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"""
File : lollms_web_ui . py
Author : ParisNeo
Description : Singleton class for the LoLLMS web UI .
This class provides a singleton instance of the LoLLMS web UI , allowing access to its functionality and data across multiple endpoints .
"""
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from lollms . server . elf_server import LOLLMSElfServer
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from datetime import datetime
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from lollms . databases . discussions_database 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 , MSG_OPERATION_TYPE , MSG_OPERATION_TYPE , CONTENT_OPERATION_TYPES , SENDER_TYPES
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from lollms . extension import LOLLMSExtension , ExtensionBuilder
from lollms . personality import AIPersonality , PersonalityBuilder
from lollms . binding import LOLLMSConfig , BindingBuilder , LLMBinding , ModelBuilder , BindingType
from lollms . paths import LollmsPaths
from lollms . helpers import ASCIIColors , trace_exception
from lollms . com import NotificationType , NotificationDisplayType , LoLLMsCom
from lollms . app import LollmsApplication
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from lollms . utilities import File64BitsManager , PromptReshaper , PackageManager , find_first_available_file_index , run_async , is_asyncio_loop_running , yes_or_no_input , process_ai_output
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from lollms . generation import RECEPTION_MANAGER , ROLE_CHANGE_DECISION , ROLE_CHANGE_OURTPUT
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from lollms . client_session import Client
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import git
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import asyncio
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import os
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import threading
from tqdm import tqdm
import traceback
import sys
import gc
import ctypes
from functools import partial
import json
import shutil
import re
import string
import requests
from datetime import datetime
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from typing import List , Tuple , Callable , Any
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import time
import numpy as np
from lollms . utilities import find_first_available_file_index , convert_language_name
if not PackageManager . check_package_installed ( " requests " ) :
PackageManager . install_package ( " requests " )
if not PackageManager . check_package_installed ( " bs4 " ) :
PackageManager . install_package ( " beautifulsoup4 " )
import requests
def terminate_thread ( thread ) :
if thread :
if not thread . is_alive ( ) :
ASCIIColors . yellow ( " Thread not alive " )
return
thread_id = thread . ident
exc = ctypes . py_object ( SystemExit )
res = ctypes . pythonapi . PyThreadState_SetAsyncExc ( thread_id , exc )
if res > 1 :
ctypes . pythonapi . PyThreadState_SetAsyncExc ( thread_id , None )
del thread
gc . collect ( )
raise SystemError ( " Failed to terminate the thread. " )
else :
ASCIIColors . yellow ( " Canceled successfully " ) # The current version of the webui
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lollms_webui_version = " 13 alpha ( code name feather 🪶) "
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class LOLLMSWebUI ( LOLLMSElfServer ) :
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__instance = None
@staticmethod
def build_instance (
config : LOLLMSConfig ,
lollms_paths : LollmsPaths ,
load_binding = True ,
load_model = True ,
load_voice_service = True ,
load_sd_service = True ,
try_select_binding = False ,
try_select_model = False ,
callback = None ,
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args = None ,
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sio = None
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) :
if LOLLMSWebUI . __instance is None :
LOLLMSWebUI (
config ,
lollms_paths ,
load_binding = load_binding ,
load_model = load_model ,
load_sd_service = load_sd_service ,
load_voice_service = load_voice_service ,
try_select_binding = try_select_binding ,
try_select_model = try_select_model ,
callback = callback ,
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args = args ,
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sio = sio
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)
return LOLLMSWebUI . __instance
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def __init__ (
self ,
config : LOLLMSConfig ,
lollms_paths : LollmsPaths ,
load_binding = True ,
load_model = True ,
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load_voice_service = True ,
load_sd_service = True ,
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try_select_binding = False ,
try_select_model = False ,
callback = None ,
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args = None ,
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sio = None
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) - > None :
super ( ) . __init__ (
config ,
lollms_paths ,
load_binding = load_binding ,
load_model = load_model ,
try_select_binding = try_select_binding ,
try_select_model = try_select_model ,
callback = callback ,
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sio = sio
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)
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self . app_name : str = " LOLLMSWebUI "
self . version : str = lollms_webui_version
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self . args = args
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self . busy = False
self . nb_received_tokens = 0
self . config_file_path = config . file_path
self . cancel_gen = False
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if self . config . auto_update :
if self . check_update_ ( ) :
ASCIIColors . info ( " New version found. Updating! " )
self . run_update_script ( )
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# Keeping track of current discussion and message
self . _current_user_message_id = 0
self . _current_ai_message_id = 0
self . _message_id = 0
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# migrate old databases to new ones:
databases_path = self . lollms_paths . personal_path / " databases "
if databases_path . exists ( ) and len ( [ f for f in databases_path . iterdir ( ) if f . suffix == " .db " ] ) > 0 :
if yes_or_no_input ( " Old databases have been spotted on your system. Do you want me to migrate them to the new format? " ) :
databases_found = False
for database_path in databases_path . iterdir ( ) :
if database_path . suffix == " .db " :
ASCIIColors . red ( f " Found old discussion database format : { database_path } " )
ASCIIColors . red ( f " Migrating to new format... " , end = " " )
new_db_path = self . lollms_paths . personal_discussions_path / database_path . stem
new_db_path . mkdir ( exist_ok = True , parents = True )
try :
shutil . copy ( database_path , new_db_path / " database.db " )
ASCIIColors . green ( " ok " )
databases_found = True
except Exception as ex :
ASCIIColors . warning ( ex )
if databases_found :
ASCIIColors . green ( f " Databases are migrated from { databases_path } to the new { self . lollms_paths . personal_discussions_path } path " )
if yes_or_no_input ( " Databases are migrated to the new format. Do you want me to delete the previous version? " ) :
for database_path in databases_path . iterdir ( ) :
if database_path . suffix == " .db " :
ASCIIColors . red ( f " Deleting { database_path } " )
database_path . unlink ( )
if config [ " discussion_db_name " ] . endswith ( " .db " ) :
config [ " discussion_db_name " ] = config [ " discussion_db_name " ] . replace ( " .db " , " " )
config . save_config ( )
self . discussion_db_name = config [ " discussion_db_name " ]
# Create database object
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self . db = DiscussionsDB ( self , self . lollms_paths , self . discussion_db_name )
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# If the database is empty, populate it with tables
ASCIIColors . info ( " Checking discussions database... " , end = " " )
self . db . create_tables ( )
self . db . add_missing_columns ( )
ASCIIColors . success ( " ok " )
# This is used to keep track of messages
self . download_infos = { }
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# Define a WebSocket event handler
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@sio.event
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async def connect ( sid , environ ) :
