mirror of
https://github.com/ParisNeo/lollms-webui.git
synced 2024-12-23 22:32:24 +00:00
1599 lines
84 KiB
Python
1599 lines
84 KiB
Python
######
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# Project : lollms-webui
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# File : api.py
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# Author : ParisNeo with the help of the community
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# Supported by Nomic-AI
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# license : Apache 2.0
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# Description :
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# A simple api to communicate with lollms-webui and its models.
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######
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from flask import request
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from datetime import datetime
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from api.db import DiscussionsDB, Discussion
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from pathlib import Path
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from lollms.config import InstallOption
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from lollms.types import MSG_TYPE, SENDER_TYPES
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from lollms.extension import LOLLMSExtension, ExtensionBuilder
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from lollms.personality import AIPersonality, PersonalityBuilder
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from lollms.binding import LOLLMSConfig, BindingBuilder, LLMBinding, ModelBuilder
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from lollms.paths import LollmsPaths
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from lollms.helpers import ASCIIColors, trace_exception
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from lollms.app import LollmsApplication
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from lollms.utilities import File64BitsManager, PromptReshaper
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from safe_store import TextVectorizer, VectorizationMethod, VisualizationMethod
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import threading
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from tqdm import tqdm
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import traceback
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import sys
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import gc
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import ctypes
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from functools import partial
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import json
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import shutil
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import re
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import string
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import requests
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from datetime import datetime
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def terminate_thread(thread):
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if thread:
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if not thread.is_alive():
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ASCIIColors.yellow("Thread not alive")
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return
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thread_id = thread.ident
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exc = ctypes.py_object(SystemExit)
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res = ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id, exc)
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if res > 1:
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ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id, None)
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del thread
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gc.collect()
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raise SystemError("Failed to terminate the thread.")
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else:
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ASCIIColors.yellow("Canceled successfully")
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__author__ = "parisneo"
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__github__ = "https://github.com/ParisNeo/lollms-webui"
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__copyright__ = "Copyright 2023, "
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__license__ = "Apache 2.0"
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import subprocess
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import pkg_resources
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# ===========================================================
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# Manage automatic install scripts
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def is_package_installed(package_name):
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try:
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dist = pkg_resources.get_distribution(package_name)
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return True
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except pkg_resources.DistributionNotFound:
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return False
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def install_package(package_name):
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try:
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# Check if the package is already installed
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__import__(package_name)
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print(f"{package_name} is already installed.")
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except ImportError:
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print(f"{package_name} is not installed. Installing...")
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# Install the package using pip
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subprocess.check_call(["pip", "install", package_name])
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print(f"{package_name} has been successfully installed.")
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def parse_requirements_file(requirements_path):
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with open(requirements_path, 'r') as f:
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for line in f:
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line = line.strip()
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if not line or line.startswith('#'):
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# Skip empty and commented lines
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continue
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package_name, _, version_specifier = line.partition('==')
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package_name, _, version_specifier = line.partition('>=')
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if is_package_installed(package_name):
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# The package is already installed
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print(f"{package_name} is already installed.")
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else:
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# The package is not installed, install it
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if version_specifier:
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install_package(f"{package_name}{version_specifier}")
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else:
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install_package(package_name)
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# ===========================================================
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class LoLLMsAPPI(LollmsApplication):
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def __init__(self, config:LOLLMSConfig, socketio, config_file_path:str, lollms_paths: LollmsPaths) -> None:
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super().__init__("Lollms_webui",config, lollms_paths, callback=self.process_chunk)
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self.busy = False
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self.nb_received_tokens = 0
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self.socketio = socketio
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self.config_file_path = config_file_path
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self.cancel_gen = False
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# Keeping track of current discussion and message
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self._current_user_message_id = 0
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self._current_ai_message_id = 0
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self._message_id = 0
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self.db_path = config["db_path"]
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if Path(self.db_path).is_absolute():
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# Create database object
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self.db = DiscussionsDB(self.db_path)
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else:
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# Create database object
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self.db = DiscussionsDB(self.lollms_paths.personal_databases_path/self.db_path)
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# If the database is empty, populate it with tables
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ASCIIColors.info("Checking discussions database... ",end="")
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self.db.create_tables()
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self.db.add_missing_columns()
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ASCIIColors.success("ok")
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# prepare vectorization
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if self.config.data_vectorization_activate and self.config.use_discussions_history:
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try:
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ASCIIColors.yellow("Loading vectorized discussions")
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folder = self.lollms_paths.personal_databases_path/"vectorized_dbs"
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folder.mkdir(parents=True, exist_ok=True)
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self.discussions_store = TextVectorizer(
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vectorization_method=VectorizationMethod.TFIDF_VECTORIZER,#=VectorizationMethod.BM25_VECTORIZER,
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database_path=folder/self.config.db_path,
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data_visualization_method=VisualizationMethod.PCA,#VisualizationMethod.PCA,
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save_db=True
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)
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ASCIIColors.yellow("1- Exporting discussions")
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discussions = self.db.export_all_as_markdown_list_for_vectorization()
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ASCIIColors.yellow("2- Adding discussions to vectorizer")
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for (title,discussion) in discussions:
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if discussion!='' and title!='None':
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self.discussions_store.add_document(title, discussion, chunk_size=self.config.data_vectorization_chunk_size, overlap_size=self.config.data_vectorization_overlap_size, force_vectorize=False, add_as_a_bloc=False)
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ASCIIColors.yellow("3- Indexing database")
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self.discussions_store.index()
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ASCIIColors.yellow("3- Saving database")
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self.discussions_store.save_to_json()
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ASCIIColors.yellow("Ready")
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except Exception as ex:
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trace_exception(ex)
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self.discussions_store = None
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else:
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self.discussions_store = None
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# This is used to keep track of messages
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self.download_infos={}
