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######
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# Project : lollms-webui
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# File : api.py
# Author : ParisNeo with the help of the community
# 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 api . helpers import compare_lists
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from pathlib import Path
import importlib
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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 . personality import AIPersonality , PersonalityBuilder
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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import multiprocessing as mp
import threading
import time
import requests
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from tqdm import tqdm
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import traceback
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import sys
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from lollms . terminal import MainMenu
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import urllib
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import gc
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import ctypes
from functools import partial
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import json
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import shutil
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def terminate_thread ( thread ) :
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if thread :
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
exc = ctypes . py_object ( SystemExit )
res = ctypes . pythonapi . PyThreadState_SetAsyncExc ( thread_id , exc )
if res > 1 :
ctypes . pythonapi . PyThreadState_SetAsyncExc ( thread_id , None )
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del thread
gc . collect ( )
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raise SystemError ( " Failed to terminate the thread. " )
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else :
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, "
__license__ = " Apache 2.0 "
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import subprocess
import pkg_resources
# ===========================================================
# Manage automatic install scripts
def is_package_installed ( package_name ) :
try :
dist = pkg_resources . get_distribution ( package_name )
return True
except pkg_resources . DistributionNotFound :
return False
def install_package ( package_name ) :
try :
# Check if the package is already installed
__import__ ( package_name )
print ( f " { package_name } is already installed. " )
except ImportError :
print ( f " { package_name } is not installed. Installing... " )
# Install the package using pip
subprocess . check_call ( [ " pip " , " install " , package_name ] )
print ( f " { package_name } has been successfully installed. " )
def parse_requirements_file ( requirements_path ) :
with open ( requirements_path , ' r ' ) as f :
for line in f :
line = line . strip ( )
if not line or line . startswith ( ' # ' ) :
# Skip empty and commented lines
continue
package_name , _ , version_specifier = line . partition ( ' == ' )
package_name , _ , version_specifier = line . partition ( ' >= ' )
if is_package_installed ( package_name ) :
# The package is already installed
print ( f " { package_name } is already installed. " )
else :
# The package is not installed, install it
if version_specifier :
install_package ( f " { package_name } { version_specifier } " )
else :
install_package ( package_name )
# ===========================================================
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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 . 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
self . _current_ai_message_id = 0
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 ( ) :
# Create database object
self . db = DiscussionsDB ( self . db_path )
else :
# Create database object
self . db = DiscussionsDB ( self . lollms_paths . personal_path / " databases " / 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 ( )
self . db . add_missing_columns ( )
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ASCIIColors . success ( " ok " )
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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 : {
" current_discussion " : None ,
" generated_text " : " " ,
" cancel_generation " : False ,
" generation_thread " : None ,
" processing " : False ,
" schedule_for_deletion " : False
}
}
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# =========================================================================================
# Socket IO stuff
# =========================================================================================
@socketio.on ( ' connect ' )
def connect ( ) :
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#Create a new connection information
self . connections [ request . sid ] = {
" current_discussion " : None ,
" generated_text " : " " ,
" cancel_generation " : False ,
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" generation_thread " : None ,
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" processing " : False ,
" schedule_for_deletion " : False
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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 ' )
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 " ] :
self . connections [ request . sid ] [ " schedule_for_deletion " ] = True
else :
del self . connections [ request . sid ]
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except Exception as ex :
pass
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ASCIIColors . error ( f ' Client { request . sid } disconnected ' )
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@socketio.on ( ' cancel_install ' )
def cancel_install ( data ) :
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try :
model_name = data [ " model_name " ]
binding_folder = data [ " binding_folder " ]
model_url = data [ " model_url " ]
signature = f " { model_name } _ { binding_folder } _ { model_url } "
self . download_infos [ signature ] [ " cancel " ] = True
self . socketio . emit ( ' canceled ' , {
' status ' : True
} ,
room = request . sid
)
except Exception as ex :
trace_exception ( ex )
self . socketio . emit ( ' canceled ' , {
' status ' : False ,
' error ' : str ( ex )
} ,
room = request . sid
)
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@socketio.on ( ' install_model ' )
def install_model ( data ) :
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room_id = request . sid