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self . session . add_client ( sid , sid , self . db . load_last_discussion ( ) , self . db )
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await self . sio . emit ( ' connected ' , to = sid )
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ASCIIColors . success ( f ' Client { sid } connected ' )
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@sio.event
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def disconnect ( sid ) :
try :
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self . session . add_client ( sid , sid , self . db . load_last_discussion ( ) , self . db )
if self . session . get_client ( sid ) . processing :
self . session . get_client ( sid ) . schedule_for_deletion = True
else :
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# Clients are now kept forever
pass # self.session.remove_client(sid, sid)
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except Exception as ex :
pass
ASCIIColors . error ( f ' Client { sid } disconnected ' )
# generation status
self . generating = False
ASCIIColors . blue ( f " Your personal data is stored here : " , end = " " )
ASCIIColors . green ( f " { self . lollms_paths . personal_path } " )
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self . start_servers ( )
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def get_uploads_path ( self , client_id ) :
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return self . session . get_client ( client_id ) . discussion_path # self.db.discussion_db_path/f'{["discussion"].discussion_id}'
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# Other methods and properties of the LoLLMSWebUI singleton class
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def check_module_update_ ( self , repo_path , branch_name = " main " ) :
try :
# Open the repository
ASCIIColors . yellow ( f " Checking for updates from { repo_path } " )
repo = git . Repo ( repo_path )
# Fetch updates from the remote for the specified branch
repo . remotes . origin . fetch ( refspec = f " refs/heads/ { branch_name } :refs/remotes/origin/ { branch_name } " )
# Compare the local and remote commit IDs for the specified branch
local_commit = repo . head . commit
remote_commit = repo . remotes . origin . refs [ branch_name ] . commit
# Check if the local branch is behind the remote branch
is_behind = repo . is_ancestor ( local_commit , remote_commit ) and local_commit != remote_commit
ASCIIColors . yellow ( f " update availability: { is_behind } " )
# Return True if the local branch is behind the remote branch
return is_behind
except Exception as e :
# Handle any errors that may occur during the fetch process
# trace_exception(e)
return False
def check_update_ ( self , branch_name = " main " ) :
try :
# Open the repository
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repo_path = str ( Path ( __file__ ) . parent / " lollms_core " )
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if self . check_module_update_ ( repo_path , branch_name ) :
return True
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repo_path = str ( Path ( __file__ ) . parent )
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if self . check_module_update_ ( repo_path , branch_name ) :
return True
return False
except Exception as e :
# Handle any errors that may occur during the fetch process
# trace_exception(e)
return False
def run_update_script ( self , args = None ) :
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# deactivate trust store for github and pip package install
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if ' REQUESTS_CA_BUNDLE ' in os . environ :
del os . environ [ ' REQUESTS_CA_BUNDLE ' ]
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update_script = Path ( __file__ ) . parent / " update_script.py "
# Convert Namespace object to a dictionary
if args :
args_dict = vars ( args )
else :
args_dict = { }
# Filter out any key-value pairs where the value is None
valid_args = { key : value for key , value in args_dict . items ( ) if value is not None }
# Save the arguments to a temporary file
temp_file = Path ( __file__ ) . parent / " temp_args.txt "
with open ( temp_file , " w " ) as file :
# Convert the valid_args dictionary to a string in the format "key1 value1 key2 value2 ..."
arg_string = " " . join ( [ f " -- { key } { value } " for key , value in valid_args . items ( ) ] )
file . write ( arg_string )
os . system ( f " python { update_script } " )
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sys . exit ( 0 )
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def run_restart_script ( self , args ) :
restart_script = Path ( __file__ ) . parent / " restart_script.py "
# Convert Namespace object to a dictionary
args_dict = vars ( args )
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# Filter out any key-value pairs where the value is None
valid_args = { key : value for key , value in args_dict . items ( ) if value is not None }
# Save the arguments to a temporary file
temp_file = Path ( __file__ ) . parent / " temp_args.txt "
with open ( temp_file , " w " ) as file :
# Convert the valid_args dictionary to a string in the format "key1 value1 key2 value2 ..."
arg_string = " " . join ( [ f " -- { key } { value } " for key , value in valid_args . items ( ) ] )
file . write ( arg_string )
os . system ( f " python { restart_script } " )
sys . exit ( 0 )
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def audio_callback ( self , text ) :
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if self . summoned :
client_id = 0
self . cancel_gen = False
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client = self . session . get_client ( client_id )
client . generated_text = " "
client . cancel_generation = False
client . continuing = False
client . first_chunk = True
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if not self . model :
ASCIIColors . error ( " Model not selected. Please select a model " )
self . error ( " Model not selected. Please select a model " , client_id = client_id )
return
if not self . busy :
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if client . discussion is None :
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if self . db . does_last_discussion_have_messages ( ) :
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client . discussion = self . db . create_discussion ( )
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else :
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client . discussion = self . db . load_last_discussion ( )
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prompt = text
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try :
nb_tokens = len ( self . model . tokenize ( prompt ) )
except :
nb_tokens = None
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message = client . discussion . add_message (
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message_type = MSG_TYPE . MSG_TYPE_CONTENT . value ,
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sender_type = SENDER_TYPES . SENDER_TYPES_USER . value ,
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sender = self . config . user_name . strip ( ) if self . config . use_user_name_in_discussions else self . config . user_name ,
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content = prompt ,
metadata = None ,
parent_message_id = self . message_id ,
nb_tokens = nb_tokens
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)
ASCIIColors . green ( " Starting message generation by " + self . personality . name )
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client . generation_thread = threading . Thread ( target = self . start_message_generation , args = ( message , message . id , client_id ) )
client . generation_thread . start ( )
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self . sio . sleep ( 0.01 )
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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 . error ( " I am busy. Come back later. " , client_id = client_id )
else :
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if " lollms " in text . lower ( ) :
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self . summoned = True
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# def scrape_and_save(self, url, file_path):
# # Send a GET request to the URL
# response = requests.get(url)
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# # Parse the HTML content using BeautifulSoup