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self.connections = {0:{
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"current_discussion":None,
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"generated_text":"",
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"cancel_generation": False,
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"generation_thread": None,
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"processing":False,
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"schedule_for_deletion":False
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}
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}
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# =========================================================================================
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# Socket IO stuff
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# =========================================================================================
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@socketio.on('connect')
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def connect():
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#Create a new connection information
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self.connections[request.sid] = {
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"current_discussion":self.db.load_last_discussion(),
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"generated_text":"",
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"continuing": False,
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"first_chunk": True,
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"cancel_generation": False,
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"generation_thread": None,
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"processing":False,
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"schedule_for_deletion":False
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}
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self.socketio.emit('connected', room=request.sid)
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ASCIIColors.success(f'Client {request.sid} connected')
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@socketio.on('disconnect')
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def disconnect():
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try:
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self.socketio.emit('disconnected', room=request.sid)
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if self.connections[request.sid]["processing"]:
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self.connections[request.sid]["schedule_for_deletion"]=True
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else:
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del self.connections[request.sid]
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except Exception as ex:
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pass
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ASCIIColors.error(f'Client {request.sid} disconnected')
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@socketio.on('cancel_install')
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def cancel_install(data):
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try:
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model_name = data["model_name"]
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binding_folder = data["binding_folder"]
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model_url = data["model_url"]
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signature = f"{model_name}_{binding_folder}_{model_url}"
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self.download_infos[signature]["cancel"]=True
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self.socketio.emit('canceled', {
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'status': True
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},
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room=request.sid
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)
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except Exception as ex:
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trace_exception(ex)
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self.socketio.emit('canceled', {
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'status': False,
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'error':str(ex)
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},
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room=request.sid
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)
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@socketio.on('install_model')
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def install_model(data):
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room_id = request.sid
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def install_model_():
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print("Install model triggered")
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model_path = data["path"].replace("\\","/")
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model_type:str=data["type"]
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progress = 0
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installation_dir = self.binding.searchModelParentFolder(model_path.split('/')[-1], model_type)
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if model_type=="gptq":
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parts = model_path.split("/")
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if len(parts)==2:
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filename = parts[1]
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else:
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filename = parts[4]
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installation_path = installation_dir / filename
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else:
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filename = Path(model_path).name
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installation_path = installation_dir / filename
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print("Model install requested")
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print(f"Model path : {model_path}")
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model_name = filename
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binding_folder = self.config["binding_name"]
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model_url = model_path
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signature = f"{model_name}_{binding_folder}_{model_url}"
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try:
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self.download_infos[signature]={
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"start_time":datetime.now(),
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"total_size":self.binding.get_file_size(model_path),
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"downloaded_size":0,
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"progress":0,
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"speed":0,
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"cancel":False
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}
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if installation_path.exists():
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print("Error: Model already exists. please remove it first")
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socketio.emit('install_progress',{
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'status': False,
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'error': f'model already exists. Please remove it first.\nThe model can be found here:{installation_path}',
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': self.download_infos[signature]['progress'],
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id
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)
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socketio.emit('install_progress',{
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'status': True,
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'progress': progress,
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': self.download_infos[signature]['progress'],
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id)
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def callback(downloaded_size, total_size):
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progress = (downloaded_size / total_size) * 100
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now = datetime.now()
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dt = (now - self.download_infos[signature]['start_time']).total_seconds()
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speed = downloaded_size/dt
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self.download_infos[signature]['downloaded_size'] = downloaded_size
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self.download_infos[signature]['speed'] = speed
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if progress - self.download_infos[signature]['progress']>2:
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self.download_infos[signature]['progress'] = progress
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socketio.emit('install_progress',{
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'status': True,
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': self.download_infos[signature]['progress'],
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id)
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if self.download_infos[signature]["cancel"]:
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raise Exception("canceled")
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if hasattr(self.binding, "download_model"):
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try:
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self.binding.download_model(model_path, installation_path, callback)
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except Exception as ex:
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ASCIIColors.warning(str(ex))
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trace_exception(ex)
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socketio.emit('install_progress',{
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'status': False,
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'error': 'canceled',
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': self.download_infos[signature]['progress'],
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id
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)
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del self.download_infos[signature]
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try:
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if installation_path.is_dir():
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shutil.rmtree(installation_path)
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else:
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installation_path.unlink()
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except Exception as ex:
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trace_exception(ex)
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ASCIIColors.error(f"Couldn't delete file. Please try to remove it manually.\n{installation_path}")
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return
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else:
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try:
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self.download_file(model_path, installation_path, callback)
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except Exception as ex:
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ASCIIColors.warning(str(ex))
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trace_exception(ex)
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socketio.emit('install_progress',{
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'status': False,
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'error': 'canceled',
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': self.download_infos[signature]['progress'],
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id
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)
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del self.download_infos[signature]
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installation_path.unlink()
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return
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socketio.emit('install_progress',{
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'status': True,
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'error': '',
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': self.download_infos[signature]['start_time'].strftime("%Y-%m-%d %H:%M:%S"),
