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new playground

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Saifeddine ALOUI 2023-08-19 03:25:27 +02:00
parent beabc2e6fd
commit ac2c8326e8
19 changed files with 3949 additions and 120 deletions
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lollms/apps/create/.vite/deps_temp_0b6cd151/package.json Normal file
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{
"type": "module"
}

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lollms/apps/create/.vite/deps_temp_889a01ff/package.json Normal file
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{
"type": "module"
}

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lollms/apps/playground2/.env.development Normal file
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VITE_LOLLMS_API = http://127.0.0.1:9601 # http://localhost:9600
VITE_LOLLMS_API_CHANGE_ORIGIN = 1 # FALSE
VITE_LOLLMS_API_SECURE = 0 # FALSE
VITE_LOLLMS_API_BASEURL = /api/ # FALSE

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lollms/apps/playground2/.eslintrc.cjs Normal file
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/* eslint-env node */
require('@rushstack/eslint-patch/modern-module-resolution')
module.exports = {
root: true,
'extends': [
'plugin:vue/vue3-essential',
'eslint:recommended',
'@vue/eslint-config-prettier/skip-formatting'
],
parserOptions: {
ecmaVersion: 'latest'
}
}

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# Logs
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
lerna-debug.log*
node_modules
.DS_Store
dist-ssr
coverage
*.local
/cypress/videos/
/cypress/screenshots/
# Editor directories and files
.vscode
!.vscode/extensions.json
.idea
*.suo
*.ntvs*
*.njsproj
*.sln
*.sw?
# REST Client files (VSCODE extension for making GET POST requests easy and fst from text files)
*.http

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lollms/apps/playground2/.prettierrc.json Normal file
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{
"$schema": "https://json.schemastore.org/prettierrc",
"semi": false,
"tabWidth": 2,
"singleQuote": true,
"printWidth": 100,
"trailingComma": "none"
}

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Apache License
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END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
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Copyright 2023 Saifeddine ALOUI (aka parisneo)
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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See the License for the specific language governing permissions and
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40
lollms/apps/playground2/__init__.py Normal file
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from flask import Flask, send_from_directory, request
import json
import os
app = Flask(__name__, static_folder='dist/')
@app.route('/')
def index():
return app.send_static_file('index.html')
@app.route('/<path:filename>')
def serve_file(filename):
root_dir = "dist/"
return send_from_directory(root_dir, filename)
@app.route("/save_preset", methods=["POST"])
def save_preset():
"""Saves a preset to a file.
Args:
None.
Returns:
None.
"""
# Get the JSON data from the POST request.
preset_data = request.get_json()
# Save the JSON data to a file.
with open("presets.json", "w") as f:
json.dump(preset_data, f)
return "Preset saved successfully!"
def main():
app.run()
if __name__ == '__main__':
main()

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lollms/apps/playground2/index.html Normal file
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<link rel="icon" href="/favicon.ico">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>LoLLMS Playground WebUI - Welcome</title>
</head>
<body>
<div id="app"></div>
<script type="module" src="/src/main.js"></script>
</body>
</html>

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{
"name": "lollms-playground-vue",
"version": "0.0.0",
"private": true,
"scripts": {
"dev": "vite",
"build": "vite build",
"preview": "vite preview",
"lint": "eslint . --ext .vue,.js,.jsx,.cjs,.mjs --fix --ignore-path .gitignore",
"format": "prettier --write src/"
},
"dependencies": {
"axios": "^1.3.6",
"feather-icons": "^4.29.0",
"flowbite": "^1.6.5",
"flowbite-vue": "^0.0.10",
"highlight.js": "^11.8.0",
"markdown-it": "^13.0.1",
"markdown-it-anchor": "^8.6.7",
"markdown-it-attrs": "^4.1.6",
"markdown-it-emoji": "^2.0.2",
"markdown-it-implicit-figures": "^0.11.0",
"markdown-it-multimd-table": "^4.2.2",
"papaparse": "^5.4.1",
"prismjs": "^1.29.0",
"socket.io-client": "^4.6.1",
"vue": "^3.2.47",
"vue-router": "^4.1.6",
"vuex": "^4.0.2"
},
"devDependencies": {
"@rushstack/eslint-patch": "^1.2.0",
"@vitejs/plugin-vue": "^4.0.0",
"@vue/eslint-config-prettier": "^7.1.0",
"autoprefixer": "^10.4.14",
"eslint": "^8.34.0",
"eslint-plugin-vue": "^9.9.0",
"postcss": "^8.4.23",
"prettier": "^2.8.4",
"tailwind-scrollbar": "^3.0.1",
"tailwindcss": "^3.3.1",
"vite": "^4.1.4"
}
}