# soup = BeautifulSoup(response.content, 'html.parser')
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# # Find all the text content in the webpage
# text_content = soup.get_text()
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# # Remove extra returns and spaces
# text_content = ' '.join(text_content.split())
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# # Save the text content as a text file
# with open(file_path, 'w', encoding="utf-8") as file:
# file.write(text_content)
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# self.info(f"Webpage content saved to {file_path}")
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def rebuild_personalities ( self , reload_all = False ) :
if reload_all :
self . mounted_personalities = [ ]
loaded = self . mounted_personalities
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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 if p is not None ]
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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 )
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mounted_personalities . append ( personality )
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if self . config . auto_read and len ( personality . audio_samples ) > 0 :
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try :
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from lollms . services . tts . xtts . lollms_xtts import LollmsXTTS
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if self . tts is None :
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voice = self . config . xtts_current_voice
if voice != " main_voice " :
voices_folder = self . lollms_paths . custom_voices_path
else :
voices_folder = Path ( __file__ ) . parent . parent . parent / " services/xtts/voices "
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self . tts = LollmsXTTS (
self ,
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voices_folders = [ voices_folder , Path ( __file__ ) . parent . parent . parent / " services/xtts/voices " ] ,
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freq = self . config . xtts_freq
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)
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except Exception as ex :
trace_exception ( ex )
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self . warning ( f " Personality { personality . name } request using custom voice but couldn ' t load XTTS " )
except Exception as ex :
ASCIIColors . error ( f " Personality file not found or is corrupted ( { personality_path } ). \n Returned the following exception: { ex } \n Please 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 )
if personality . processor :
personality . processor . mounted ( )
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 ,
app = self ,
run_scripts = True ,
installation_option = InstallOption . FORCE_INSTALL )
mounted_personalities . append ( personality )
if personality . processor :
personality . processor . mounted ( )
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
# ================================== 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 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 make_discussion_title ( self , discussion , client_id = None ) :
"""
Builds a title for a discussion
"""
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# Get the list of messages
messages = discussion . get_messages ( )
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discussion_messages = f " { self . start_header_id_template } instruction { self . end_header_id_template } Create a short title to this discussion \n Your response should only contain the title without any comments. \n "
discussion_title = f " \n { self . start_header_id_template } Discussion title { self . end_header_id_template } "
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available_space = self . config . ctx_size - 150 - len ( self . model . tokenize ( discussion_messages ) ) - len ( self . model . tokenize ( discussion_title ) )
# Initialize a list to store the full messages
full_message_list = [ ]
# Accumulate messages until the cumulative number of tokens exceeds available_space
tokens_accumulated = 0
# Accumulate messages starting from message_index
for message in messages :
# Check if the message content is not empty and visible to the AI
if message . content != ' ' and (
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message . message_type < = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT_INVISIBLE_TO_USER . value and message . message_type != MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT_INVISIBLE_TO_AI . value ) :
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# Tokenize the message content
message_tokenized = self . model . tokenize (
" \n " + self . config . discussion_prompt_separator + message . sender + " : " + message . content . strip ( ) )
# Check if adding the message will exceed the available space
if tokens_accumulated + len ( message_tokenized ) > available_space :
break
# Add the tokenized message to the full_message_list
full_message_list . insert ( 0 , message_tokenized )
# Update the cumulative number of tokens
tokens_accumulated + = len ( message_tokenized )
# Build the final discussion messages by detokenizing the full_message_list
for message_tokens in full_message_list :
discussion_messages + = self . model . detokenize ( message_tokens )
discussion_messages + = discussion_title
title = [ " " ]
def receive (
chunk : str ,
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message_type : MSG_OPERATION_TYPE
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) :
if chunk :
title [ 0 ] + = chunk
antiprompt = self . personality . detect_antiprompt ( title [ 0 ] )
if antiprompt :
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ASCIIColors . warning ( f " \n { antiprompt } detected. Stopping generation " )
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title [ 0 ] = self . remove_text_from_string ( title [ 0 ] , antiprompt )
return False
else :
return True
self . _generate ( discussion_messages , 150 , client_id , receive )
ASCIIColors . info ( title [ 0 ] )
return title [ 0 ]
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def get_discussion_to ( self , client_id , message_id = - 1 ) :
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messages = self . session . get_client ( client_id ) . discussion . get_messages ( )
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full_message_list = [ ]
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ump = f " { self . start_header_id_template } { self . config . user_name . strip ( ) if self . config . use_user_name_in_discussions else self . personality . user_message_prefix } { self . end_header_id_template } "
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for message in messages :
if message [ " id " ] < = message_id or message_id == - 1 :
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if message [ " type " ] != MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT_INVISIBLE_TO_USER :
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if message [ " sender " ] == self . personality . name :
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full_message_list . append ( self . config . discussion_prompt_separator + self . personality . ai_message_prefix + message [ " content " ] )
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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 " ] :
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discussion_messages = self . config . discussion_prompt_separator + self . personality . personality_conditioning + link_text . join ( full_message_list [ - self . config [ " nb_messages_to_remember " ] : ] )
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else :
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discussion_messages = self . config . discussion_prompt_separator + self . personality . personality_conditioning + link_text . join ( full_message_list )
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return discussion_messages # Removes the last return
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def set_message_content ( self , full_text : str , callback : Callable [ [ str | list | None , MSG_OPERATION_TYPE , str , Any | None ] , bool ] | None = None , client_id = 0 ) :
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""" This sends full text to front end
Args :
step_text ( dict ) : The step text
callback ( callable , optional ) : A callable with this signature ( str , MSG_TYPE ) to send the text to . Defaults to None .