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'total_size': self.download_infos[signature]['total_size'],
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'downloaded_size': self.download_infos[signature]['downloaded_size'],
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'progress': 100,
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'speed': self.download_infos[signature]['speed'],
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}, room=room_id)
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del self.download_infos[signature]
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except Exception as ex:
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trace_exception(ex)
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socketio.emit('install_progress',{
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'status': False,
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'error': str(ex),
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'model_name' : model_name,
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'binding_folder' : binding_folder,
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'model_url' : model_url,
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'start_time': '',
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'total_size': 0,
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'downloaded_size': 0,
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'progress': 0,
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'speed': 0,
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}, room=room_id
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)
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tpe = threading.Thread(target=install_model_, args=())
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tpe.start()
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@socketio.on('uninstall_model')
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def uninstall_model(data):
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model_path = data['path']
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model_type:str=data.get("type","ggml")
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installation_dir = self.binding.searchModelParentFolder()
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binding_folder = self.config["binding_name"]
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if model_type=="gptq":
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filename = model_path.split("/")[4]
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installation_path = installation_dir / filename
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else:
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filename = Path(model_path).name
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installation_path = installation_dir / filename
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model_name = filename
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if not installation_path.exists():
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socketio.emit('uninstall_progress',{
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'status': False,
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'error': 'The model does not exist',
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'model_name' : model_name,
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'binding_folder' : binding_folder
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}, room=request.sid)
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try:
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if not installation_path.exists():
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# Try to find a version
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model_path = installation_path.name.lower().replace("-ggml","").replace("-gguf","")
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candidates = [m for m in installation_dir.iterdir() if model_path in m.name]
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if len(candidates)>0:
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model_path = candidates[0]
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installation_path = model_path
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|
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if installation_path.is_dir():
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shutil.rmtree(installation_path)
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else:
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installation_path.unlink()
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socketio.emit('uninstall_progress',{
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'status': True,
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'error': '',
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'model_name' : model_name,
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'binding_folder' : binding_folder
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}, room=request.sid)
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except Exception as ex:
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trace_exception(ex)
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ASCIIColors.error(f"Couldn't delete {installation_path}, please delete it manually and restart the app")
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socketio.emit('uninstall_progress',{
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'status': False,
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'error': f"Couldn't delete {installation_path}, please delete it manually and restart the app",
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'model_name' : model_name,
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'binding_folder' : binding_folder
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}, room=request.sid)
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|
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@socketio.on('new_discussion')
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def new_discussion(data):
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client_id = request.sid
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title = data["title"]
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self.connections[client_id]["current_discussion"] = self.db.create_discussion(title)
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# Get the current timestamp
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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|
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# Return a success response
|
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if self.connections[client_id]["current_discussion"] is None:
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self.connections[client_id]["current_discussion"] = self.db.load_last_discussion()
|
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|
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if self.personality.welcome_message!="":
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message = self.connections[client_id]["current_discussion"].add_message(
|
|
message_type = MSG_TYPE.MSG_TYPE_FULL.value if self.personality.include_welcome_message_in_disucssion else MSG_TYPE.MSG_TYPE_FULL_INVISIBLE_TO_AI.value,
|
|
sender_type = SENDER_TYPES.SENDER_TYPES_AI.value,
|
|
sender = self.personality.name,
|
|
content = self.personality.welcome_message,
|
|
metadata = None,
|
|
rank = 0,
|
|
parent_message_id = -1,
|
|
binding = self.config.binding_name,
|
|
model = self.config.model_name,
|
|
personality = self.config.personalities[self.config.active_personality_id],
|
|
created_at=None,
|
|
finished_generating_at=None
|
|
)
|
|
|
|
self.socketio.emit('discussion_created',
|
|
{'id':self.connections[client_id]["current_discussion"].discussion_id},
|
|
room=client_id
|
|
)
|
|
else:
|
|
self.socketio.emit('discussion_created',
|
|
{'id':0},
|
|
room=client_id
|
|
)
|
|
|
|
@socketio.on('load_discussion')
|
|
def load_discussion(data):
|
|
client_id = request.sid
|
|
ASCIIColors.yellow(f"Loading discussion for client {client_id}")
|
|
if "id" in data:
|
|
discussion_id = data["id"]
|
|
self.connections[client_id]["current_discussion"] = Discussion(discussion_id, self.db)
|
|
else:
|
|
if self.connections[client_id]["current_discussion"] is not None:
|
|
discussion_id = self.connections[client_id]["current_discussion"].discussion_id
|
|
self.connections[client_id]["current_discussion"] = Discussion(discussion_id, self.db)
|
|
else:
|
|
self.connections[client_id]["current_discussion"] = self.db.create_discussion()
|
|
messages = self.connections[client_id]["current_discussion"].get_messages()
|
|
jsons = [m.to_json() for m in messages]
|
|
self.socketio.emit('discussion',
|
|
jsons,
|
|
room=client_id
|
|
)
|
|
|
|
@socketio.on('upload_file')
|
|
def upload_file(data):
|
|
ASCIIColors.yellow("Uploading file")
|
|
file = data['file']
|
|
filename = file.filename
|
|
save_path = self.lollms_paths.personal_uploads_path/filename # Specify the desired folder path
|
|
|
|
try:
|
|
if not self.personality.processor is None:
|
|
file.save(save_path)
|
|
self.personality.processor.add_file(save_path, partial(self.process_chunk, client_id = request.sid))
|
|
# File saved successfully
|
|
socketio.emit('progress', {'status':True, 'progress': 100})
|
|
|
|
else:
|
|
file.save(save_path)
|
|
self.personality.add_file(save_path, partial(self.process_chunk, client_id = request.sid))
|
|
# File saved successfully
|
|
socketio.emit('progress', {'status':True, 'progress': 100})
|
|
except Exception as e:
|
|
# Error occurred while saving the file
|
|
socketio.emit('progress', {'status':False, 'error': str(e)})
|
|
|
|
@socketio.on('cancel_generation')
|
|
def cancel_generation():
|
|
client_id = request.sid
|
|
self.cancel_gen = True
|
|
#kill thread
|
|
ASCIIColors.error(f'Client {request.sid} requested cancelling generation')
|
|
terminate_thread(self.connections[client_id]['generation_thread'])
|
|
ASCIIColors.error(f'Client {request.sid} canceled generation')
|
|
self.busy=False
|
|
|
|
@socketio.on('get_personality_files')
|
|
def get_personality_files(data):
|
|
client_id = request.sid
|
|
self.connections[client_id]["generated_text"] = ""
|
|
self.connections[client_id]["cancel_generation"] = False
|
|
|
|
try:
|
|
self.personality.setCallback(partial(self.process_chunk,client_id = client_id))
|
|
except Exception as ex:
|
|
trace_exception(ex)
|
|
|
|
@socketio.on('send_file')
|
|
def send_file(data):
|
|
ASCIIColors.yellow("Receiving file")
|
|
|
|
client_id = request.sid
|
|
self.connections[client_id]["generated_text"] = ""
|
|
self.connections[client_id]["cancel_generation"] = False
|
|
|
|
if not self.config.use_files:
|
|
self.socketio.emit('file_received',
|
|
{
|
|
"status":False,
|
|
"filename":data["filename"],
|
|
"error":"Couldn't receive file: Verify that file type is compatible with the personality"
|
|
}, room=client_id
|
|
)
|
|
return
|
|
|
|
try:
|
|
self.personality.setCallback(partial(self.process_chunk,client_id = client_id))
|
|
ASCIIColors.info("Recovering file from front end")
|
|
|
|
path:Path = self.lollms_paths.personal_uploads_path / self.personality.personality_folder_name
|
|
path.mkdir(parents=True, exist_ok=True)
|
|
file_path = path / data["filename"]
|
|
File64BitsManager.b642file(data["fileData"],file_path)
|
|
if self.personality.processor:
|
|
result = self.personality.processor.add_file(file_path, partial(self.process_chunk, client_id=client_id))
|
|
else:
|
|
result = self.personality.add_file(file_path, partial(self.process_chunk, client_id=client_id))
|
|
if result:
|
|
self.socketio.emit('file_received',
|
|
{
|
|
"status":True,
|
|
"filename":data["filename"],
|
|
}, room=client_id
|
|
)
|
|
else:
|
|
self.socketio.emit('file_received',
|
|
{
|
|
"status":False,
|
|
"filename":data["filename"],
|
|
"error":"Couldn't receive file: Verify that file type is compatible with the personality"
|
|
}, room=client_id
|
|
)
|
|
|
|
except Exception as ex:
|
|
ASCIIColors.error(ex)
|
|
trace_exception(ex)
|
|
self.socketio.emit('file_received',
|
|
{
|
|
"status":False,
|
|
"filename":data["filename"],
|
|
"error":"Couldn't receive file: "+str(ex)
|
|
}, room=client_id
|
|
)
|
|
self.close_message(client_id)
|
|
|
|
@self.socketio.on('cancel_text_generation')
|
|
def cancel_text_generation(data):
|
|
client_id = request.sid
|
|
self.connections[client_id]["requested_stop"]=True
|
|
print(f"Client {client_id} requested canceling generation")
|
|
self.socketio.emit("generation_canceled", {"message":"Generation is canceled."}, room=client_id)
|
|
self.socketio.sleep(0)
|
|
self.busy = False
|
|
|
|
@self.socketio.on('execute_python_code')
|
|
def execute_python_code(data):
|
|
"""Executes Python code and returns the output."""
|
|
client_id = request.sid
|
|
code = data["code"]
|
|
# Import the necessary modules.
|
|
import io
|
|
import sys
|
|
import time
|
|
|
|
# Create a Python interpreter.
|
|
interpreter = io.StringIO()
|
|
sys.stdout = interpreter
|
|
|
|
# Execute the code.
|
|
start_time = time.time()
|
|
exec(code)
|
|
end_time = time.time()
