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