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module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}

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{
"preset1" : "Once apon a time",
"preset2" : "1+1="
}

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lollms/apps/playground2/tailwind.config.js Normal file
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/** @type {import('tailwindcss').Config} */
module.exports = {
content: [
'./index.html',
'./src/**/*.{vue,js,ts,jsx,tsx}',
'node_modules/flowbite-vue/**/*.{js,jsx,ts,tsx}'
],
darkMode: 'class',
theme: {
extend: {
colors: {
primary: '#0e8ef0',
'primary-light': '#3dabff',
secondary: '#0fd974',
accent: '#f0700e',
'bg-dark': '#132e59',
'bg-dark-tone': '#25477d',
'bg-dark-tone-panel': '#4367a3',
'bg-dark-code-block': '#2254a7',
'bg-light': '#e2edff',
'bg-light-tone': '#b9d2f7',
'bg-light-code-block': '#cad7ed',
'bg-light-tone-panel': '#8fb5ef',
'bg-dark-discussion': '#435E8A',
'bg-dark-discussion-odd': '#284471',
'bg-light-discussion': '#c5d8f8',
'bg-light-discussion-odd': '#d6e7ff'
},
fontFamily: {
sans: ['PTSans', 'Roboto', 'sans-serif']
},
container: {
padding: '2rem',
center: true
}
}
},
plugins: [require('flowbite/plugin'), require('tailwind-scrollbar')]
}

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lollms/apps/playground2/vite.config.mjs Normal file
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import { fileURLToPath, URL } from 'node:url'
import { defineConfig,loadEnv } from 'vite'
import vue from '@vitejs/plugin-vue'
// https://vitejs.dev/config/
export default ({ mode }) => {
// Load app-level env vars to node-level env vars.
process.env = {...process.env, ...loadEnv(mode, process.cwd())};
return defineConfig({
plugins: [
vue()
],
resolve: {
alias: {
'@': fileURLToPath(new URL('./src', import.meta.url))
}
},
server: {
serveStatic: {
// This will force Vite to serve the YAML file.
paths: ['./presets.json'],
},
proxy: {
"/api/": {
target: process.env.VITE_LOLLMS_API,
changeOrigin: process.env.VITE_LOLLMS_API_CHANGE_ORIGIN,
secure: process.env.VITE_LOLLMS_API_SECURE,
rewrite: (path) => path.replace(/^\/api/, ""),
},
// "/": {
// target: process.env.VITE_LOLLMS_API,
// changeOrigin: process.env.VITE_LOLLMS_API_CHANGE_ORIGIN,
// secure: process.env.VITE_LOLLMS_API_SECURE,
// },
},
}
})}