|
|
|
|
# Get the output.
|
|
output = interpreter.getvalue()
|
|
self.socketio.emit("execution_output", {"output":output,"execution_time":end_time - start_time}, room=client_id)
|
|
|
|
@self.socketio.on('create_empty_message')
|
|
def create_empty_message(data):
|
|
client_id = request.sid
|
|
if self.personality is None:
|
|
self.notify("Select a personality",False,None)
|
|
return
|
|
ASCIIColors.info(f"Text generation requested by client: {client_id}")
|
|
# send the message to the bot
|
|
print(f"Creating an empty message for AI answer orientation")
|
|
if self.connections[client_id]["current_discussion"]:
|
|
if not self.model:
|
|
self.notify("No model selected. Please make sure you select a model before starting generation", False, client_id)
|
|
return
|
|
self.new_message(client_id, self.personality.name, "<edit this to put your ai answer start>")
|
|
self.socketio.sleep(0.01)
|
|
|
|
# A copy of the original lollms-server generation code needed for playground
|
|
@self.socketio.on('generate_text')
|
|
def handle_generate_text(data):
|
|
client_id = request.sid
|
|
self.cancel_gen = False
|
|
ASCIIColors.info(f"Text generation requested by client: {client_id}")
|
|
if self.busy:
|
|
self.socketio.emit("busy", {"message":"I am busy. Come back later."}, room=client_id)
|
|
self.socketio.sleep(0)
|
|
ASCIIColors.warning(f"OOps request {client_id} refused!! Server busy")
|
|
return
|
|
def generate_text():
|
|
self.busy = True
|
|
try:
|
|
model = self.model
|
|
self.connections[client_id]["is_generating"]=True
|
|
self.connections[client_id]["requested_stop"]=False
|
|
prompt = data['prompt']
|
|
tokenized = model.tokenize(prompt)
|
|
personality_id = data.get('personality', -1)
|
|
|
|
n_crop = data.get('n_crop', len(tokenized))
|
|
if n_crop!=-1:
|
|
prompt = model.detokenize(tokenized[-n_crop:])
|
|
|
|
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.connections:# Client disconnected
|
|
if self.connections[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.connections:
|
|
if not self.connections[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.busy = False
|
|
else:
|
|
try:
|
|
personality: AIPersonality = self.personalities[personality_id]
|
|
ump = self.config.discussion_prompt_separator +self.config.user_name.strip() 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.connections[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)
|
|
|
|
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.connections[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.busy = False
|
|
except Exception as ex:
|
|
trace_exception(ex)
|
|
self.socketio.emit('generation_error', {'error': str(ex)}, room=client_id)
|
|
self.busy = False
|
|
|
|
# Start the text generation task in a separate thread
|
|
task = self.socketio.start_background_task(target=generate_text)
|
|
|
|
@socketio.on('generate_msg')
|
|
def generate_msg(data):
|
|
client_id = request.sid
|
|
self.cancel_gen = False
|
|
self.connections[client_id]["generated_text"]=""
|
|
self.connections[client_id]["cancel_generation"]=False
|
|
self.connections[client_id]["continuing"]=False
|
|
self.connections[client_id]["first_chunk"]=True
|
|
|
|
|
|
|
|
if not self.model:
|
|
ASCIIColors.error("Model not selected. Please select a model")
|
|
self.notify("Model not selected. Please select a model", False, client_id)
|
|
return
|
|
|
|
if not self.busy:
|
|
if self.connections[client_id]["current_discussion"] is None:
|
|
if self.db.does_last_discussion_have_messages():
|
|
self.connections[client_id]["current_discussion"] = self.db.create_discussion()
|
|
else:
|
|
self.connections[client_id]["current_discussion"] = self.db.load_last_discussion()
|
|
|
|
prompt = data["prompt"]
|
|
ump = self.config.discussion_prompt_separator +self.config.user_name.strip() if self.config.use_user_name_in_discussions else self.personality.user_message_prefix
|
|
message = self.connections[client_id]["current_discussion"].add_message(
|
|
message_type = MSG_TYPE.MSG_TYPE_FULL.value,
|
|
sender_type = SENDER_TYPES.SENDER_TYPES_USER.value,
|
|
sender = ump.replace(self.config.discussion_prompt_separator,"").replace(":",""),
|
|
content=prompt,
|
|
metadata=None,
|
|
parent_message_id=self.message_id
|
|
)
|
|
|
|
ASCIIColors.green("Starting message generation by "+self.personality.name)
|
|
self.connections[client_id]['generation_thread'] = threading.Thread(target=self.start_message_generation, args=(message, message.id, client_id))
|
|
self.connections[client_id]['generation_thread'].start()
|
|
|
|
self.socketio.sleep(0.01)
|
|
ASCIIColors.info("Started generation task")
|
|
self.busy=True
|
|
#tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id, client_id))
|
|
#tpe.start()
|
|
else:
|
|
self.notify("I am busy. Come back later.", False, client_id)
|
|
|
|
@socketio.on('generate_msg_from')
|
|
def generate_msg_from(data):
|
|
client_id = request.sid
|
|
self.cancel_gen = False
|
|
self.connections[client_id]["continuing"]=False
|
|
self.connections[client_id]["first_chunk"]=True
|
|
|
|
if self.connections[client_id]["current_discussion"] is None:
|
|
ASCIIColors.warning("Please select a discussion")
|
|
self.notify("Please select a discussion first", False, client_id)
|
|
return
|
|
id_ = data['id']
|
|
if id_==-1:
|
|
message = self.connections[client_id]["current_discussion"].current_message
|
|
else:
|
|
message = self.connections[client_id]["current_discussion"].load_message(id_)
|
|
if message is None:
|
|
return
|
|
self.connections[client_id]['generation_thread'] = threading.Thread(target=self.start_message_generation, args=(message, message.id, client_id))
|
|
self.connections[client_id]['generation_thread'].start()
|
|
|
|
@socketio.on('continue_generate_msg_from')
|
|
def handle_connection(data):
|
|
client_id = request.sid
|
|
self.cancel_gen = False
|
|
self.connections[client_id]["continuing"]=True
|
|
self.connections[client_id]["first_chunk"]=True
|
|
|
|
if self.connections[client_id]["current_discussion"] is None:
|
|
ASCIIColors.yellow("Please select a discussion")
|
|
self.notify("Please select a discussion", False, client_id)
|
|
return
|
|
id_ = data['id']
|
|
if id_==-1:
|
|
message = self.connections[client_id]["current_discussion"].current_message
|
|
else:
|
|
message = self.connections[client_id]["current_discussion"].load_message(id_)
|
|
|
|
self.connections[client_id]["generated_text"]=message.content
|
|
self.connections[client_id]['generation_thread'] = threading.Thread(target=self.start_message_generation, args=(message, message.id, client_id, True))
|
|
self.connections[client_id]['generation_thread'].start()
|
|
|
|
# generation status
|
|
self.generating=False
|
|
ASCIIColors.blue(f"Your personal data is stored here :",end="")
|
|
ASCIIColors.green(f"{self.lollms_paths.personal_path}")
|
|
|
|
|
|
def rebuild_personalities(self, reload_all=False):
|
|
if reload_all:
|
|
self.mounted_personalities=[]
|
|
|
|
loaded = self.mounted_personalities
|
|
loaded_names = [f"{p.category}/{p.personality_folder_name}:{p.selected_language}" if p.selected_language else f"{p.category}/{p.personality_folder_name}" for p in loaded]
|
|
mounted_personalities=[]
|
|
ASCIIColors.success(f" ╔══════════════════════════════════════════════════╗ ")
|
|
ASCIIColors.success(f" ║ Building mounted Personalities ║ ")
|
|
ASCIIColors.success(f" ╚══════════════════════════════════════════════════╝ ")
|
|
to_remove=[]
|
|
for i,personality in enumerate(self.config['personalities']):
|
|
if i==self.config["active_personality_id"]:
|
|
ASCIIColors.red("*", end="")
|
|
ASCIIColors.green(f" {personality}")
|
|
else:
|
|
ASCIIColors.yellow(f" {personality}")
|
|
if personality in loaded_names:
|
|
mounted_personalities.append(loaded[loaded_names.index(personality)])
|
|
else:
|
|
personality_path = f"{personality}" if not ":" in personality else f"{personality.split(':')[0]}"
|
|
try:
|
|
personality = AIPersonality(personality_path,
|
|
self.lollms_paths,
|
|
self.config,
|
|
model=self.model,
|
|
app=self,
|
|
selected_language=personality.split(":")[1] if ":" in personality else None,
|
|
run_scripts=True)
|
|
mounted_personalities.append(personality)
|
|
except Exception as ex:
|
|
ASCIIColors.error(f"Personality file not found or is corrupted ({personality_path}).\nReturned the following exception:{ex}\nPlease verify that the personality you have selected exists or select another personality. Some updates may lead to change in personality name or category, so check the personality selection in settings to be sure.")