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def install_model_ ( ) :
print ( " Install model triggered " )
model_path = data [ " path " ]
progress = 0
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installation_dir = self . lollms_paths . personal_models_path / self . config [ " binding_name " ]
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filename = Path ( model_path ) . name
installation_path = installation_dir / filename
print ( " Model install requested " )
print ( f " Model path : { model_path } " )
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model_name = filename
binding_folder = self . config [ " binding_name " ]
model_url = model_path
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signature = f " { model_name } _ { binding_folder } _ { model_url } "
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try :
self . download_infos [ signature ] = {
" start_time " : datetime . now ( ) ,
" total_size " : self . binding . get_file_size ( model_path ) ,
" downloaded_size " : 0 ,
" progress " : 0 ,
" speed " : 0 ,
" cancel " : False
}
if installation_path . exists ( ) :
print ( " Error: Model already exists. please remove it first " )
socketio . emit ( ' install_progress ' , {
' status ' : False ,
' error ' : f ' model already exists. Please remove it first. \n The model can be found here: { installation_path } ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : self . download_infos [ signature ] [ ' progress ' ] ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
} , room = room_id
)
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socketio . emit ( ' install_progress ' , {
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' status ' : True ,
' progress ' : progress ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : self . download_infos [ signature ] [ ' progress ' ] ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
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} , room = room_id )
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def callback ( downloaded_size , total_size ) :
progress = ( downloaded_size / total_size ) * 100
now = datetime . now ( )
dt = ( now - self . download_infos [ signature ] [ ' start_time ' ] ) . total_seconds ( )
speed = downloaded_size / dt
self . download_infos [ signature ] [ ' downloaded_size ' ] = downloaded_size
self . download_infos [ signature ] [ ' speed ' ] = speed
if progress - self . download_infos [ signature ] [ ' progress ' ] > 2 :
self . download_infos [ signature ] [ ' progress ' ] = progress
socketio . emit ( ' install_progress ' , {
' status ' : True ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : self . download_infos [ signature ] [ ' progress ' ] ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
} , room = room_id )
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if self . download_infos [ signature ] [ " cancel " ] :
raise Exception ( " canceled " )
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 ) )
trace_exception ( ex )
socketio . emit ( ' install_progress ' , {
' status ' : False ,
' error ' : ' canceled ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : self . download_infos [ signature ] [ ' progress ' ] ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
} , room = room_id
)
del self . download_infos [ signature ]
try :
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if installation_path . is_dir ( ) :
shutil . rmtree ( installation_path )
else :
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 } " )
return
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else :
try :
self . download_file ( model_path , installation_path , callback )
except Exception as ex :
ASCIIColors . warning ( str ( ex ) )
trace_exception ( ex )
socketio . emit ( ' install_progress ' , {
' status ' : False ,
' error ' : ' canceled ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : self . download_infos [ signature ] [ ' progress ' ] ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
} , room = room_id
)
del self . download_infos [ signature ]
installation_path . unlink ( )
return
socketio . emit ( ' install_progress ' , {
' status ' : True ,
' error ' : ' ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : self . download_infos [ signature ] [ ' start_time ' ] . strftime ( " % Y- % m- %d % H: % M: % S " ) ,
' total_size ' : self . download_infos [ signature ] [ ' total_size ' ] ,
' downloaded_size ' : self . download_infos [ signature ] [ ' downloaded_size ' ] ,
' progress ' : 100 ,
' speed ' : self . download_infos [ signature ] [ ' speed ' ] ,
} , room = room_id )
del self . download_infos [ signature ]
except Exception as ex :
trace_exception ( ex )
socketio . emit ( ' install_progress ' , {
' status ' : False ,
' error ' : str ( ex ) ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder ,
' model_url ' : model_url ,
' start_time ' : ' ' ,
' total_size ' : 0 ,
' downloaded_size ' : 0 ,
' progress ' : 0 ,
' speed ' : 0 ,
} , room = room_id
)
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tpe = threading . Thread ( target = install_model_ , args = ( ) )
tpe . start ( )
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@socketio.on ( ' uninstall_model ' )
def uninstall_model ( data ) :
model_path = data [ ' path ' ]
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installation_dir = self . lollms_paths . personal_models_path / self . config [ " binding_name " ]
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filename = Path ( model_path ) . name
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installation_path : Path = installation_dir / filename
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model_name = filename
binding_folder = self . config [ " binding_name " ]
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if not installation_path . exists ( ) :
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socketio . emit ( ' install_progress ' , {
' status ' : False ,
' error ' : ' The model does not exist ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder
} , room = request . sid )
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try :
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if installation_path . is_dir ( ) :
shutil . rmtree ( installation_path )
else :
installation_path . unlink ( )
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socketio . emit ( ' install_progress ' , {
' status ' : True ,
' error ' : ' ' ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder
} , 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 ( ' install_progress ' , {
' status ' : False ,