249
lollms/apps/server/__init__.py
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@ -1,5 +1,5 @@
from lollms.config import InstallOption
from flask import Flask, request
from flask import Flask, request, jsonify
from flask_socketio import SocketIO, emit
from flask_cors import CORS
from lollms.types import MSG_TYPE
@ -12,7 +12,7 @@ from lollms.apps.console import MainMenu
from lollms.paths import LollmsPaths
from lollms.apps.console import MainMenu
from lollms.app import LollmsApplication
from lollms.utilities import TextVectorizer
from lollms.utilities import TextVectorizer, trace_exception
from typing import List, Tuple
from typing import Callable
import importlib
@ -84,7 +84,13 @@ class LoLLMsServer(LollmsApplication):
self.app = Flask("LoLLMsServer")
#self.app.config['SECRET_KEY'] = 'lollmssecret'
CORS(self.app) # Enable CORS for all routes
def get_config(self):
ASCIIColors.yellow("Requested configuration")
return jsonify(self.config.to_dict())
self.app.add_url_rule(
"/get_config", "get_config", get_config, methods=["GET"]
)
self.socketio = SocketIO(self.app, cors_allowed_origins='*', ping_timeout=1200, ping_interval=4000)
# Set log level to warning
@ -118,6 +124,7 @@ class LoLLMsServer(LollmsApplication):
print(f'Client disconnected with session ID: {client_id}')
@self.socketio.on('list_available_bindings')
def handle_list_bindings():
binding_infs = []
@ -460,137 +467,143 @@ class LoLLMsServer(LollmsApplication):
return
def generate_text():
self.is_ready = False
model = self.model
self.clients[client_id]["is_generating"]=True
self.clients[client_id]["requested_stop"]=False
prompt = data['prompt']
personality_id = data['personality']
n_predicts = data["n_predicts"]
parameters = data.get("parameters",{
"temperature":self.config["temperature"],
"top_k":self.config["top_k"],
"top_p":self.config["top_p"],
"repeat_penalty":self.config["repeat_penalty"],
"repeat_last_n":self.config["repeat_last_n"],
"seed":self.config["seed"]
})
if personality_id==-1:
# Raw text generation
self.answer = {"full_text":""}
def callback(text, message_type: MSG_TYPE, metadata:dict={}):
if message_type == MSG_TYPE.MSG_TYPE_CHUNK:
ASCIIColors.success(f"generated:{len(self.answer['full_text'].split())} words", end='\r')
self.answer["full_text"] = self.answer["full_text"] + text
self.socketio.emit('text_chunk', {'chunk': text, 'type':MSG_TYPE.MSG_TYPE_CHUNK.value}, room=client_id)
self.socketio.sleep(0)
if client_id in self.clients:# Client disconnected
if self.clients[client_id]["requested_stop"]:
return False
else:
return True
else:
return False
tk = model.tokenize(prompt)
n_tokens = len(tk)
fd = model.detokenize(tk[-min(self.config.ctx_size-n_predicts,n_tokens):])
try:
ASCIIColors.print("warming up", ASCIIColors.color_bright_cyan)
generated_text = model.generate(fd,
n_predict=n_predicts,
callback=callback,
temperature = parameters["temperature"],
top_k = parameters["top_k"],
top_p = parameters["top_p"],
repeat_penalty = parameters["repeat_penalty"],
repeat_last_n = parameters["repeat_last_n"],
seed = parameters["seed"]
)
ASCIIColors.success(f"\ndone")
if client_id in self.clients:
if not self.clients[client_id]["requested_stop"]:
# Emit the generated text to the client
self.socketio.emit('text_generated', {'text': generated_text}, room=client_id)
self.socketio.sleep(0)
except Exception as ex:
self.socketio.emit('generation_error', {'error': str(ex)}, room=client_id)
ASCIIColors.error(f"\ndone")
self.is_ready = True
else:
try:
personality: AIPersonality = self.personalities[personality_id]
ump = self.config.discussion_prompt_separator +self.config.user_name+": " if self.config.use_user_name_in_discussions else self.personality.user_message_prefix
personality.model = model
cond_tk = personality.model.tokenize(personality.personality_conditioning)
n_cond_tk = len(cond_tk)
# Placeholder code for text generation
# Replace this with your actual text generation logic
print(f"Text generation requested by client: {client_id}")