|
|
ASCIIColors.info("Trying to force reinstall")
|
|
if self.config["debug"]:
|
|
print(ex)
|
|
try:
|
|
personality = AIPersonality(
|
|
personality_path,
|
|
self.lollms_paths,
|
|
self.config,
|
|
self.model,
|
|
app = self,
|
|
run_scripts=True,
|
|
selected_language=personality.split(":")[1] if ":" in personality else None,
|
|
installation_option=InstallOption.FORCE_INSTALL)
|
|
mounted_personalities.append(personality)
|
|
except Exception as ex:
|
|
ASCIIColors.error(f"Couldn't load personality at {personality_path}")
|
|
trace_exception(ex)
|
|
ASCIIColors.info(f"Unmounting personality")
|
|
to_remove.append(i)
|
|
personality = AIPersonality(None,
|
|
self.lollms_paths,
|
|
self.config,
|
|
self.model,
|
|
run_scripts=True,
|
|
installation_option=InstallOption.FORCE_INSTALL)
|
|
mounted_personalities.append(personality)
|
|
ASCIIColors.info("Reverted to default personality")
|
|
if self.config["active_personality_id"]>=0 and self.config["active_personality_id"]<len(self.config["personalities"]):
|
|
ASCIIColors.success(f'selected model : {self.config["personalities"][self.config["active_personality_id"]]}')
|
|
else:
|
|
ASCIIColors.warning('An error was encountered while trying to mount personality')
|
|
ASCIIColors.success(f" ╔══════════════════════════════════════════════════╗ ")
|
|
ASCIIColors.success(f" ║ Done ║ ")
|
|
ASCIIColors.success(f" ╚══════════════════════════════════════════════════╝ ")
|
|
# Sort the indices in descending order to ensure correct removal
|
|
to_remove.sort(reverse=True)
|
|
|
|
# Remove elements from the list based on the indices
|
|
for index in to_remove:
|
|
if 0 <= index < len(mounted_personalities):
|
|
mounted_personalities.pop(index)
|
|
self.config["personalities"].pop(index)
|
|
ASCIIColors.info(f"removed personality {personality_path}")
|
|
|
|
if self.config["active_personality_id"]>=len(self.config["personalities"]):
|
|
self.config["active_personality_id"]=0
|
|
|
|
return mounted_personalities
|
|
|
|
|
|
def rebuild_extensions(self, reload_all=False):
|
|
if reload_all:
|
|
self.mounted_extensions=[]
|
|
|
|
loaded = self.mounted_extensions
|
|
loaded_names = [f"{p.category}/{p.extension_folder_name}" for p in loaded]
|
|
mounted_extensions=[]
|
|
ASCIIColors.success(f" ╔══════════════════════════════════════════════════╗ ")
|
|
ASCIIColors.success(f" ║ Building mounted Extensions ║ ")
|
|
ASCIIColors.success(f" ╚══════════════════════════════════════════════════╝ ")
|
|
to_remove=[]
|
|
for i,extension in enumerate(self.config['extensions']):
|
|
ASCIIColors.yellow(f" {extension}")
|
|
if extension in loaded_names:
|
|
mounted_extensions.append(loaded[loaded_names.index(extension)])
|
|
else:
|
|
extension_path = self.lollms_paths.extensions_zoo_path/f"{extension}"
|
|
try:
|
|
extension = ExtensionBuilder().build_extension(extension_path,self.lollms_paths, self)
|
|
mounted_extensions.append(extension)
|
|
except Exception as ex:
|
|
ASCIIColors.error(f"Personality file not found or is corrupted ({extension_path}).\nReturned the following exception:{ex}\nPlease verify that the personality you have selected exists or select another personality. Some updates may lead to change in personality name or category, so check the personality selection in settings to be sure.")
|
|
ASCIIColors.info("Trying to force reinstall")
|
|
if self.config["debug"]:
|
|
print(ex)
|
|
if self.config["active_personality_id"]>=0 and self.config["active_personality_id"]<len(self.config["personalities"]):
|
|
ASCIIColors.success(f'selected model : {self.config["personalities"][self.config["active_personality_id"]]}')
|
|
else:
|
|
ASCIIColors.warning('An error was encountered while trying to mount personality')
|
|
ASCIIColors.success(f" ╔══════════════════════════════════════════════════╗ ")
|
|
ASCIIColors.success(f" ║ Done ║ ")
|
|
ASCIIColors.success(f" ╚══════════════════════════════════════════════════╝ ")
|
|
# Sort the indices in descending order to ensure correct removal
|
|
to_remove.sort(reverse=True)
|
|
|
|
# Remove elements from the list based on the indices
|
|
for index in to_remove:
|
|
if 0 <= index < len(mounted_extensions):
|
|
mounted_extensions.pop(index)
|
|
self.config["personalities"].pop(index)
|
|
ASCIIColors.info(f"removed personality {personality_path}")
|
|
|
|
if self.config["active_personality_id"]>=len(self.config["personalities"]):
|
|
self.config["active_personality_id"]=0
|
|
|
|
return mounted_extensions
|
|
# ================================== LOLLMSApp
|
|
|
|
#properties
|
|
@property
|
|
def message_id(self):
|
|
return self._message_id
|
|
@message_id.setter
|
|
def message_id(self, id):
|
|
self._message_id=id
|
|
|
|
@property
|
|
def current_user_message_id(self):
|
|
return self._current_user_message_id
|
|
@current_user_message_id.setter
|
|
def current_user_message_id(self, id):
|
|
self._current_user_message_id=id
|
|
self._message_id = id
|
|
@property
|
|
def current_ai_message_id(self):
|
|
return self._current_ai_message_id
|
|
@current_ai_message_id.setter
|
|
def current_ai_message_id(self, id):
|
|
self._current_ai_message_id=id
|
|
self._message_id = id
|
|
|
|
def download_file(self, url, installation_path, callback=None):
|
|
"""
|
|
Downloads a file from a URL, reports the download progress using a callback function, and displays a progress bar.
|
|
|
|
Args:
|
|
url (str): The URL of the file to download.
|
|
installation_path (str): The path where the file should be saved.
|
|
callback (function, optional): A callback function to be called during the download
|
|
with the progress percentage as an argument. Defaults to None.