' error ' : f " Couldn ' t delete { installation_path } , please delete it manually and restart the app " ,
' model_name ' : model_name ,
' binding_folder ' : binding_folder
} , room = request . sid )
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@socketio.on ( ' new_discussion ' )
def new_discussion ( data ) :
client_id = request . sid
title = data [ " title " ]
self . connections [ client_id ] [ " current_discussion " ] = self . db . create_discussion ( title )
# Get the current timestamp
timestamp = datetime . now ( ) . strftime ( " % Y- % m- %d % H: % M: % S " )
# Return a success response
if self . connections [ client_id ] [ " current_discussion " ] is None :
self . connections [ client_id ] [ " current_discussion " ] = self . db . load_last_discussion ( )
if self . personality . welcome_message != " " :
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
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ASCIIColors . yellow ( f " Loading discussion for client { client_id } " )
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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 ( )
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jsons = [ m . to_json ( ) for m in messages ]
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self . socketio . emit ( ' discussion ' ,
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jsons ,
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room = client_id
)
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@socketio.on ( ' upload_file ' )
def upload_file ( data ) :
file = data [ ' file ' ]
filename = file . filename
save_path = self . lollms_paths . personal_uploads_path / filename # Specify the desired folder path
try :
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if not self . personality . processor is None :
file . save ( save_path )
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self . personality . processor . add_file ( save_path , partial ( self . process_chunk , client_id = request . sid ) )
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# File saved successfully
socketio . emit ( ' progress ' , { ' status ' : True , ' progress ' : 100 } )
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else :
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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 } )
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except Exception as e :
# Error occurred while saving the file
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socketio . emit ( ' progress ' , { ' status ' : False , ' error ' : str ( e ) } )
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@socketio.on ( ' cancel_generation ' )
def cancel_generation ( ) :
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client_id = request . sid
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self . cancel_gen = True
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#kill thread
ASCIIColors . error ( f ' Client { request . sid } requested cancelling generation ' )
terminate_thread ( self . connections [ client_id ] [ ' generation_thread ' ] )
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ASCIIColors . error ( f ' Client { request . sid } canceled generation ' )
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self . cancel_gen = False
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self . busy = False
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@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 )
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@socketio.on ( ' send_file ' )
def send_file ( data ) :
client_id = request . sid
self . connections [ client_id ] [ " generated_text " ] = " "
self . connections [ client_id ] [ " cancel_generation " ] = False
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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
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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 " ]
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File64BitsManager . b642file ( data [ " fileData " ] , file_path )
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if self . personality . processor :
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result = self . personality . processor . add_file ( file_path , partial ( self . process_chunk , client_id = client_id ) )
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else :
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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
)
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except Exception as ex :
ASCIIColors . error ( ex )
trace_exception ( ex )
self . socketio . emit ( ' file_received ' ,
{
" status " : False ,
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" filename " : data [ " filename " ] ,
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" error " : " Couldn ' t receive file: " + str ( ex )
} , room = client_id
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)
self . close_message ( client_id )
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@self.socketio.on ( ' cancel_text_generation ' )
def cancel_text_generation ( data ) :
client_id = request . sid
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self . connections [ client_id ] [ " requested_stop " ] = True
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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
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@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 )
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# 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
ASCIIColors . info ( f " Text generation requested by client: { client_id } " )
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if self . busy :
self . socketio . emit ( " busy " , { " message " : " I am busy. Come back later. " } , room = client_id )
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self . socketio . sleep ( 0 )
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ASCIIColors . warning ( f " OOps request { client_id } refused!! Server busy " )
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return
def generate_text ( ) :
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self . busy = True
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try :
model = self . model
self . connections [ client_id ] [ " is_generating " ] = True
self . connections [ client_id ] [ " requested_stop " ] = False
prompt = data [ ' prompt ' ]
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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 : ] )
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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 )