self.answer["full_text"] = ''
full_discussion_blocks = self.clients[client_id]["full_discussion_blocks"]
if prompt != '':
if personality.processor is not None and personality.processor_cfg["process_model_input"]:
preprocessed_prompt = personality.processor.process_model_input(prompt)
else:
preprocessed_prompt = prompt
if personality.processor is not None and personality.processor_cfg["custom_workflow"]:
full_discussion_blocks.append(ump)
full_discussion_blocks.append(preprocessed_prompt)
else:
full_discussion_blocks.append(ump)
full_discussion_blocks.append(preprocessed_prompt)
full_discussion_blocks.append(personality.link_text)
full_discussion_blocks.append(personality.ai_message_prefix)
full_discussion = personality.personality_conditioning + ''.join(full_discussion_blocks)
try:
model = self.model
self.clients[client_id]["is_generating"]=True
self.clients[client_id]["requested_stop"]=False
prompt = data['prompt']
personality_id = data['personality']
n_predicts = data["n_predicts"]
parameters = data.get("parameters",{
"temperature":self.config["temperature"],
"top_k":self.config["top_k"],
"top_p":self.config["top_p"],
"repeat_penalty":self.config["repeat_penalty"],
"repeat_last_n":self.config["repeat_last_n"],
"seed":self.config["seed"]
})
if personality_id==-1:
# Raw text generation
self.answer = {"full_text":""}
def callback(text, message_type: MSG_TYPE, metadata:dict={}):
if message_type == MSG_TYPE.MSG_TYPE_CHUNK:
ASCIIColors.success(f"generated:{len(self.answer['full_text'].split())} words", end='\r')
self.answer["full_text"] = self.answer["full_text"] + text
self.socketio.emit('text_chunk', {'chunk': text}, room=client_id)
self.socketio.emit('text_chunk', {'chunk': text, 'type':MSG_TYPE.MSG_TYPE_CHUNK.value}, room=client_id)
self.socketio.sleep(0)
try:
if client_id in self.clients:# Client disconnected
if self.clients[client_id]["requested_stop"]:
return False
else:
return True
except: # If the client is disconnected then we stop talking to it
return False
else:
return False
tk = personality.model.tokenize(full_discussion)
tk = model.tokenize(prompt)
n_tokens = len(tk)
fd = personality.model.detokenize(tk[-min(self.config.ctx_size-n_cond_tk-personality.model_n_predicts,n_tokens):])
if personality.processor is not None and personality.processor_cfg["custom_workflow"]:
ASCIIColors.info("processing...")
generated_text = personality.processor.run_workflow(prompt, previous_discussion_text=personality.personality_conditioning+fd, callback=callback)
else:
ASCIIColors.info("generating...")
generated_text = personality.model.generate(
personality.personality_conditioning+fd,
n_predict=personality.model_n_predicts,
callback=callback)
fd = model.detokenize(tk[-min(self.config.ctx_size-n_predicts,n_tokens):])
if personality.processor is not None and personality.processor_cfg["process_model_output"]:
generated_text = personality.processor.process_model_output(generated_text)
try:
ASCIIColors.print("warming up", ASCIIColors.color_bright_cyan)
generated_text = model.generate(fd,
n_predict=n_predicts,
callback=callback,
temperature = parameters["temperature"],
top_k = parameters["top_k"],
top_p = parameters["top_p"],
repeat_penalty = parameters["repeat_penalty"],
repeat_last_n = parameters["repeat_last_n"],
seed = parameters["seed"]
)
ASCIIColors.success(f"\ndone")
if client_id in self.clients:
if not self.clients[client_id]["requested_stop"]:
# Emit the generated text to the client
self.socketio.emit('text_generated', {'text': generated_text}, room=client_id)
self.socketio.sleep(0)
except Exception as ex:
self.socketio.emit('generation_error', {'error': str(ex)}, room=client_id)
ASCIIColors.error(f"\ndone")
self.is_ready = True
else:
try:
personality: AIPersonality = self.personalities[personality_id]