|
|
"""
|
|
try:
|
|
response = requests.get(url, stream=True)
|
|
|
|
# Get the file size from the response headers
|
|
total_size = int(response.headers.get('content-length', 0))
|
|
|
|
with open(installation_path, 'wb') as file:
|
|
downloaded_size = 0
|
|
with tqdm(total=total_size, unit='B', unit_scale=True, ncols=80) as progress_bar:
|
|
for chunk in response.iter_content(chunk_size=8192):
|
|
if chunk:
|
|
file.write(chunk)
|
|
downloaded_size += len(chunk)
|
|
if callback is not None:
|
|
callback(downloaded_size, total_size)
|
|
progress_bar.update(len(chunk))
|
|
|
|
if callback is not None:
|
|
callback(total_size, total_size)
|
|
|
|
print("File downloaded successfully")
|
|
except Exception as e:
|
|
print("Couldn't download file:", str(e))
|
|
|
|
|
|
|
|
|
|
def prepare_reception(self, client_id):
|
|
if not self.connections[client_id]["continuing"]:
|
|
self.connections[client_id]["generated_text"] = ""
|
|
|
|
self.connections[client_id]["first_chunk"]=True
|
|
|
|
self.nb_received_tokens = 0
|
|
self.start_time = datetime.now()
|
|
|
|
|
|
def clean_string(self, input_string):
|
|
# Remove extra spaces by replacing multiple spaces with a single space
|
|
#cleaned_string = re.sub(r'\s+', ' ', input_string)
|
|
|
|
# Remove extra line breaks by replacing multiple consecutive line breaks with a single line break
|
|
cleaned_string = re.sub(r'\n\s*\n', '\n', input_string)
|
|
# Create a string containing all punctuation characters
|
|
punctuation_chars = string.punctuation
|
|
# Define a regular expression pattern to match and remove non-alphanumeric characters
|
|
#pattern = f'[^a-zA-Z0-9\s{re.escape(punctuation_chars)}]' # This pattern matches any character that is not a letter, digit, space, or punctuation
|
|
pattern = f'[^a-zA-Z0-9\u00C0-\u017F\s{re.escape(punctuation_chars)}]'
|
|
# Use re.sub to replace the matched characters with an empty string
|
|
cleaned_string = re.sub(pattern, '', cleaned_string)
|
|
return cleaned_string
|
|
|
|
|
|
def prepare_query(self, client_id, message_id=-1, is_continue=False):
|
|
messages = self.connections[client_id]["current_discussion"].get_messages()
|
|
full_message_list = []
|
|
for i, message in enumerate(messages):
|
|
if message.id< message_id or (message_id==-1 and i<len(messages)-1):
|
|
if message.content!='' and (message.message_type<=MSG_TYPE.MSG_TYPE_FULL_INVISIBLE_TO_USER.value and message.message_type!=MSG_TYPE.MSG_TYPE_FULL_INVISIBLE_TO_AI.value):
|
|
full_message_list.append("\n"+self.config.discussion_prompt_separator+message.sender+": "+message.content.strip())
|
|
else:
|
|
break
|
|
|
|
link_text = "\n" #self.personality.link_text
|
|
if not is_continue:
|
|
full_message_list.append(self.config.discussion_prompt_separator +message.sender.strip().replace(":","")+": "+message.content.strip()+link_text+self.personality.ai_message_prefix.strip())
|
|
else:
|
|
full_message_list.append(self.config.discussion_prompt_separator +message.sender.strip().replace(":","")+": "+message.content.strip())
|
|
|
|
|
|
composed_messages = link_text.join(full_message_list)
|
|
t = self.model.tokenize(composed_messages)
|
|
cond_tk = self.model.tokenize(self.personality.personality_conditioning)
|
|
n_t = len(t)
|
|
n_cond_tk = len(cond_tk)
|
|
max_prompt_stx_size = 3*int(self.config.ctx_size/4)
|
|
if n_cond_tk+n_t>max_prompt_stx_size:
|
|
nb_tk = max_prompt_stx_size-n_cond_tk
|
|
composed_messages = self.model.detokenize(t[-nb_tk:])
|
|
ASCIIColors.warning(f"Cropping discussion to fit context [using {nb_tk} tokens/{self.config.ctx_size}]")
|
|
discussion_messages = composed_messages
|
|
|
|
|
|
conditionning = self.personality.personality_conditioning
|
|
if self.config["override_personality_model_parameters"]:
|
|
conditionning = conditionning+ "\n!@>user description:\nName:"+self.config["user_name"]+"\n"+self.config["user_description"]+"\n"
|
|
|
|
str_docs = ""
|
|
|
|
if self.config.use_discussions_history:
|
|
if self.discussions_store is not None:
|
|
pr = PromptReshaper("{{conditionning}}\n!@>document chunks:\n{{doc}}\n{{content}}")
|
|
docs, sorted_similarities = self.discussions_store.recover_text(message.content, top_k=self.config.data_vectorization_nb_chunks)
|
|
for doc, infos in zip(docs, sorted_similarities):
|
|
str_docs+=f"discussion chunk:\ndiscussion title: {infos[0]}\nchunk content:{doc}"
|
|
|
|
|
|
if len(self.personality.files)>0 and self.personality.vectorizer:
|
|
docs, sorted_similarities = self.personality.vectorizer.recover_text(message.content, top_k=self.config.data_vectorization_nb_chunks)
|
|
for doc, infos in zip(docs, sorted_similarities):
|
|
str_docs+=f"document chunk:\nchunk path: {infos[0]}\nchunk content:{doc}"
|
|
|
|
if str_docs!="":
|
|
pr = PromptReshaper("{{conditionning}}\n!@>document chunks:\n{{doc}}\n{{content}}")
|
|
discussion_messages = pr.build({
|
|
"doc":str_docs,
|
|
"conditionning":conditionning,
|
|
"content":discussion_messages
|
|
}, self.model.tokenize, self.model.detokenize, self.config.ctx_size-self.config.min_n_predict, place_holders_to_sacrifice=["content"])
|
|
else:
|
|
pr = PromptReshaper("{{conditionning}}\n{{content}}")
|
|
discussion_messages = pr.build({
|
|
"conditionning":conditionning,
|
|
"content":discussion_messages
|
|
}, self.model.tokenize, self.model.detokenize, self.config.ctx_size-self.config.min_n_predict, place_holders_to_sacrifice=["content"])
|
|
# remove extra returns
|
|
discussion_messages = self.clean_string(discussion_messages)
|
|
tokens = self.model.tokenize(discussion_messages)
|
|
if self.config["debug"]:
|
|
ASCIIColors.yellow(discussion_messages)
|
|
ASCIIColors.info(f"prompt size:{len(tokens)} tokens")
|
|
|
|
return discussion_messages, message.content, tokens
|
|
|
|
def get_discussion_to(self, client_id, message_id=-1):
|
|
messages = self.connections[client_id]["current_discussion"].get_messages()
|
|
full_message_list = []
|
|
ump = self.config.discussion_prompt_separator +self.config.user_name.strip() if self.config.use_user_name_in_discussions else self.personality.user_message_prefix
|
|
|
|
for message in messages:
|
|
if message["id"]<= message_id or message_id==-1:
|
|
if message["type"]!=MSG_TYPE.MSG_TYPE_FULL_INVISIBLE_TO_USER:
|
|
if message["sender"]==self.personality.name:
|
|
full_message_list.append(self.personality.ai_message_prefix+message["content"])
|
|
else:
|
|
full_message_list.append(ump + message["content"])
|
|
|
|
link_text = "\n"# self.personality.link_text
|
|
|
|
if len(full_message_list) > self.config["nb_messages_to_remember"]:
|
|
discussion_messages = self.personality.personality_conditioning+ link_text.join(full_message_list[-self.config["nb_messages_to_remember"]:])
|
|
else:
|
|
discussion_messages = self.personality.personality_conditioning+ link_text.join(full_message_list)
|
|
|
|
return discussion_messages # Removes the last return
|
|
|
|
def remove_text_from_string(self, string, text_to_find):
|
|
"""
|
|
Removes everything from the first occurrence of the specified text in the string (case-insensitive).
|
|
|
|
Parameters:
|
|
string (str): The original string.
|
|
text_to_find (str): The text to find in the string.
|
|
|
|
Returns:
|
|
str: The updated string.
