###### # Project : GPT4ALL-UI # 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 gpt4all-ui and its models. ###### from datetime import datetime from api.db import DiscussionsDB from pathlib import Path import importlib from pyaipersonality import AIPersonality import multiprocessing as mp import threading import time import requests from tqdm import tqdm import traceback __author__ = "parisneo" __github__ = "https://github.com/ParisNeo/gpt4all-ui" __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 ModelProcess: def __init__(self, config=None): self.config = config self.generate_queue = mp.Queue() self.generation_queue = mp.Queue() self.cancel_queue = mp.Queue(maxsize=1) self.clear_queue_queue = mp.Queue(maxsize=1) self.set_config_queue = mp.Queue(maxsize=1) self.set_config_result_queue = mp.Queue(maxsize=1) self.process = None # Create synchronization objects self.start_signal = mp.Event() self.completion_signal = mp.Event() self.model_ready = mp.Value('i', 0) self.curent_text = "" self.ready = False self.id=0 self.n_predict=2048 self.reset_config_result() def reset_config_result(self): self._set_config_result = { 'status': 'succeeded', 'binding_status':'ok', 'model_status':'ok', 'personality_status':'ok', 'errors':[] } 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 load_binding(self, binding_name:str, install=False): if install: print(f"Loading binding {binding_name} install ON") else: print(f"Loading binding : {binding_name} install is off") binding_path = Path("bindings")/binding_name if install: # first find out if there is a requirements.txt file install_file_name="install.py" install_script_path = binding_path / install_file_name if install_script_path.exists(): module_name = install_file_name[:-3] # Remove the ".py" extension module_spec = importlib.util.spec_from_file_location(module_name, str(install_script_path)) module = importlib.util.module_from_spec(module_spec) module_spec.loader.exec_module(module) if hasattr(module, "Install"): module.Install(self) # define the full absolute path to the module absolute_path = binding_path.resolve() # infer the module name from the file path module_name = binding_path.stem # use importlib to load the module from the file path loader = importlib.machinery.SourceFileLoader(module_name, str(absolute_path/"__init__.py")) binding_module = loader.load_module() binding_class = getattr(binding_module, binding_module.binding_name) return binding_class def start(self): if self.process is None: self.process = mp.Process(target=self._run) self.process.start() def stop(self): if self.process is not None: self.generate_queue.put(None) self.process.join() self.process = None def set_binding(self, binding_path): self.binding = binding_path def set_model(self, model_path): self.model = model_path def set_config(self, config): try: self.set_config_result_queue.get_nowait() except: pass self.set_config_queue.put(config) # Wait for it t o be consumed while self.set_config_result_queue.empty(): time.sleep(0.1) return self.set_config_result_queue.get() def generate(self, full_prompt, prompt, id, n_predict): self.start_signal.clear() self.generate_queue.put((full_prompt, prompt, id, n_predict)) def cancel_generation(self): self.completion_signal.set() self.cancel_queue.put(('cancel',)) print("Canel request received") def clear_queue(self): self.clear_queue_queue.put(('clear_queue',)) def rebuild_binding(self, config): try: print(" ******************* Building Binding from main Process *************************") binding = self.load_binding(config["binding"], install=True) print("Binding loaded successfully") except Exception as ex: print("Couldn't build binding.") print(ex) binding = None return binding def _rebuild_model(self): try: self.reset_config_result() print(" ******************* Building Binding from generation Process *************************") self.binding = self.load_binding(self.config["binding"], install=True) print("Binding loaded successfully") try: model_file = Path("models")/self.config["binding"]/self.config["model"] print(f"Loading model : {model_file}") self.model = self.binding(self.config) self.model_ready.value = 1 print("Model created successfully\n") except Exception as ex: if self.config["model"] is None: print("No model is selected.\nPlease select a backend and a model to start using the ui.") else: print(f"Couldn't build model {self.config['model']} : {ex}") self.model = None self._set_config_result['status'] ='failed' self._set_config_result['binding_status'] ='failed' self._set_config_result['errors'].append(f"couldn't build binding:{ex}") except Exception as ex: traceback.print_exc() print("Couldn't build binding") print(ex) self.binding = None self.model = None self._set_config_result['status'] ='failed' self._set_config_result['binding_status'] ='failed' self._set_config_result['errors'].append(f"couldn't build binding:{ex}") def rebuild_personality(self): try: print(f" ******************* Building Personality {self.config['personality']} from main Process *************************") personality_path = f"personalities/{self.config['personality_language']}/{self.config['personality_category']}/{self.config['personality']}" personality = AIPersonality(personality_path, run_scripts=False) print(f" ************ Personality {personality.name} is ready (Main process) ***************************") except Exception as ex: print(f"Personality file not found or is corrupted ({personality_path}).