['top_p'],step=0.01,label='top_p')
|
||||
with gr.Row():
|
||||
repetition_penalty = gr.Slider(1.0,4.99,value=generate_params['repetition_penalty'],step=0.01,label="repetition_penalty")
|
||||
no_repeat_ngram_size = gr.Slider(0, 20, step=1, value=generate_params["no_repeat_ngram_size"], label="no_repeat_ngram_size")
|
||||
shared.gradio['repetition_penalty'] = gr.Slider(1.0,4.99,value=generate_params['repetition_penalty'],step=0.01,label='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')
|
||||
with gr.Row():
|
||||
typical_p = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label="typical_p")
|
||||
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['typical_p'] = gr.Slider(0.0,1.0,value=generate_params['typical_p'],step=0.01,label='typical_p')
|
||||
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)
|
||||
|
||||
gr.Markdown("Contrastive search:")
|
||||
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')
|
||||
|
||||
gr.Markdown("Beam search (uses a lot of VRAM):")
|
||||
gr.Markdown('Beam search (uses a lot of VRAM):')
|
||||
with gr.Row():
|
||||
num_beams = gr.Slider(1, 20, step=1, value=generate_params["num_beams"], label="num_beams")
|
||||
length_penalty = gr.Slider(-5, 5, value=generate_params["length_penalty"], label="length_penalty")
|
||||
early_stopping = gr.Checkbox(value=generate_params["early_stopping"], label="early_stopping")
|
||||
shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
|
||||
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.Accordion("Soft prompt", open=False, elem_id="accordion"):
|
||||
with gr.Accordion('Soft prompt', open=False, elem_id='accordion'):
|
||||
with gr.Row():
|
||||
softprompts_menu = gr.Dropdown(choices=available_softprompts, value="None", label='Soft prompt')
|
||||
ui.create_refresh_button(softprompts_menu, lambda : None, lambda : {"choices": get_available_softprompts()}, "refresh-button")
|
||||
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')
|
||||
|
||||
gr.Markdown('Upload a soft prompt (.zip format):')
|
||||
with gr.Row():
|
||||
upload_softprompt = gr.File(type='binary', file_types=[".zip"])
|
||||
shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
|
||||
|
||||
model_menu.change(load_model_wrapper, [model_menu], [model_menu], show_progress=True)
|
||||
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])
|
||||
softprompts_menu.change(load_soft_prompt, [softprompts_menu], [softprompts_menu], show_progress=True)
|
||||
upload_softprompt.upload(upload_soft_prompt, [upload_softprompt], [softprompts_menu])
|
||||
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
|
||||
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['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']])
|
||||
|
||||
available_models = get_available_models()
|
||||
available_presets = get_available_presets()
|
||||
@ -159,25 +158,24 @@ if shared.args.model is not None:
|
||||
shared.model_name = shared.args.model
|
||||
else:
|
||||
if len(available_models) == 0:
|
||||
print("No models are available! Please download at least one.")
|
||||
print('No models are available! Please download at least one.')