ump = self.config.discussion_prompt_separator +self.config.user_name+": " if self.config.use_user_name_in_discussions else self.personality.user_message_prefix
personality.model = model
cond_tk = personality.model.tokenize(personality.personality_conditioning)
n_cond_tk = len(cond_tk)
# Placeholder code for text generation
# Replace this with your actual text generation logic
print(f"Text generation requested by client: {client_id}")
full_discussion_blocks.append(generated_text.strip())
ASCIIColors.success("\ndone")
self.answer["full_text"] = ''
full_discussion_blocks = self.clients[client_id]["full_discussion_blocks"]
# Emit the generated text to the client
self.socketio.emit('text_generated', {'text': generated_text}, room=client_id)
self.socketio.sleep(0)
except Exception as ex:
if prompt != '':
if personality.processor is not None and personality.processor_cfg["process_model_input"]:
preprocessed_prompt = personality.processor.process_model_input(prompt)
else:
preprocessed_prompt = prompt
if personality.processor is not None and personality.processor_cfg["custom_workflow"]:
full_discussion_blocks.append(ump)
full_discussion_blocks.append(preprocessed_prompt)
else:
full_discussion_blocks.append(ump)
full_discussion_blocks.append(preprocessed_prompt)
full_discussion_blocks.append(personality.link_text)
full_discussion_blocks.append(personality.ai_message_prefix)
full_discussion = personality.personality_conditioning + ''.join(full_discussion_blocks)
def callback(text, message_type: MSG_TYPE, metadata:dict={}):
if message_type == MSG_TYPE.MSG_TYPE_CHUNK:
self.answer["full_text"] = self.answer["full_text"] + text
self.socketio.emit('text_chunk', {'chunk': text}, room=client_id)
self.socketio.sleep(0)
try:
if self.clients[client_id]["requested_stop"]:
return False
else:
return True
except: # If the client is disconnected then we stop talking to it
return False
tk = personality.model.tokenize(full_discussion)
n_tokens = len(tk)
fd = personality.model.detokenize(tk[-min(self.config.ctx_size-n_cond_tk-personality.model_n_predicts,n_tokens):])
if personality.processor is not None and personality.processor_cfg["custom_workflow"]:
ASCIIColors.info("processing...")
generated_text = personality.processor.run_workflow(prompt, previous_discussion_text=personality.personality_conditioning+fd, callback=callback)
else:
ASCIIColors.info("generating...")
generated_text = personality.model.generate(
personality.personality_conditioning+fd,
n_predict=personality.model_n_predicts,
callback=callback)
if personality.processor is not None and personality.processor_cfg["process_model_output"]:
generated_text = personality.processor.process_model_output(generated_text)
full_discussion_blocks.append(generated_text.strip())
ASCIIColors.success("\ndone")
# Emit the generated text to the client
self.socketio.emit('text_generated', {'text': generated_text}, room=client_id)
self.socketio.sleep(0)
except Exception as ex:
self.socketio.emit('generation_error', {'error': str(ex)}, room=client_id)
ASCIIColors.error(f"\ndone")
self.is_ready = True
except Exception as ex:
trace_exception(ex)
self.socketio.emit('generation_error', {'error': str(ex)}, room=client_id)
ASCIIColors.error(f"\ndone")
self.is_ready = True
self.is_ready = True
# Start the text generation task in a separate thread
task = self.socketio.start_background_task(target=generate_text)

4
setup.py
View File

@ -26,7 +26,7 @@ def get_all_files(path):
setuptools.setup(
name="lollms",
version="3.0.0",
version="3.1.0",
author="Saifeddine ALOUI",
author_email="aloui.saifeddine@gmail.com",
description="A python library for AI personality definition",
@ -41,7 +41,7 @@ setuptools.setup(
'lollms-server = lollms.apps.server:main',
'lollms-console = lollms.apps.console:main',
'lollms-settings = lollms.apps.settings:main',
'lollms-playground = lollms.apps.playground:main'
'lollms-playground = lollms.apps.playground2:main'
],
},
extras_require={"dev": requirements_dev},