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fd = model . detokenize ( tk [ - min ( self . config . ctx_size - n_predicts , n_tokens ) : ] )
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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 " ] ,
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seed = parameters [ " seed " ] ,
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)
ASCIIColors . success ( f " \n done " )
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 " \n done " )
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self . busy = False
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else :
try :
personality : AIPersonality = self . personalities [ personality_id ]
ump = self . config . discussion_prompt_separator + self . config . user_name + " : " if self . config . use_user_name_in_discussions else self . personality . user_message_prefix
personality . model = model
cond_tk = personality . model . tokenize ( personality . personality_conditioning )
n_cond_tk = len ( cond_tk )
# Placeholder code for text generation
# Replace this with your actual text generation logic
print ( f " Text generation requested by client: { client_id } " )
self . answer [ " full_text " ] = ' '
full_discussion_blocks = self . 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 ( " \n done " )
# 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 " \n done " )
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self . busy = False
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except Exception as ex :
trace_exception ( ex )
self . socketio . emit ( ' generation_error ' , { ' error ' : str ( ex ) } , room = client_id )
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self . busy = False
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# Start the text generation task in a separate thread
task = self . socketio . start_background_task ( target = generate_text )
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@socketio.on ( ' generate_msg ' )
def generate_msg ( data ) :
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client_id = request . sid
self . connections [ client_id ] [ " generated_text " ] = " "
self . connections [ client_id ] [ " cancel_generation " ] = False
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if not self . model :
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self . notify ( " Model not selected. Please select a model " , False , client_id )
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return
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if not self . busy :
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if self . connections [ client_id ] [ " current_discussion " ] is None :
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if self . db . does_last_discussion_have_messages ( ) :
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self . connections [ client_id ] [ " current_discussion " ] = self . db . create_discussion ( )
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else :
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self . connections [ client_id ] [ " current_discussion " ] = self . db . load_last_discussion ( )
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prompt = data [ " prompt " ]
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ump = self . config . discussion_prompt_separator + self . config . user_name + " : " if self . config . use_user_name_in_discussions else self . personality . user_message_prefix
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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
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)
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ASCIIColors . green ( " Starting message generation by " + self . personality . name )
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self . connections [ client_id ] [ ' generation_thread ' ] = threading . Thread ( target = self . start_message_generation , args = ( message , message . id , client_id ) )
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self . connections [ client_id ] [ ' generation_thread ' ] . start ( )
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self . socketio . sleep ( 0.01 )
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ASCIIColors . info ( " Started generation task " )
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self . busy = True
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#tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id, client_id))
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#tpe.start()
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else :
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self . notify ( " I am busy. Come back later. " , False , client_id )
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@socketio.on ( ' generate_msg_from ' )
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def generate_msg_from ( data ) :
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client_id = request . sid
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if self . connections [ client_id ] [ " current_discussion " ] is None :
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ASCIIColors . warning ( " Please select a discussion " )
self . notify ( " Please select a discussion first " , False , client_id )
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return
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id_ = data [ ' id ' ]
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if id_ == - 1 :
message = self . connections [ client_id ] [ " current_discussion " ] . current_message
else :
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message = self . connections [ client_id ] [ " current_discussion " ] . get_message ( id_ )
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if message is None :
return
self . connections [ client_id ] [ ' generation_thread ' ] = threading . Thread ( target = self . start_message_generation , args = ( message , message . id , client_id ) )
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self . connections [ client_id ] [ ' generation_thread ' ] . start ( )
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@socketio.on ( ' continue_generate_msg_from ' )
def handle_connection ( data ) :
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client_id = request . sid
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if self . connections [ client_id ] [ " current_discussion " ] is None :
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ASCIIColors . yellow ( " Please select a discussion " )