|
||||
sys.exit(0)
|
||||
elif len(available_models) == 1:
|
||||
i = 0
|
||||
else:
|
||||
print("The following models are available:\n")
|
||||
print('The following models are available:\n')
|
||||
for i, model in enumerate(available_models):
|
||||
print(f"{i+1}. {model}")
|
||||
print(f"\nWhich one do you want to load? 1-{len(available_models)}\n")
|
||||
print(f'{i+1}. {model}')
|
||||
print(f'\nWhich one do you want to load? 1-{len(available_models)}\n')
|
||||
i = int(input())-1
|
||||
print()
|
||||
shared.model_name = available_models[i]
|
||||
shared.model, shared.tokenizer = load_model(shared.model_name)
|
||||
|
||||
# UI settings
|
||||
buttons = {}
|
||||
gen_events = []
|
||||
suffix = '_pygmalion' if 'pygmalion' in shared.model_name.lower() else ''
|
||||
description = f"\n\n# Text generation lab\nGenerate text using Large Language Models.\n"
|
||||
description = '\n\n# Text generation lab\nGenerate text using Large Language Models.\n'
|
||||
if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')):
|
||||
default_text = shared.settings['prompt_gpt4chan']
|
||||
elif re.match('(rosey|chip|joi)_.*_instruct.*', shared.model_name.lower()) is not None:
|
||||
@ -186,176 +184,169 @@ else:
|
||||
default_text = shared.settings['prompt']
|
||||
|
||||
if shared.args.chat or shared.args.cai_chat:
|
||||
with gr.Blocks(css=ui.css+ui.chat_css, analytics_enabled=False) as interface:
|
||||
interface.load(lambda : chat.load_default_history(shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}']), None, None)
|
||||
with gr.Blocks(css=ui.css+ui.chat_css, analytics_enabled=False) as shared.gradio['interface']:
|
||||
if shared.args.cai_chat:
|
||||
display = gr.HTML(value=generate_chat_html(shared.history['visible'], shared.settings[f'name1{suffix}'], shared.settings[f'name2{suffix}'], shared.character))
|
||||
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:
|
||||
display = gr.Chatbot(value=shared.history['visible'])
|
||||
textbox = gr.Textbox(label='Input')
|
||||
shared.gradio['display'] = gr.Chatbot(value=shared.history['visible'])
|
||||
shared.gradio['textbox'] = gr.Textbox(label='Input')
|
||||
with gr.Row():
|
||||
buttons["Stop"] = gr.Button("Stop")
|
||||
buttons["Generate"] = gr.Button("Generate")
|
||||
buttons["Regenerate"] = gr.Button("Regenerate")
|
||||
shared.gradio['Stop'] = gr.Button('Stop')
|
||||
shared.gradio['Generate'] = gr.Button('Generate')
|
||||
shared.gradio['Regenerate'] = gr.Button('Regenerate')
|
||||
with gr.Row():
|
||||
buttons["Impersonate"] = gr.Button("Impersonate")
|
||||
buttons["Remove last"] = gr.Button("Remove last")
|
||||
buttons["Clear history"] = gr.Button("Clear history")
|
||||
shared.gradio['Impersonate'] = gr.Button('Impersonate')
|
||||
shared.gradio['Remove last'] = gr.Button('Remove last')
|
||||
shared.gradio['Clear history'] = gr.Button('Clear history')
|
||||
with gr.Row():
|
||||
buttons["Send last reply to input"] = gr.Button("Send last reply to input")
|
||||
buttons["Replace last reply"] = gr.Button("Replace last reply")
|
||||
if shared.args.picture:
|
||||
shared.gradio['Send last reply to input'] = gr.Button('Send last reply to input')
|
||||
shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
|
||||
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=2, label='Context')
|
||||
with gr.Row():
|
||||
picture_select = gr.Image(label="Send a picture", type='pil')
|
||||
|
||||
with gr.Tab("Chat settings"):
|
||||
name1 = gr.Textbox(value=shared.settings[f'name1{suffix}'], lines=1, label='Your name')
|
||||
name2 = gr.Textbox(value=shared.settings[f'name2{suffix}'], lines=1, label='Bot\'s name')
|
||||
context = gr.Textbox(value=shared.settings[f'context{suffix}'], lines=2, label='Context')
|
||||
with gr.Row():
|
||||
character_menu = gr.Dropdown(choices=available_characters, value="None", label='Character')
|
||||
ui.create_refresh_button(character_menu, lambda : None, lambda : {"choices": get_available_characters()}, "refresh-button")
|
||||
shared.gradio['character_menu'] = gr.Dropdown(choices=available_characters, value='None', label='Character')
|
||||
ui.create_refresh_button(shared.gradio['character_menu'], lambda : None, lambda : {'choices': get_available_characters()}, 'refresh-button')
|
||||
|
||||
with gr.Row():
|
||||
check = gr.Checkbox(value=shared.settings[f'stop_at_newline{suffix}'], label='Stop generating at new line character?')