"""
if not callback :
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callback = partial ( self . process_data , client_id = client_id )
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if callback :
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callback ( full_text , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT )
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def emit_socket_io_info ( self , name , data , client_id ) :
run_async ( partial ( self . sio . emit , name , data , to = client_id ) )
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def notify (
self ,
content ,
notification_type : NotificationType = NotificationType . NOTIF_SUCCESS ,
duration : int = 4 ,
client_id = None ,
display_type : NotificationDisplayType = NotificationDisplayType . TOAST ,
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verbose : bool | None = None ,
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) :
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if verbose is None :
verbose = self . verbose
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run_async ( partial ( self . sio . emit , ' notification ' , {
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' content ' : content ,
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' notification_type ' : notification_type . value ,
" duration " : duration ,
' display_type ' : display_type . value
} , to = client_id
)
)
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if verbose :
if notification_type == NotificationType . NOTIF_SUCCESS :
ASCIIColors . success ( content )
elif notification_type == NotificationType . NOTIF_INFO :
ASCIIColors . info ( content )
elif notification_type == NotificationType . NOTIF_WARNING :
ASCIIColors . warning ( content )
else :
ASCIIColors . red ( content )
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def refresh_files ( self , client_id = None ) :
run_async ( partial ( self . sio . emit , ' refresh_files ' , to = client_id
)
)
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def new_message ( self ,
client_id ,
sender = None ,
content = " " ,
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message_type : MSG_OPERATION_TYPE = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT ,
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sender_type : SENDER_TYPES = SENDER_TYPES . SENDER_TYPES_AI ,
open = False
) :
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client = self . session . get_client ( client_id )
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#self.close_message(client_id)
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if sender == None :
sender = self . personality . name
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msg = client . discussion . add_message (
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message_type = message_type . value ,
sender_type = sender_type . value ,
sender = sender ,
content = content ,
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steps = [ ] ,
metadata = None ,
ui = None ,
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rank = 0 ,
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parent_message_id = client . discussion . current_message . id if client . discussion . current_message is not None else 0 ,
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binding = self . config [ " binding_name " ] ,
model = self . config [ " model_name " ] ,
personality = self . config [ " personalities " ] [ self . config [ " active_personality_id " ] ] ,
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created_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
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) # first the content is empty, but we'll fill it at the end
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run_async ( partial (
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self . sio . emit , ' new_message ' ,
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{
" sender " : sender ,
" message_type " : message_type . value ,
" sender_type " : SENDER_TYPES . SENDER_TYPES_AI . value ,
" content " : content ,
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" metadata " : None ,
" ui " : None ,
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" id " : msg . id ,
" parent_message_id " : msg . parent_message_id ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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' created_at ' : client . discussion . current_message . created_at ,
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' started_generating_at ' : client . discussion . current_message . started_generating_at ,
' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
' nb_tokens ' : client . discussion . current_message . nb_tokens ,
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' open ' : open
} , to = client_id
)
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)
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def new_block ( self ,
client_id ,
sender = None ,
content = " " ,
parameters = None ,
metadata = None ,
ui = None ,
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message_type : MSG_OPERATION_TYPE = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT ,
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sender_type : SENDER_TYPES = SENDER_TYPES . SENDER_TYPES_AI ,
open = False
) :
# like new_message but without adding the information to the database
client = self . session . get_client ( client_id )
run_async ( partial (
self . sio . emit , ' new_message ' ,
{
" sender " : sender ,
" message_type " : message_type . value ,
" sender_type " : SENDER_TYPES . SENDER_TYPES_AI . value ,
" content " : content ,
" parameters " : parameters ,
" metadata " : metadata ,
" ui " : ui ,
" id " : 0 ,
" parent_message_id " : 0 ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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' created_at ' : client . discussion . current_message . created_at ,
' started_generating_at ' : client . discussion . current_message . started_generating_at ,
' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
' nb_tokens ' : client . discussion . current_message . nb_tokens ,
' open ' : open
} , to = client_id
)
)
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def send_refresh ( self , client_id ) :
client = self . session . get_client ( client_id )
run_async (
partial ( self . sio . emit , ' update_message ' , {
" sender " : client . discussion . current_message . sender ,
' id ' : client . discussion . current_message . id ,
' content ' : client . discussion . current_message . content ,
' discussion_id ' : client . discussion . discussion_id ,
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' operation_type ' : MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT . value ,
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' message_type ' : client . discussion . current_message . message_type ,
' created_at ' : client . discussion . current_message . created_at ,
' started_generating_at ' : client . discussion . current_message . started_generating_at ,
' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
' nb_tokens ' : client . discussion . current_message . nb_tokens ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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} , to = client_id
)
)
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def update_message ( self , client_id , chunk ,
parameters = None ,
metadata = [ ] ,
ui = None ,
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operation_type : MSG_OPERATION_TYPE = None
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) :
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client = self . session . get_client ( client_id )
client . discussion . current_message . finished_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
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client . discussion . current_message . nb_tokens = self . nb_received_tokens
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mtdt = json . dumps ( metadata , indent = 4 ) if metadata is not None and type ( metadata ) == list else metadata
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if self . nb_received_tokens == 1 :
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client . discussion . current_message . started_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . update_message_step ( client_id , " ✍ generating ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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run_async (
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partial ( self . sio . emit , ' update_message ' , {
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" sender " : self . personality . name ,
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' id ' : client . discussion . current_message . id ,
' content ' : chunk ,
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' ui ' : client . discussion . current_message . ui if ui is None else ui ,
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' discussion_id ' : client . discussion . discussion_id ,
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' operation_type ' : operation_type . value if operation_type is not None else MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_ADD_CHUNK . value if self . nb_received_tokens > 1 else MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT . value ,
' message_type ' : MSG_TYPE . MSG_TYPE_CONTENT . value ,
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' created_at ' : client . discussion . current_message . created_at ,
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' started_generating_at ' : client . discussion . current_message . started_generating_at ,
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' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
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' nb_tokens ' : client . discussion . current_message . nb_tokens ,
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' parameters ' : parameters ,
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' metadata ' : metadata ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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} , to = client_id
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)