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self . notify ( " Please select a discussion " , False , client_id )
return
id_ = data [ ' id ' ]
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if id_ == - 1 :
message = self . connections [ client_id ] [ " current_discussion " ] . current_message
else :
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message = self . connections [ client_id ] [ " current_discussion " ] . get_message ( id_ )
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self . connections [ client_id ] [ ' generation_thread ' ] = threading . Thread ( target = self . start_message_generation , args = ( message , message . id , client_id , True ) )
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self . connections [ client_id ] [ ' generation_thread ' ] . start ( )
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# 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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def rebuild_personalities ( self , reload_all = False ) :
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if reload_all :
self . mounted_personalities = [ ]
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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 ]
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mounted_personalities = [ ]
ASCIIColors . success ( f " ╔══════════════════════════════════════════════════╗ " )
ASCIIColors . success ( f " ║ Building mounted Personalities ║ " )
ASCIIColors . success ( f " ╚══════════════════════════════════════════════════╝ " )
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to_remove = [ ]
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for i , personality in enumerate ( self . config [ ' personalities ' ] ) :
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if i == self . config [ " active_personality_id " ] :
ASCIIColors . red ( " * " , end = " " )
ASCIIColors . green ( f " { personality } " )
else :
ASCIIColors . yellow ( f " { personality } " )
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if personality in loaded_names :
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mounted_personalities . append ( loaded [ loaded_names . index ( personality ) ] )
else :
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personality_path = self . lollms_paths . personalities_zoo_path / f " { personality } " if not " : " in personality else self . lollms_paths . personalities_zoo_path / f " { personality . split ( ' : ' ) [ 0 ] } "
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try :
personality = AIPersonality ( personality_path ,
self . lollms_paths ,
self . config ,
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model = self . model ,
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app = self ,
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selected_language = personality . split ( " : " ) [ 1 ] if " : " in personality else None ,
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run_scripts = True )
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mounted_personalities . append ( personality )
except Exception as ex :
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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. " )
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ASCIIColors . info ( " Trying to force reinstall " )
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if self . config [ " debug " ] :
print ( ex )
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try :
personality = AIPersonality (
personality_path ,
self . lollms_paths ,
self . config ,
self . model ,
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app = self ,
run_scripts = True ,
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selected_language = personality . split ( " : " ) [ 1 ] if " : " in personality else None ,
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installation_option = InstallOption . FORCE_INSTALL )
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mounted_personalities . append ( personality )
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except Exception as ex :
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ASCIIColors . error ( f " Couldn ' t load personality at { personality_path } " )
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trace_exception ( ex )
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ASCIIColors . info ( f " Unmounting personality " )
to_remove . append ( i )
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personality = AIPersonality ( None ,
self . lollms_paths ,
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self . config ,
self . model ,
run_scripts = True ,
installation_option = InstallOption . FORCE_INSTALL )
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mounted_personalities . append ( personality )
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ASCIIColors . info ( " Reverted to default personality " )
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print ( f ' selected : { self . config [ " active_personality_id " ] } ' )
ASCIIColors . success ( f " ╔══════════════════════════════════════════════════╗ " )
ASCIIColors . success ( f " ║ Done ║ " )
ASCIIColors . success ( f " ╚══════════════════════════════════════════════════╝ " )
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# 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
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return mounted_personalities
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# ================================== LOLLMSApp
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#properties
@property
def message_id ( self ) :
return self . _message_id
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@message_id.setter
def message_id ( self , id ) :
self . _message_id = id
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@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
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def download_file ( self , url , installation_path , callback = None ) :
"""
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Downloads a file from a URL , reports the download progress using a callback function , and displays a progress bar .
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Args :
url ( str ) : The URL of the file to download .
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installation_path ( str ) : The path where the file should be saved .
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callback ( function , optional ) : A callback function to be called during the download
with the progress percentage as an argument . Defaults to None .