|
||||
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')
|
||||
upload_chat_history = gr.File(type='binary', file_types=[".json", ".txt"])
|
||||
shared.gradio['upload_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'])
|
||||
with gr.Column():
|
||||
gr.Markdown('Download')
|
||||
download = gr.File()
|
||||
buttons["Download"] = gr.Button(value="Click me")
|
||||
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')
|
||||
upload_char = gr.File(type='binary', file_types=[".json"])
|
||||
shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json'])
|
||||
with gr.Column():
|
||||
gr.Markdown('2. Select your character\'s profile picture (optional)')
|
||||
upload_img = gr.File(type='binary', file_types=["image"])
|
||||
buttons["Upload character"] = gr.Button(value="Submit")
|
||||
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'):
|
||||
upload_img_me = gr.File(type='binary', file_types=["image"])
|
||||
shared.gradio['upload_img_me'] = gr.File(type='binary', file_types=['image'])
|
||||
with gr.Tab('Upload TavernAI Character Card'):
|
||||
upload_img_tavern = gr.File(type='binary', file_types=["image"])
|
||||
shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
|
||||
|
||||
with gr.Tab("Generation settings"):
|
||||
with gr.Tab('Generation settings'):
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
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['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():
|
||||
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'])
|
||||
|
||||
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()
|
||||
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')
|
||||
create_settings_menus()
|
||||
|
||||
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"):
|
||||
with gr.Tab('Extensions'):
|
||||
extensions_module.create_extensions_block()
|
||||
|
||||
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]
|
||||
if shared.args.picture:
|
||||
input_params.append(picture_select)
|
||||
function_call = "chat.cai_chatbot_wrapper" if shared.args.cai_chat else "chat.chatbot_wrapper"
|
||||
function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
|
||||
|
||||
gen_events.append(buttons["Generate"].click(eval(function_call), input_params, display, show_progress=shared.args.no_stream, api_name="textgen"))
|
||||
gen_events.append(textbox.submit(eval(function_call), input_params, display, show_progress=shared.args.no_stream))
|
||||
if shared.args.picture:
|
||||
picture_select.upload(eval(function_call), input_params, display, show_progress=shared.args.no_stream)
|
||||
gen_events.append(buttons["Regenerate"].click(chat.regenerate_wrapper, input_params, display, show_progress=shared.args.no_stream))
|
||||
gen_events.append(buttons["Impersonate"].click(chat.impersonate_wrapper, input_params, textbox, show_progress=shared.args.no_stream))
|
||||
buttons["Stop"].click(chat.stop_everything_event, [], [], cancels=gen_events)
|
||||
gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream, api_name='textgen'))
|
||||
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)
|
||||
|
||||
buttons["Send last reply to input"].click(chat.send_last_reply_to_input, [], textbox, show_progress=shared.args.no_stream)
|
||||
buttons["Replace last reply"].click(chat.replace_last_reply, [textbox, name1, name2], display, show_progress=shared.args.no_stream)
|
||||
buttons["Clear history"].click(chat.clear_chat_log, [name1, name2], display)
|
||||
buttons["Remove last"].click(chat.remove_last_message, [name1, name2], [display, textbox], show_progress=False)
|
||||
buttons["Download"].click(chat.save_history, inputs=[], outputs=[download])
|
||||
buttons["Upload character"].click(chat.upload_character, [upload_char, upload_img], [character_menu])
|
||||
shared.gradio['Send last reply to input'].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)
|
||||
shared.gradio['Clear history'].click(chat.clear_chat_log, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
|
||||
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"]:
|
||||
buttons[i].click(lambda x: "", textbox, textbox, show_progress=False)
|
||||
buttons[i].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
|
||||
buttons["Clear history"].click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
|
||||
textbox.submit(lambda x: "", textbox, textbox, show_progress=False)