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)
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if operation_type and operation_type . value < MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_INFO . value :
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client . discussion . update_message ( client . generated_text , new_metadata = mtdt , new_ui = ui , started_generating_at = client . discussion . current_message . started_generating_at , nb_tokens = client . discussion . current_message . nb_tokens )
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def update_message_content ( self , client_id , chunk , operation_type : MSG_OPERATION_TYPE = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT , message_type : MSG_TYPE = None ) :
client = self . session . get_client ( client_id )
client . discussion . current_message . finished_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
client . discussion . current_message . nb_tokens = self . nb_received_tokens
if self . nb_received_tokens == 1 :
client . discussion . current_message . started_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
run_async (
partial ( self . sio . emit , ' update_message ' , {
" sender " : self . personality . name ,
' id ' : client . discussion . current_message . id ,
' content ' : chunk ,
' discussion_id ' : client . discussion . discussion_id ,
' operation_type ' : operation_type . value ,
' message_type ' : client . discussion . current_message . message_type if message_type is None else message_type ,
' created_at ' : client . discussion . current_message . created_at ,
' started_generating_at ' : client . discussion . current_message . started_generating_at ,
' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
' nb_tokens ' : client . discussion . current_message . nb_tokens ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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} , to = client_id
)
)
client . discussion . update_message_content ( client . generated_text , started_generating_at = client . discussion . current_message . started_generating_at , nb_tokens = client . discussion . current_message . nb_tokens )
def update_message_step ( self , client_id , step_text , msg_operation_type : MSG_OPERATION_TYPE = None ) :
client = self . session . get_client ( client_id )
if msg_operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP :
client . discussion . current_message . add_step ( step_text , " instant " , True , True )
elif msg_operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_START :
client . discussion . current_message . add_step ( step_text , " start_end " , True , False )
elif msg_operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS :
client . discussion . current_message . add_step ( step_text , " start_end " , True , True )
elif msg_operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_FAILURE :
client . discussion . current_message . add_step ( step_text , " start_end " , False , True )
run_async (
partial ( self . sio . emit , ' update_message ' , {
' id ' : client . discussion . current_message . id ,
' discussion_id ' : client . discussion . discussion_id ,
' operation_type ' : msg_operation_type . value ,
' steps ' : client . discussion . current_message . steps ,
} , to = client_id
)
)
def update_message_metadata ( self , client_id , metadata ) :
client = self . session . get_client ( client_id )
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md = json . dumps ( metadata ) if type ( metadata ) == dict or type ( metadata ) == list else metadata
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run_async (
partial ( self . sio . emit , ' update_message ' , {
" sender " : self . personality . name ,
' id ' : client . discussion . current_message . id ,
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' metadata ' : md ,
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' discussion_id ' : client . discussion . discussion_id ,
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' operation_type ' : MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_JSON_INFOS . value ,
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} , to = client_id
)
)
client . discussion . update_message_metadata ( metadata )
def update_message_ui ( self , client_id , ui ) :
client = self . session . get_client ( client_id )
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run_async (
partial ( self . sio . emit , ' update_message ' , {
" sender " : self . personality . name ,
' id ' : client . discussion . current_message . id ,
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' ui ' : ui ,
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' discussion_id ' : client . discussion . discussion_id ,
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' operation_type ' : MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_UI . value ,
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} , to = client_id
)
)
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client . discussion . update_message_ui ( ui )
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def close_message ( self , client_id ) :
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client = self . session . get_client ( client_id )
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for msg in client . discussion . messages :
if msg . steps is not None :
for step in msg . steps :
step [ " done " ] = True
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if not client . discussion :
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return
#fix halucination
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if len ( client . generated_text ) > 0 and len ( self . start_header_id_template ) > 0 :
client . generated_text = client . generated_text . split ( f " { self . start_header_id_template } " ) [ 0 ]
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# Send final message
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client . discussion . current_message . finished_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
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try :
client . discussion . current_message . nb_tokens = len ( self . model . tokenize ( client . generated_text ) )
except :
client . discussion . current_message . nb_tokens = None
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run_async (
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partial ( self . sio . emit , ' close_message ' , {
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" sender " : self . personality . name ,
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" id " : client . discussion . current_message . id ,
" content " : client . generated_text ,
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' binding ' : self . binding . binding_folder_name ,
' model ' : self . model . model_name ,
' personality ' : self . personality . name ,
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' created_at ' : client . discussion . current_message . created_at ,
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' started_generating_at ' : client . discussion . current_message . started_generating_at ,
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' finished_generating_at ' : client . discussion . current_message . finished_generating_at ,
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' nb_tokens ' : client . discussion . current_message . nb_tokens ,
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} , to = client_id
)
)
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def process_data (
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self ,
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data : str | list | None ,
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operation_type : MSG_OPERATION_TYPE ,
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client_id : str = 0 ,
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personality : AIPersonality = None
) :
"""
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Processes a data of generated text
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"""
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client = self . session . get_client ( client_id )
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if data is None and operation_type in [ MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_ADD_CHUNK ] :
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return
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if data is not None :
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if not client_id in list ( self . session . clients . keys ( ) ) :
self . error ( " Connection lost " , client_id = client_id )
return
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if operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP :
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ASCIIColors . info ( " --> Step: " + data )
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self . update_message_step ( client_id , data , operation_type )
elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_START :
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ASCIIColors . info ( " --> Step started: " + data )
self . update_message_step ( client_id , data , operation_type )
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS :
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ASCIIColors . success ( " --> Step ended: " + data )
self . update_message_step ( client_id , data , operation_type )
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_FAILURE :
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ASCIIColors . success ( " --> Step ended: " + data )
self . update_message_step ( client_id , data , operation_type )
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_WARNING :
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self . warning ( data , client_id = client_id )
ASCIIColors . error ( " --> Exception from personality: " + data )
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_EXCEPTION :
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self . error ( data , client_id = client_id )
ASCIIColors . error ( " --> Exception from personality: " + data )
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return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_INFO :