"""
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try :
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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 :
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callback ( downloaded_size , total_size )
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progress_bar . update ( len ( chunk ) )
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if callback is not None :
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callback ( total_size , total_size )
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print ( " File downloaded successfully " )
except Exception as e :
print ( " Couldn ' t download file: " , str ( e ) )
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def prepare_reception ( self , client_id ) :
self . connections [ client_id ] [ " generated_text " ] = " "
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self . nb_received_tokens = 0
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def prepare_query ( self , client_id , message_id = - 1 , is_continue = False ) :
messages = self . connections [ client_id ] [ " current_discussion " ] . get_messages ( )
full_message_list = [ ]
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for i , message in enumerate ( messages ) :
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if message . id < message_id or ( message_id == - 1 and i < len ( messages ) - 1 ) :
if 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 ( ) )
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else :
break
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link_text = " \n " #self.personality.link_text
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if not is_continue :
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full_message_list . append ( self . config . discussion_prompt_separator + message . sender . replace ( " : " , " " ) + " : " + message . content . strip ( ) + link_text + self . personality . ai_message_prefix )
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else :
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full_message_list . append ( self . config . discussion_prompt_separator + message . sender . replace ( " : " , " " ) + " : " + message . content . strip ( ) )
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composed_messages = link_text . join ( full_message_list )
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t = self . model . tokenize ( composed_messages )
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cond_tk = self . model . tokenize ( self . personality . personality_conditioning )
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n_t = len ( t )
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n_cond_tk = len ( cond_tk )
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max_prompt_stx_size = 3 * int ( self . config . ctx_size / 4 )
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if n_cond_tk + n_t > max_prompt_stx_size :
nb_tk = max_prompt_stx_size - n_cond_tk
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composed_messages = self . model . detokenize ( t [ - nb_tk : ] )
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ASCIIColors . warning ( f " Cropping discussion to fit context [using { nb_tk } tokens/ { self . config . ctx_size } ] " )
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discussion_messages = composed_messages
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if len ( self . personality . files ) > 0 and self . personality . vectorizer :
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pr = PromptReshaper ( " !@>document chunks: \n {{ doc}} \n {{ conditionning}} \n {{ content}} " )
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emb = self . personality . vectorizer . embed_query ( message . content )
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docs , sorted_similarities = self . personality . vectorizer . recover_text ( emb , top_k = self . config . data_vectorization_nb_chunks )
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str_docs = " "
for doc , infos in zip ( docs , sorted_similarities ) :
str_docs + = f " document chunk: \n chunk path: { infos [ 0 ] } \n chunk content: { doc } "
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discussion_messages = pr . build ( {
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" doc " : str_docs ,
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" conditionning " : self . personality . personality_conditioning ,
" content " : discussion_messages
} , self . model . tokenize , self . model . detokenize , self . config . ctx_size , place_holders_to_sacrifice = [ " content " ] )
else :
pr = PromptReshaper ( " {{ conditionning}} \n {{ content}} " )
discussion_messages = pr . build ( {
" conditionning " : self . personality . personality_conditioning ,
" content " : discussion_messages
} , self . model . tokenize , self . model . detokenize , self . config . ctx_size , place_holders_to_sacrifice = [ " content " ] )
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tokens = self . model . tokenize ( discussion_messages )
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if self . config [ " debug " ] :
ASCIIColors . yellow ( discussion_messages )
ASCIIColors . info ( f " prompt size: { len ( tokens ) } tokens " )
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return discussion_messages , message . content , tokens
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def get_discussion_to ( self , client_id , message_id = - 1 ) :
messages = self . connections [ client_id ] [ " current_discussion " ] . get_messages ( )
full_message_list = [ ]
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ump = self . config . discussion_prompt_separator + self . config . user_name + " : " if self . config . use_user_name_in_discussions else self . personality . user_message_prefix
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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_TYPE . MSG_TYPE_FULL_INVISIBLE_TO_USER :
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if message [ " sender " ] == self . personality . name :
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full_message_list . append ( self . personality . ai_message_prefix + message [ " content " ] )
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else :
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full_message_list . append ( ump + message [ " content " ] )
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link_text = " \n " # self.personality.link_text
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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 " ] : ] )
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else :
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discussion_messages = 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 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 ( ) )
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if index != - 1 :
string = string [ : index ]
return string
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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 ,
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content ,
parameters = None ,
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metadata = None ,
ui = None ,
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message_type : MSG_TYPE = MSG_TYPE . MSG_TYPE_FULL ,
sender_type : SENDER_TYPES = SENDER_TYPES . SENDER_TYPES_AI
) :