|
|
"""
|
|
index = string.lower().find(text_to_find.lower())
|
|
|
|
if index != -1:
|
|
string = string[:index]
|
|
|
|
return string
|
|
|
|
def notify(self, content, status, client_id):
|
|
self.socketio.emit('notification', {
|
|
'content': content,# self.connections[client_id]["generated_text"],
|
|
'status': status
|
|
}, room=client_id
|
|
)
|
|
|
|
def new_message(self,
|
|
client_id,
|
|
sender,
|
|
content,
|
|
parameters=None,
|
|
metadata=None,
|
|
ui=None,
|
|
message_type:MSG_TYPE=MSG_TYPE.MSG_TYPE_FULL,
|
|
sender_type:SENDER_TYPES=SENDER_TYPES.SENDER_TYPES_AI
|
|
):
|
|
|
|
mtdt = metadata if metadata is None or type(metadata) == str else json.dumps(metadata, indent=4)
|
|
|
|
msg = self.connections[client_id]["current_discussion"].add_message(
|
|
message_type = message_type.value,
|
|
sender_type = sender_type.value,
|
|
sender = sender,
|
|
content = content,
|
|
metadata = mtdt,
|
|
ui = ui,
|
|
rank = 0,
|
|
parent_message_id = self.connections[client_id]["current_discussion"].current_message.id,
|
|
binding = self.config["binding_name"],
|
|
model = self.config["model_name"],
|
|
personality = self.config["personalities"][self.config["active_personality_id"]],
|
|
) # first the content is empty, but we'll fill it at the end
|
|
|
|
self.socketio.emit('new_message',
|
|
{
|
|
"sender": self.personality.name,
|
|
"message_type": message_type.value,
|
|
"sender_type": SENDER_TYPES.SENDER_TYPES_AI.value,
|
|
"content": content,
|
|
"parameters": parameters,
|
|
"metadata": metadata,
|
|
"ui": ui,
|
|
"id": msg.id,
|
|
"parent_message_id": msg.parent_message_id,
|
|
|
|
'binding': self.config["binding_name"],
|
|
'model' : self.config["model_name"],
|
|
'personality': self.config["personalities"][self.config["active_personality_id"]],
|
|
|
|
'created_at': self.connections[client_id]["current_discussion"].current_message.created_at,
|
|
'finished_generating_at': self.connections[client_id]["current_discussion"].current_message.finished_generating_at,
|
|
}, room=client_id
|
|
)
|
|
|
|
def update_message(self, client_id, chunk,
|
|
parameters=None,
|
|
metadata=[],
|
|
ui=None,
|
|
msg_type:MSG_TYPE=None
|
|
):
|
|
self.connections[client_id]["current_discussion"].current_message.finished_generating_at=datetime.now().strftime('%Y-%m-%d %H:%M:%S')
|
|
mtdt = json.dumps(metadata, indent=4) if metadata is not None and type(metadata)== list else metadata
|
|
if self.nb_received_tokens==1 and msg_type==MSG_TYPE.MSG_TYPE_CHUNK:
|
|
self.socketio.emit('update_message', {
|
|
"sender": self.personality.name,
|
|
'id':self.connections[client_id]["current_discussion"].current_message.id,
|
|
'content': "✍ warming up ...",# self.connections[client_id]["generated_text"],
|
|
'ui': ui,
|
|
'discussion_id':self.connections[client_id]["current_discussion"].discussion_id,
|
|
'message_type': MSG_TYPE.MSG_TYPE_STEP_END.value,
|
|
'finished_generating_at': self.connections[client_id]["current_discussion"].current_message.finished_generating_at,
|
|
'parameters':parameters,
|
|
'metadata':metadata
|
|
}, room=client_id
|
|
)
|
|
|
|
|
|
self.socketio.emit('update_message', {
|
|
"sender": self.personality.name,
|
|
'id':self.connections[client_id]["current_discussion"].current_message.id,
|
|
'content': chunk,# self.connections[client_id]["generated_text"],
|
|
'ui': ui,
|
|
'discussion_id':self.connections[client_id]["current_discussion"].discussion_id,
|
|
'message_type': msg_type.value if msg_type is not None else MSG_TYPE.MSG_TYPE_CHUNK.value if self.nb_received_tokens>1 else MSG_TYPE.MSG_TYPE_FULL.value,
|
|
'finished_generating_at': self.connections[client_id]["current_discussion"].current_message.finished_generating_at,
|
|
'parameters':parameters,
|
|
'metadata':metadata
|
|
}, room=client_id
|
|
)
|
|
self.socketio.sleep(0.01)
|
|
self.connections[client_id]["current_discussion"].update_message(self.connections[client_id]["generated_text"], new_metadata=mtdt, new_ui=ui)
|
|
|
|
def close_message(self, client_id):
|
|
if not self.connections[client_id]["current_discussion"]:
|
|
return
|
|
#fix halucination
|
|
self.connections[client_id]["generated_text"]=self.connections[client_id]["generated_text"].split("!@>")[0]
|
|
# Send final message
|
|
self.connections[client_id]["current_discussion"].current_message.finished_generating_at=datetime.now().strftime('%Y-%m-%d %H:%M:%S')
|
|
self.socketio.emit('close_message', {
|
|
"sender": self.personality.name,
|
|
"id": self.connections[client_id]["current_discussion"].current_message.id,
|
|
"content":self.connections[client_id]["generated_text"],
|
|
|
|
'binding': self.config["binding_name"],
|
|
'model' : self.config["model_name"],
|
|
'personality':self.config["personalities"][self.config["active_personality_id"]],
|
|
|
|
'created_at': self.connections[client_id]["current_discussion"].current_message.created_at,
|
|
'finished_generating_at': self.connections[client_id]["current_discussion"].current_message.finished_generating_at,
|
|
|
|
}, room=client_id
|
|
)
|
|
def process_chunk(
|
|
self,
|
|
chunk:str,
|
|
message_type:MSG_TYPE,
|
|
|
|
parameters:dict=None,
|
|
metadata:list=None,
|
|
client_id:int=0
|
|
):
|
|
"""
|
|
Processes a chunk of generated text
|
|
"""
|
|
|
|
if message_type == MSG_TYPE.MSG_TYPE_STEP:
|
|
ASCIIColors.info("--> Step:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_STEP_START:
|
|
ASCIIColors.info("--> Step started:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_STEP_END:
|
|
if parameters['status']:
|
|
ASCIIColors.success("--> Step ended:"+chunk)
|
|
else:
|
|
ASCIIColors.error("--> Step ended:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_EXCEPTION:
|
|
self.notify(chunk,False, client_id)
|
|
ASCIIColors.error("--> Exception from personality:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_WARNING:
|
|
self.notify(chunk,True, client_id)
|
|
ASCIIColors.error("--> Exception from personality:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_INFO:
|
|
self.notify(chunk,True, client_id)
|
|
ASCIIColors.info("--> Info:"+chunk)
|
|
if message_type == MSG_TYPE.MSG_TYPE_UI:
|
|
self.update_message(client_id, "", parameters, metadata, chunk, MSG_TYPE.MSG_TYPE_UI)
|
|
|
|
if message_type == MSG_TYPE.MSG_TYPE_NEW_MESSAGE:
|
|
self.nb_received_tokens = 0
|
|
self.start_time = datetime.now()
|
|
self.new_message(
|
|
client_id,
|
|
self.personality.name,
|
|
chunk if parameters["type"]!=MSG_TYPE.MSG_TYPE_UI.value else '',
|
|
metadata = [{
|
|
"title":chunk,
|
|
"content":parameters["metadata"]
|
|
}
|
|
] if parameters["type"]==MSG_TYPE.MSG_TYPE_JSON_INFOS.value else None,
|
|
ui= chunk if parameters["type"]==MSG_TYPE.MSG_TYPE_UI.value else None,
|
|
message_type= MSG_TYPE(parameters["type"]))
|
|
|
|
elif message_type == MSG_TYPE.MSG_TYPE_FINISHED_MESSAGE:
|
|
self.close_message(client_id)
|
|
|
|
elif message_type == MSG_TYPE.MSG_TYPE_CHUNK:
|
|
dt =(datetime.now() - self.start_time).seconds