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self . info ( data , client_id = client_id )
ASCIIColors . info ( " --> Info: " + data )
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return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_UI :
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self . update_message_ui ( client_id , data )
return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_JSON_INFOS :
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self . update_message_metadata ( client_id , data )
return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_NEW_MESSAGE :
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self . nb_received_tokens = 0
self . start_time = datetime . now ( )
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . update_message_step ( client_id , " ✍ generating ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . new_message (
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client_id ,
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self . personality . name if personality is None else personality . name ,
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data ,
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message_type = MSG_TYPE . MSG_TYPE_CONTENT
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)
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return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_FINISHED_MESSAGE :
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self . close_message ( client_id )
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return
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elif operation_type == MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_ADD_CHUNK :
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if self . nb_received_tokens == 0 :
self . start_time = datetime . now ( )
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try :
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . update_message_step ( client_id , " ✍ generating ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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except Exception as ex :
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trace_exception ( ex )
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ASCIIColors . warning ( " Couldn ' t send status update to client " )
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dt = ( datetime . now ( ) - self . start_time ) . seconds
if dt == 0 :
dt = 1
spd = self . nb_received_tokens / dt
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if self . config . debug_show_chunks :
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print ( data , end = " " , flush = True )
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#ASCIIColors.green(f"Received {self.nb_received_tokens} tokens (speed: {spd:.2f}t/s) ",end="\r",flush=True)
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sys . stdout = sys . __stdout__
sys . stdout . flush ( )
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if data :
client . generated_text + = data
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antiprompt = self . personality . detect_antiprompt ( client . generated_text )
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if antiprompt :
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ASCIIColors . warning ( f " \n { antiprompt } detected. Stopping generation " )
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client . generated_text = self . remove_text_from_string ( client . generated_text , antiprompt )
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self . update_message_content ( client_id , client . generated_text , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT )
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return False
else :
self . nb_received_tokens + = 1
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if client . continuing and client . first_chunk :
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self . update_message_content ( client_id , client . generated_text , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT )
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else :
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self . update_message_content ( client_id , data , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_ADD_CHUNK )
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client . first_chunk = False
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# 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
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elif operation_type in [ MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT_INVISIBLE_TO_AI , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT_INVISIBLE_TO_USER ] :
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if self . nb_received_tokens == 0 :
self . start_time = datetime . now ( )
try :
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . update_message_step ( client_id , " ✍ generating ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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except Exception as ex :
ASCIIColors . warning ( " Couldn ' t send status update to client " )
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client . generated_text = data
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antiprompt = self . personality . detect_antiprompt ( client . generated_text )
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if antiprompt :
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ASCIIColors . warning ( f " \n { antiprompt } detected. Stopping generation " )
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client . generated_text = self . remove_text_from_string ( client . generated_text , antiprompt )
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self . update_message_content ( client_id , client . generated_text , operation_type )
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return False
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self . update_message_content ( client_id , data , operation_type )
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return True
# Stream the generated text to the frontend
else :
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self . update_message_content ( client_id , data , operation_type )
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return True
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def generate ( self , full_prompt , prompt , context_details , n_predict , client_id , callback = None ) :
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if self . config . debug and self . config . debug_show_final_full_prompt :
ASCIIColors . highlight ( full_prompt , [ r for r in [
self . config . discussion_prompt_separator ,
self . config . start_header_id_template ,
self . config . end_header_id_template ,
self . config . separator_template ,
self . config . start_user_header_id_template ,
self . config . end_user_header_id_template ,
self . config . end_user_message_id_template ,
self . config . start_ai_header_id_template ,
self . config . end_ai_header_id_template ,
self . config . end_ai_message_id_template ,
self . config . system_message_template ,
] if r != " " and r != " \n " ] )
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if self . config . use_smart_routing :
if self . config . smart_routing_router_model != " " and len ( self . config . smart_routing_models_by_power ) > = 2 :
ASCIIColors . yellow ( " Using smart routing " )
self . personality . step_start ( " Routing request " )
self . back_model = f " { self . binding . binding_folder_name } :: { self . model . model_name } "
try :
binding , model_name = self . model_path_to_binding_model ( self . config . smart_routing_router_model )
self . select_model ( binding , model_name )
output_id = self . personality . multichoice_question ( " assess the complexity of the following prompt (higher means more complex, lower less complex), if the user asking simple questions or just saying hello, please select the lowest model. " , [ str ( i ) for i in range ( len ( self . config . smart_routing_models_by_power ) ) ] , full_prompt )
if output_id > = 0 and output_id < len ( self . config . smart_routing_models_by_power ) :
binding , model_name = self . model_path_to_binding_model ( self . config . smart_routing_models_by_power [ output_id ] )
self . select_model ( binding , model_name )
self . personality . step_end ( " Routing request " )
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self . personality . step ( f " Complexity level: { output_id } " )
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self . personality . step ( f " Selected { self . config . smart_routing_models_by_power [ output_id ] } " )
except Exception as ex :
self . error ( " Failed to route beceause of this error : " + str ( ex ) )
self . personality . step_end ( " Routing request " , False )
else :
ASCIIColors . yellow ( " Warning! Smart routing is active but one of the following requirements are not met " )
ASCIIColors . yellow ( " - smart_routing_router_model must be set correctly " )
ASCIIColors . yellow ( " - smart_routing_models_by_power must contain at least one model " )
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if self . personality . processor is not None :
ASCIIColors . info ( " Running workflow " )
try :
self . personality . callback = callback
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client = self . session . get_client ( client_id )
self . personality . vectorizer = client . discussion . vectorizer
self . personality . text_files = client . discussion . text_files
self . personality . image_files = client . discussion . image_files
self . personality . audio_files = client . discussion . audio_files
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output = self . personality . processor . run_workflow ( prompt , full_prompt , callback , context_details , client = client )
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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. \n Error: { ex } " )
ASCIIColors . error ( traceback_text )
if callback :
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callback ( f " Workflow run failed \n Error: { ex } " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_EXCEPTION )