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mtdt = metadata if metadata is None or type ( metadata ) == str else json . dumps ( metadata , indent = 4 )
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msg = self . connections [ client_id ] [ " current_discussion " ] . add_message (
message_type = message_type . value ,
sender_type = sender_type . value ,
sender = sender ,
content = content ,
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metadata = mtdt ,
ui = ui ,
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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 ,
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" parameters " : parameters ,
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" metadata " : metadata ,
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" ui " : ui ,
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" 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
)
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def update_message ( self , client_id , chunk ,
parameters = None ,
metadata = [ ] ,
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ui = None ,
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msg_type : MSG_TYPE = None
) :
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self . connections [ client_id ] [ " current_discussion " ] . current_message . finished_generating_at = datetime . now ( ) . strftime ( ' % Y- % m- %d % H: % M: % S ' )
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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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self . socketio . emit ( ' update_message ' , {
" sender " : self . personality . name ,
' id ' : self . connections [ client_id ] [ " current_discussion " ] . current_message . id ,
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' content ' : chunk , # self.connections[client_id]["generated_text"],
' ui ' : ui ,
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' 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 ,
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' parameters ' : parameters ,
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' metadata ' : metadata
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} , room = client_id
)
self . socketio . sleep ( 0.01 )
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self . connections [ client_id ] [ " current_discussion " ] . update_message ( self . connections [ client_id ] [ " generated_text " ] , new_metadata = mtdt , new_ui = ui )
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def close_message ( self , client_id ) :
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#fix halucination
self . connections [ client_id ] [ " generated_text " ] = self . connections [ client_id ] [ " generated_text " ] . split ( " !@> " ) [ 0 ]
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# 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
)
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def process_chunk (
self ,
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chunk : str ,
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message_type : MSG_TYPE ,
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parameters : dict = None ,
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metadata : list = None ,
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client_id : int = 0
) :
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"""
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Processes a chunk of generated text
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"""
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if message_type == MSG_TYPE . MSG_TYPE_STEP :
ASCIIColors . info ( " --> Step: " + chunk )
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if message_type == MSG_TYPE . MSG_TYPE_STEP_START :
ASCIIColors . info ( " --> Step started: " + chunk )
if message_type == MSG_TYPE . MSG_TYPE_STEP_END :
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if parameters [ ' status ' ] :
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ASCIIColors . success ( " --> Step ended: " + chunk )
else :
ASCIIColors . error ( " --> Step ended: " + chunk )
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if message_type == MSG_TYPE . MSG_TYPE_EXCEPTION :
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self . notify ( chunk , False , client_id )
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ASCIIColors . error ( " --> Exception from personality: " + chunk )
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if message_type == MSG_TYPE . MSG_TYPE_WARNING :
self . notify ( chunk , True , client_id )
ASCIIColors . error ( " --> Exception from personality: " + chunk )
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if message_type == MSG_TYPE . MSG_TYPE_INFO :
self . notify ( chunk , True , client_id )
ASCIIColors . info ( " --> Info: " + chunk )
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if message_type == MSG_TYPE . MSG_TYPE_UI :
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self . update_message ( client_id , " " , parameters , metadata , chunk , MSG_TYPE . MSG_TYPE_UI )
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if message_type == MSG_TYPE . MSG_TYPE_NEW_MESSAGE :
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self . nb_received_tokens = 0
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self . new_message (
client_id ,
self . personality . name ,
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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 ,
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message_type = MSG_TYPE ( parameters [ " type " ] ) )
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elif message_type == MSG_TYPE . MSG_TYPE_FINISHED_MESSAGE :
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self . close_message ( client_id )
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elif message_type == MSG_TYPE . MSG_TYPE_CHUNK :
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ASCIIColors . green ( f " Received { self . nb_received_tokens } tokens " , end = " \r " )
sys . stdout = sys . __stdout__
sys . stdout . flush ( )
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antiprompt = self . personality . detect_antiprompt ( self . connections [ client_id ] [ " generated_text " ] + chunk )
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if antiprompt :
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ASCIIColors . warning ( f " \n Detected hallucination with antiprompt: { antiprompt } " )
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self . connections [ client_id ] [ " generated_text " ] = self . remove_text_from_string ( self . connections [ client_id ] [ " generated_text " ] , antiprompt )
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self . update_message ( client_id , self . connections [ client_id ] [ " generated_text " ] , parameters , metadata , None , MSG_TYPE . MSG_TYPE_FULL )
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return False
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else :
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self . connections [ client_id ] [ " generated_text " ] + = chunk
self . nb_received_tokens + = 1
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self . update_message ( client_id , chunk , parameters , metadata )
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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
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# Stream the generated text to the main process