|
||||
textbox.submit(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
|
||||
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'].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)
|
||||
|
||||
character_menu.change(chat.load_character, [character_menu, name1, name2], [name2, context, display])
|
||||
upload_chat_history.upload(chat.load_history, [upload_chat_history, name1, name2], [])
|
||||
upload_img_tavern.upload(chat.upload_tavern_character, [upload_img_tavern, name1, name2], [character_menu])
|
||||
upload_img_me.upload(chat.upload_your_profile_picture, [upload_img_me], [])
|
||||
if shared.args.picture:
|
||||
picture_select.upload(lambda : None, [], [picture_select], 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 = [name1, name2] if shared.args.cai_chat else []
|
||||
upload_chat_history.upload(reload_func, reload_inputs, [display])
|
||||
upload_img_me.upload(reload_func, reload_inputs, [display])
|
||||
interface.load(reload_func, reload_inputs, [display], show_progress=True)
|
||||
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['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) as interface:
|
||||
with gr.Blocks(css=ui.css, analytics_enabled=False) as shared.gradio['interface']:
|
||||
gr.Markdown(description)
|
||||
with gr.Tab('Raw'):
|
||||
textbox = gr.Textbox(value=default_text, lines=23)
|
||||
shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=23)
|
||||
with gr.Tab('Markdown'):
|
||||
markdown = gr.Markdown()
|
||||
shared.gradio['markdown'] = gr.Markdown()
|
||||
with gr.Tab('HTML'):
|
||||
html = gr.HTML()
|
||||
shared.gradio['html'] = gr.HTML()
|
||||
|
||||
buttons["Generate"] = gr.Button("Generate")
|
||||
buttons["Stop"] = gr.Button("Stop")
|
||||
|
||||
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'])
|
||||
|
||||
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()
|
||||
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()
|
||||
if shared.args.extensions is not None:
|
||||
extensions_module.create_extensions_block()
|
||||
|
||||
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"))
|
||||
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))
|
||||
buttons["Stop"].click(None, None, None, cancels=gen_events)
|
||||
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) as interface:
|
||||
with gr.Blocks(css=ui.css, analytics_enabled=False) as shared.gradio['interface']:
|
||||
gr.Markdown(description)
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
textbox = gr.Textbox(value=default_text, lines=15, label='Input')
|
||||
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'])
|
||||
buttons["Generate"] = gr.Button("Generate")
|
||||
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():
|
||||
buttons["Continue"] = gr.Button("Continue")
|
||||
shared.gradio['Continue'] = gr.Button('Continue')
|
||||
with gr.Column():
|
||||
buttons["Stop"] = gr.Button("Stop")
|
||||
shared.gradio['Stop'] = gr.Button('Stop')
|
||||
|
||||
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()
|
||||
create_settings_menus()
|
||||
if shared.args.extensions is not None:
|
||||
extensions_module.create_extensions_block()
|
||||
|
||||
with gr.Column():
|
||||
with gr.Tab('Raw'):
|
||||
output_textbox = gr.Textbox(lines=15, label='Output')
|
||||
shared.gradio['output_textbox'] = gr.Textbox(lines=15, label='Output')
|
||||
with gr.Tab('Markdown'):
|
||||
markdown = gr.Markdown()
|
||||
shared.gradio['markdown'] = gr.Markdown()
|
||||
with gr.Tab('HTML'):
|
||||
html = gr.HTML()
|
||||
shared.gradio['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)
|
||||
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)
|
||||
|
||||
interface.queue()
|
||||
shared.gradio['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)
|
||||
shared.gradio['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)
|
||||
shared.gradio['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:
|
||||
|
||||
@ -12,6 +12,9 @@
|
||||
"chat_prompt_size": 2048,
|
||||
"chat_prompt_size_min": 0,
|
||||
"chat_prompt_size_max": 2048,
|
||||
"chat_generation_attempts": 1,
|
||||
"chat_generation_attempts_min": 1,
|
||||
"chat_generation_attempts_max": 5,
|
||||
"preset_pygmalion": "Pygmalion",
|
||||
"name1_pygmalion": "You",
|
||||
"name2_pygmalion": "Kawaii",
|
||||
|
||||
Loading…
Reference in New Issue
Block a user