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return
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print ( " Finished executing the workflow " )
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return output
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txt = self . _generate ( full_prompt , n_predict , client_id , callback )
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ASCIIColors . success ( " \n Finished executing the generation " )
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if self . config . use_smart_routing and self . config . restore_model_after_smart_routing :
if self . config . smart_routing_router_model != " " and len ( self . config . smart_routing_models_by_power ) > = 2 :
ASCIIColors . yellow ( " Restoring model " )
self . personality . step_start ( " Restoring main model " )
binding , model_name = self . model_path_to_binding_model ( self . back_model )
self . select_model ( binding , model_name )
self . personality . step_end ( " Restoring main model " )
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return txt
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def _generate ( self , prompt , n_predict , client_id , callback = None ) :
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client = self . session . get_client ( client_id )
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if client is None :
return None
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self . nb_received_tokens = 0
self . start_time = datetime . now ( )
if self . model is not None :
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if self . model . binding_type == BindingType . TEXT_IMAGE and len ( client . discussion . image_files ) > 0 :
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if self . config [ " override_personality_model_parameters " ] :
output = self . model . generate_with_images (
prompt ,
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client . discussion . image_files ,
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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 :
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prompt = " \n " . join ( [
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f " { self . start_header_id_template } { self . system_message_template } { self . end_header_id_template } I am an AI assistant that can converse and analyze images. When asked to locate something in an image you send, I will reply with: " ,
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" boundingbox(image_index, label, left, top, width, height) " ,
" Where: " ,
" image_index: 0-based index of the image " ,
" label: brief description of what is located " ,
" left, top: x,y coordinates of top-left box corner (0-1 scale) " ,
" width, height: box dimensions as fraction of image size " ,
" Coordinates have origin (0,0) at top-left, (1,1) at bottom-right. " ,
" For other queries, I will respond conversationally to the best of my abilities. " ,
prompt
] )
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output = self . model . generate_with_images (
prompt ,
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client . discussion . image_files ,
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callback = callback ,
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n_predict = n_predict ,
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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 ' ]
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)
try :
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post_processed_output = process_ai_output ( output , client . discussion . image_files , client . discussion . discussion_folder )
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if len ( post_processed_output ) != output :
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self . process_data ( post_processed_output , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT , client_id = client_id )
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except Exception as ex :
ASCIIColors . error ( str ( ex ) )
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else :
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 ,
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n_predict = n_predict ,
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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
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def start_message_generation ( self , message , message_id , client_id , is_continue = False , generation_type = None , force_using_internet = False ) :
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client = self . session . get_client ( client_id )
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if self . personality is None :
self . warning ( " Select a personality " )
return
ASCIIColors . info ( f " Text generation requested by client: { client_id } " )
# send the message to the bot
print ( f " Received message : { message . content } " )
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if client . discussion :
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try :
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# First we need to send the new message ID to the client
if is_continue :
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client . discussion . load_message ( message_id )
client . generated_text = message . content
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else :
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self . send_refresh ( client_id )
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self . new_message ( client_id , self . personality . name , " " )
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_START )
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# prepare query and reception
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self . discussion_messages , self . current_message , tokens , context_details , internet_search_infos = self . prepare_query ( client_id , message_id , is_continue , n_tokens = self . config . min_n_predict , generation_type = generation_type , force_using_internet = force_using_internet , previous_chunk = client . generated_text if is_continue else " " )
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ASCIIColors . info ( f " prompt has { self . config . ctx_size - context_details [ ' available_space ' ] } tokens " )
ASCIIColors . info ( f " warmup for generating up to { min ( context_details [ ' available_space ' ] , self . config . max_n_predict ) } tokens " )
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self . prepare_reception ( client_id )
self . generating = True
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client . processing = True
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try :
self . generate (
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self . discussion_messages ,
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self . current_message ,
context_details = context_details ,
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n_predict = min ( self . config . ctx_size - len ( tokens ) - 1 , self . config . max_n_predict ) ,
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client_id = client_id ,
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callback = partial ( self . process_data , client_id = client_id )
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)
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if self . tts and self . config . auto_read and len ( self . personality . audio_samples ) > 0 :
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try :
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self . process_data ( " Generating voice output " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_START , client_id = client_id )
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from lollms . services . tts . xtts . lollms_xtts import LollmsXTTS
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voice = self . config . xtts_current_voice
if voice != " main_voice " :
voices_folder = self . lollms_paths . custom_voices_path
else :
voices_folder = Path ( __file__ ) . parent . parent . parent / " services/xtts/voices "
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if self . xtts . ready :
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language = convert_language_name ( self . personality . language )
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self . xtts . set_speaker_folder ( Path ( self . personality . audio_samples [ 0 ] ) . parent )
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fn = self . personality . name . lower ( ) . replace ( ' ' , " _ " ) . replace ( ' . ' , ' ' )
fn = f " { fn } _ { message_id } .wav "
url = f " audio/ { fn } "
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self . xtts . tts_file ( client . generated_text , Path ( self . personality . audio_samples [ 0 ] ) . name , f " { fn } " , language = language )
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fl = f " \n " . join ( [
f " <audio controls> " ,
f ' <source src= " { url } " type= " audio/wav " > ' ,
f ' Your browser does not support the audio element. ' ,
f ' </audio> '
] )
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self . process_data ( " Generating voice output " , operation_type = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS , client_id = client_id )
self . process_data ( fl , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_UI , client_id = client_id )
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else :
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self . InfoMessage ( " xtts is not up yet. \n Please wait for it to load then try again. This may take some time. " )
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except Exception as ex :
ASCIIColors . error ( " Couldn ' t read " )
trace_exception ( ex )
print ( )
ASCIIColors . success ( " ## Done Generation ## " )
print ( )
except Exception as ex :
trace_exception ( ex )
print ( )
ASCIIColors . error ( " ## Generation Error ## " )
print ( )
self . cancel_gen = False
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sources_text = " "
if len ( context_details [ " documentation_entries " ] ) > 0 :