elif message_type == MSG_TYPE . MSG_TYPE_FULL :
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self . connections [ client_id ] [ " generated_text " ] = chunk
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self . nb_received_tokens + = 1
ASCIIColors . green ( f " Received { self . nb_received_tokens } tokens " , end = " \r " , flush = True )
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self . update_message ( client_id , chunk , parameters , metadata , ui = None , msg_type = message_type )
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return True
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# Stream the generated text to the frontend
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else :
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self . update_message ( client_id , chunk , parameters , metadata , ui = None , msg_type = message_type )
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return True
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def generate ( self , full_prompt , prompt , n_predict , client_id , callback = None ) :
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if self . personality . processor is not None :
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ASCIIColors . info ( " Running workflow " )
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try :
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self . personality . processor . run_workflow ( prompt , full_prompt , callback )
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except Exception as ex :
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trace_exception ( ex )
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# 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 )
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if callback :
callback ( f " Workflow run failed \n Error: { ex } " , MSG_TYPE . MSG_TYPE_EXCEPTION )
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print ( " Finished executing the workflow " )
return
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self . _generate ( full_prompt , n_predict , client_id , callback )
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ASCIIColors . success ( " \n Finished executing the generation " )
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def _generate ( self , prompt , n_predict , client_id , callback = None ) :
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self . nb_received_tokens = 0
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if self . model is not None :
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ASCIIColors . info ( f " warmup for generating { n_predict } tokens " )
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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 = min ( n_predict , self . personality . model_n_predicts ) ,
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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 ,
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seed = self . config [ ' seed ' ] ,
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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 ) :
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ASCIIColors . info ( f " Text generation requested by client: { client_id } " )
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# send the message to the bot
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print ( f " Received message : { message . content } " )
if self . connections [ client_id ] [ " current_discussion " ] :
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if not self . model :
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self . notify ( " No model selected. Please make sure you select a model before starting generation " , False , client_id )
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return
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# First we need to send the new message ID to the client
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if is_continue :
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self . connections [ client_id ] [ " current_discussion " ] . load_message ( message_id )
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self . connections [ client_id ] [ " generated_text " ] = message . content
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else :
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self . new_message ( client_id , self . personality . name , " ✍ please stand by ... " )
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self . socketio . sleep ( 0.01 )
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# prepare query and reception
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self . discussion_messages , self . current_message , tokens = self . prepare_query ( client_id , message_id , is_continue )
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self . prepare_reception ( client_id )
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self . generating = True
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self . connections [ client_id ] [ " processing " ] = True
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self . generate (
self . discussion_messages ,
self . current_message ,
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n_predict = self . config . ctx_size - len ( tokens ) - 1 ,
client_id = client_id ,
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callback = partial ( self . process_chunk , client_id = client_id )
)
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print ( )
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print ( " ## Done Generation ## " )
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print ( )
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self . cancel_gen = False
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# Send final message
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self . close_message ( client_id )
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self . socketio . sleep ( 0.01 )
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self . connections [ client_id ] [ " processing " ] = False
if self . connections [ client_id ] [ " schedule_for_deletion " ] :
del self . connections [ client_id ]
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ASCIIColors . success ( f " ╔══════════════════════════════════════════════════╗ " )
ASCIIColors . success ( f " ║ Done ║ " )
ASCIIColors . success ( f " ╚══════════════════════════════════════════════════╝ " )
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self . busy = False
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else :
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ump = self . config . discussion_prompt_separator + self . config . user_name + " : " if self . config . use_user_name_in_discussions else self . personality . user_message_prefix
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self . cancel_gen = False
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#No discussion available
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ASCIIColors . warning ( " No discussion selected!!! " )
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self . notify ( " No discussion selected!!! " , False , client_id )
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print ( )
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self . busy = False
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return " "