|
|
if dt==0:
|
|
dt=1
|
|
spd = self.nb_received_tokens/dt
|
|
ASCIIColors.green(f"Received {self.nb_received_tokens} tokens (speed: {spd:.2f}t/s) ",end="\r",flush=True)
|
|
sys.stdout = sys.__stdout__
|
|
sys.stdout.flush()
|
|
self.connections[client_id]["generated_text"] += chunk
|
|
antiprompt = self.personality.detect_antiprompt(self.connections[client_id]["generated_text"])
|
|
if antiprompt:
|
|
ASCIIColors.warning(f"\nDetected hallucination with antiprompt: {antiprompt}")
|
|
self.connections[client_id]["generated_text"] = self.remove_text_from_string(self.connections[client_id]["generated_text"],antiprompt)
|
|
self.update_message(client_id, self.connections[client_id]["generated_text"], parameters, metadata, None, MSG_TYPE.MSG_TYPE_FULL)
|
|
return False
|
|
else:
|
|
self.nb_received_tokens += 1
|
|
if self.connections[client_id]["continuing"] and self.connections[client_id]["first_chunk"]:
|
|
self.update_message(client_id, self.connections[client_id]["generated_text"], parameters, metadata)
|
|
else:
|
|
self.update_message(client_id, chunk, parameters, metadata, msg_type=MSG_TYPE.MSG_TYPE_CHUNK)
|
|
self.connections[client_id]["first_chunk"]=False
|
|
# if stop generation is detected then stop
|
|
if not self.cancel_gen:
|
|
return True
|
|
else:
|
|
self.cancel_gen = False
|
|
ASCIIColors.warning("Generation canceled")
|
|
return False
|
|
|
|
# Stream the generated text to the main process
|
|
elif message_type == MSG_TYPE.MSG_TYPE_FULL:
|
|
self.connections[client_id]["generated_text"] = chunk
|
|
self.nb_received_tokens += 1
|
|
dt =(datetime.now() - self.start_time).seconds
|
|
if dt==0:
|
|
dt=1
|
|
spd = self.nb_received_tokens/dt
|
|
ASCIIColors.green(f"Received {self.nb_received_tokens} tokens (speed: {spd:.2f}t/s) ",end="\r",flush=True)
|
|
self.update_message(client_id, chunk, parameters, metadata, ui=None, msg_type=message_type)
|
|
return True
|
|
# Stream the generated text to the frontend
|
|
else:
|
|
self.update_message(client_id, chunk, parameters, metadata, ui=None, msg_type=message_type)
|
|
return True
|
|
|
|
|
|
def generate(self, full_prompt, prompt, n_predict, client_id, callback=None):
|
|
if self.personality.processor is not None:
|
|
ASCIIColors.info("Running workflow")
|
|
try:
|
|
self.personality.processor.run_workflow( prompt, full_prompt, callback)
|
|
except Exception as ex:
|
|
trace_exception(ex)
|
|
# Catch the exception and get the traceback as a list of strings
|
|
traceback_lines = traceback.format_exception(type(ex), ex, ex.__traceback__)
|
|
# Join the traceback lines into a single string
|
|
traceback_text = ''.join(traceback_lines)
|
|
ASCIIColors.error(f"Workflow run failed.\nError:{ex}")
|
|
ASCIIColors.error(traceback_text)
|
|
if callback:
|
|
callback(f"Workflow run failed\nError:{ex}", MSG_TYPE.MSG_TYPE_EXCEPTION)
|
|
print("Finished executing the workflow")
|
|
return
|
|
|
|
|
|
self._generate(full_prompt, n_predict, client_id, callback)
|
|
ASCIIColors.success("\nFinished executing the generation")
|
|
|
|
def _generate(self, prompt, n_predict, client_id, callback=None):
|
|
self.nb_received_tokens = 0
|
|
self.start_time = datetime.now()
|
|
if self.model is not None:
|
|
ASCIIColors.info(f"warmup for generating {n_predict} tokens")
|
|
if self.config["override_personality_model_parameters"]:
|
|
output = self.model.generate(
|
|
prompt,
|
|
callback=callback,
|
|
n_predict=n_predict,
|
|
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'],
|
|
n_threads=self.config['n_threads']
|
|
)
|
|
else:
|
|
output = self.model.generate(
|
|
prompt,
|
|
callback=callback,
|
|
n_predict=min(n_predict,self.personality.model_n_predicts),
|
|
temperature=self.personality.model_temperature,
|
|
top_k=self.personality.model_top_k,
|
|
top_p=self.personality.model_top_p,
|
|
repeat_penalty=self.personality.model_repeat_penalty,
|
|
repeat_last_n = self.personality.model_repeat_last_n,
|
|
seed=self.config['seed'],
|
|
n_threads=self.config['n_threads']
|
|
)
|
|
else:
|
|
print("No model is installed or selected. Please make sure to install a model and select it inside your configuration before attempting to communicate with the model.")
|
|
print("To do this: Install the model to your models/<binding name> folder.")
|
|
print("Then set your model information in your local configuration file that you can find in configs/local_config.yaml")
|
|
print("You can also use the ui to set your model in the settings page.")
|
|
output = ""
|
|
return output
|
|
|
|
def start_message_generation(self, message, message_id, client_id, is_continue=False):
|
|
if self.personality is None:
|
|
self.notify("Select a personality",False,None)
|
|
return
|
|
ASCIIColors.info(f"Text generation requested by client: {client_id}")
|
|
# send the message to the bot
|
|
print(f"Received message : {message.content}")
|
|
if self.connections[client_id]["current_discussion"]:
|
|
if not self.model:
|
|
self.notify("No model selected. Please make sure you select a model before starting generation", False, client_id)
|
|
return
|
|
# First we need to send the new message ID to the client
|
|
if is_continue:
|
|
self.connections[client_id]["current_discussion"].load_message(message_id)
|
|
self.connections[client_id]["generated_text"] = message.content
|
|
else:
|
|
self.new_message(client_id, self.personality.name, "")
|
|
self.update_message(client_id, "✍ warming up ...", msg_type=MSG_TYPE.MSG_TYPE_STEP_START)
|
|
self.socketio.sleep(0.01)
|
|
|
|
# prepare query and reception
|
|
self.discussion_messages, self.current_message, tokens = self.prepare_query(client_id, message_id, is_continue)
|
|
self.prepare_reception(client_id)
|
|
self.generating = True
|
|
self.connections[client_id]["processing"]=True
|
|
self.generate(
|
|
self.discussion_messages,
|
|
self.current_message,
|
|
n_predict = self.config.ctx_size-len(tokens)-1,
|
|
client_id=client_id,
|
|
callback=partial(self.process_chunk,client_id = client_id)
|
|
)
|
|
print()
|
|
print("## Done Generation ##")
|
|
print()
|
|
self.cancel_gen = False
|
|
|
|
# Send final message
|
|
self.close_message(client_id)
|
|
self.socketio.sleep(0.01)
|
|
self.connections[client_id]["processing"]=False
|
|
if self.connections[client_id]["schedule_for_deletion"]:
|
|
del self.connections[client_id]
|
|
|
|
ASCIIColors.success(f" ╔══════════════════════════════════════════════════╗ ")
|
|
ASCIIColors.success(f" ║ Done ║ ")
|
|
ASCIIColors.success(f" ╚══════════════════════════════════════════════════╝ ")
|
|
self.busy=False
|
|
|
|
else:
|
|
ump = self.config.discussion_prompt_separator +self.config.user_name.strip() if self.config.use_user_name_in_discussions else self.personality.user_message_prefix
|
|
|
|
self.cancel_gen = False
|
|
#No discussion available
|
|
ASCIIColors.warning("No discussion selected!!!")
|
|
|
|
self.notify("No discussion selected!!!",False, client_id)
|
|
|
|
print()
|
|
self.busy=False
|
|
return ""
|
|
|