sources_text + = ' <div class= " text-gray-400 mr-10px " >Sources:</div> '
sources_text + = ' <div class= " mt-4 flex flex-col items-start gap-x-2 gap-y-1.5 text-sm " style= " max-height: 500px; overflow-y: auto; " > '
for source in context_details [ " documentation_entries " ] :
title = source [ " document_title " ]
path = source [ " document_path " ]
content = source [ " chunk_content " ]
size = source [ " chunk_size " ]
distance = source [ " distance " ]
sources_text + = f '''
< div class = " source-item " >
< button onclick = " var details = document.getElementById( ' source-details- {title} ' ); details.style.display = details.style.display === ' none ' ? ' block ' : ' none ' ; " style = " text-align: left; font-weight: bold; " > < strong > { title } < / strong > < / button >
< div id = " source-details- {title} " style = " display:none; " >
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< div style = " max-height: 200px; overflow-y: auto; " >
< p > < strong > Path : < / strong > { path } < / p >
< p > < strong > Content : < / strong > { content } < / p >
< p > < strong > Size : < / strong > { size } < / p >
< p > < strong > Distance : < / strong > { distance } < / p >
< / div >
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< / div >
< / div >
'''
sources_text + = ' </div> '
self . personality . ui ( sources_text )
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if len ( context_details [ " skills " ] ) > 0 :
sources_text + = ' <div class= " text-gray-400 mr-10px " >Memories:</div> '
sources_text + = ' <div class= " mt-4 flex flex-col items-start gap-x-2 gap-y-1.5 text-sm " style= " max-height: 500px; overflow-y: auto; " > '
ind = 0
for skill in context_details [ " skills " ] :
sources_text + = f '''
< div class = " source-item " >
< button onclick = " var details = document.getElementById( ' source-details- {ind} ' ); details.style.display = details.style.display === ' none ' ? ' block ' : ' none ' ; " style = " text-align: left; font-weight: bold; " > < strong > Memory { ind } < / strong > < / button >
< div id = " source-details- {ind} " style = " display:none; " >
< div style = " max-height: 200px; overflow-y: auto; " >
< pre > { skill } < / pre >
< / div >
< / div >
< / div >
'''
ind + = 1
sources_text + = ' </div> '
self . personality . ui ( sources_text )
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# Send final message
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if self . config . activate_internet_search or force_using_internet or generation_type == " full_context_with_internet " :
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from lollms . internet import get_favicon_url , get_root_url
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sources_text + = '''
< div class = " mt-4 text-sm " >
< div class = " text-gray-500 font-semibold mb-2 " > Sources : < / div >
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< div class = " grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4 h-64 overflow-y-auto scrollbar-thin scrollbar-thumb-gray-300 scrollbar-track-gray-100 " >
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'''
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for source in internet_search_infos :
url = source [ " url " ]
title = source [ " title " ]
brief = source [ " brief " ]
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favicon_url = get_favicon_url ( url ) or " /personalities/generic/lollms/assets/logo.png "
root_url = get_root_url ( url )
sources_text + = f '''
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< div class = " relative flex flex-col items-start gap-2 rounded-lg border border-gray-200 bg-white p-3 shadow-sm transition duration-200 ease-in-out transform hover:scale-105 hover:border-gray-300 hover:shadow-lg dark:border-gray-700 dark:bg-gray-800 dark:hover:border-gray-600 dark:hover:shadow-lg animate-fade-in " >
< a class = " flex items-center w-full " target = " _blank " href = " {url} " title = " {brief} " >
< img class = " h-8 w-8 rounded-full " src = " {favicon_url} " alt = " {title} " onerror = " this.onerror=null;this.src= ' /personalities/generic/lollms/assets/logo.png ' ; " >
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< div class = " ml-2 " >
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< div class = " text-gray-700 dark:text-gray-300 font-semibold text-sm " > { title } < / div >
< div class = " text-gray-500 dark:text-gray-400 text-xs " > { root_url } < / div >
< div class = " text-gray-400 dark:text-gray-500 text-xs " > { brief } < / div >
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< / div >
< / a >
< / div >
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'''
sources_text + = '''
< / div >
< / div >
'''
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# Add CSS for animations and scrollbar styles
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sources_text + = '''
< style >
@keyframes fadeIn {
from { opacity : 0 ; transform : translateY ( 10 px ) ; }
to { opacity : 1 ; transform : translateY ( 0 ) ; }
}
. animate - fade - in {
animation : fadeIn 0.5 s ease - in - out ;
}
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. scrollbar - thin : : - webkit - scrollbar {
width : 8 px ;
}
. scrollbar - thin : : - webkit - scrollbar - thumb {
background - color : #cbd5e1; /* Tailwind gray-300 */
border - radius : 10 px ;
}
. scrollbar - thin : : - webkit - scrollbar - track {
background : #f9fafb; /* Tailwind gray-100 */
}
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< / style >
'''
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self . personality . ui ( sources_text )
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except Exception as ex :
trace_exception ( ex )
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try :
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self . update_message_step ( client_id , " 🔥 warming up ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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self . update_message_step ( client_id , " ✍ generating ... " , MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_STEP_END_SUCCESS )
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except Exception as ex :
ASCIIColors . warning ( " Couldn ' t send status update to client " )
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self . close_message ( client_id )
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client . processing = False
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# Clients are now kept forever
#if client.schedule_for_deletion:
# self.session.remove_client(client.client_id, client.client_id)
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ASCIIColors . success ( f " ╔══════════════════════════════════════════════════╗ " )
ASCIIColors . success ( f " ║ Done ║ " )
ASCIIColors . success ( f " ╚══════════════════════════════════════════════════╝ " )
if self . config . auto_title :
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d = client . discussion
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ttl = d . title ( )
if ttl is None or ttl == " " or ttl == " untitled " :
title = self . make_discussion_title ( d , client_id = client_id )
d . rename ( title )
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asyncio . run (
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self . sio . emit ( ' disucssion_renamed ' , {
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' status ' : True ,
' discussion_id ' : d . discussion_id ,
' title ' : title
} , to = client_id )
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)
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self . busy = False
else :
self . cancel_gen = False
#No discussion available
ASCIIColors . warning ( " No discussion selected!!! " )
self . error ( " No discussion selected!!! " , client_id = client_id )
print ( )
self . busy = False
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return " "
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def receive_and_generate ( self , text , client : Client , callback = None ) :
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prompt = text
try :
nb_tokens = len ( self . model . tokenize ( prompt ) )
except :
nb_tokens = None
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message = client . discussion . add_message (
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operation_type = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT . value ,
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sender_type = SENDER_TYPES . SENDER_TYPES_USER . value ,
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sender = self . config . user_name . strip ( ) if self . config . use_user_name_in_discussions else self . personality . user_message_prefix ,
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content = prompt ,
metadata = None ,
parent_message_id = self . message_id ,
nb_tokens = nb_tokens
)
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discussion_messages , current_message , tokens , context_details , internet_search_infos = self . prepare_query ( client . client_id , client . discussion . current_message . id , False , n_tokens = self . config . min_n_predict , force_using_internet = False )
self . new_message (
client . client_id ,
self . personality . name ,
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operation_type = MSG_OPERATION_TYPE . MSG_OPERATION_TYPE_SET_CONTENT ,
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content = " "
)
client . generated_text = " "
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ASCIIColors . info ( f " prompt has { self . config . ctx_size - context_details [ ' available_space ' ] } tokens " )
ASCIIColors . info ( f " warmup for generating up to { min ( context_details [ ' available_space ' ] , self . config . max_n_predict ) } tokens " )
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self . generate ( discussion_messages , current_message , context_details , min ( self . config . ctx_size - len ( tokens ) - 1 , self . config . max_n_predict ) , client . client_id , callback if callback else partial ( self . process_data , client_id = client . client_id ) )
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self . close_message ( client . client_id )
return client . generated_text