\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.") if self.config["debug"]: print(ex) personality = AIPersonality() return personality def _rebuild_personality(self): try: self.reset_config_result() print(f" ******************* Building Personality {self.config['personality']} from generation Process *************************") personality_path = f"personalities/{self.config['personality_language']}/{self.config['personality_category']}/{self.config['personality']}" self.personality = AIPersonality(personality_path) print(f" ************ Personality {self.personality.name} is ready (generation process) ***************************") except Exception as ex: print(f"Personality file not found or is corrupted ({personality_path}).") print(f"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.") print(f"Exception: {ex}") if self.config["debug"]: print(ex) self.personality = AIPersonality() self._set_config_result['status'] ='failed' self._set_config_result['binding_status'] ='failed' self._set_config_result['errors'].append(f"couldn't build binding:{ex}") def _run(self): self._rebuild_model() self._rebuild_personality() self.check_set_config_thread = threading.Thread(target=self._check_set_config_queue, args=()) print("Launching config verification thread") self.check_set_config_thread.start() self.check_cancel_thread = threading.Thread(target=self._check_cancel_queue, args=()) print("Launching cancel verification thread") self.check_cancel_thread.start() self._check_clear_thread = threading.Thread(target=self._check_clear_queue, args=()) print("Launching clear verification thread") self._check_clear_thread.start() if self.model_ready.value == 1: self.n_predict = 1 self._generate("I",1) print() print("Ready to receive data") else: print("No model loaded. Waiting for new configuration instructions") self.ready = True print(f"Listening on :http://{self.config['host']}:{self.config['port']}") while True: try: if not self.generate_queue.empty(): command = self.generate_queue.get() if command is not None: if self.cancel_queue.empty() and self.clear_queue_queue.empty(): self.id=command[2] self.n_predict=command[3] if self.personality.processor is not None: if self.personality.processor_cfg is not None: if "custom_workflow" in self.personality.processor_cfg: if self.personality.processor_cfg["custom_workflow"]: print("Running workflow") self.completion_signal.clear() self.start_signal.set() output = self.personality.processor.run_workflow(self._generate, command[1], command[0], self._callback) self._callback(output, 0) self.completion_signal.set() print("Finished executing the workflow") continue self.start_signal.set() self.completion_signal.clear() self._generate(command[0], self.n_predict, self._callback) self.completion_signal.set() print("Finished executing the generation") except Exception as ex: print(ex) time.sleep(1) def _generate(self, prompt, n_predict=50, callback=None): self.curent_text = "" if self.model is not None: print("Generating message...") self.id = self.id if self.config["override_personality_model_parameters"]: output = self.model.generate( prompt, new_text_callback=callback, n_predict=n_predict, temp=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, new_text_callback=callback, n_predict=self.n_predict, temp=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 _callback(self, text, text_type=0): print(text,end="", flush=True) self.curent_text += text detected_anti_prompt = False anti_prompt_to_remove="" for prompt in self.personality.anti_prompts: if prompt.lower() in text.lower(): detected_anti_prompt=True anti_prompt_to_remove = prompt.lower() if not detected_anti_prompt: if not self.ready: print(".",end="", flush=True) return True else: # Stream the generated text to the main process self.generation_queue.put((text,self.id, text_type)) # if stop generation is detected then stop if self.completion_signal.is_set(): return True else: return False else: self.curent_text = self.remove_text_from_string(self.curent_text, anti_prompt_to_remove) print("The model is halucinating") return False def _check_cancel_queue(self): while True: command = self.cancel_queue.get() if command is not None: self._cancel_generation() print("Stop generation received") def _check_clear_queue(self): while True: command = self.clear_queue_queue.get() if command is not None: self._clear_queue() print("Clear received") def _check_set_config_queue(self): while True: config = self.set_config_queue.get() if config is not None: print("Inference process : Setting configuration") self.reset_config_result() self._set_config(config) self.set_config_result_queue.put(self._set_config_result) def _cancel_generation(self): self.completion_signal.set() def _clear_queue(self): while not self.generate_queue.empty(): self.generate_queue.get() def _set_config(self, config): bk_cfg = self.config self.config = config print("Changing configuration") # verify that the binding is the same if self.config["binding"]!=bk_cfg["binding"] or self.config["model"]!=bk_cfg["model"]: self._rebuild_model() # verify that the personality is the same if self.config["personality"]!=bk_cfg["personality"] or self.config["personality_category"]!=bk_cfg["personality_category"] or self.config["personality_language"]!=bk_cfg["personality_language"]: self._rebuild_personality() class GPT4AllAPI(): def __init__(self, config:dict, socketio, config_file_path:str) -> None: self.socketio = socketio #Create and launch the process self.process = ModelProcess(config) self.config = config self.binding = self.process.rebuild_binding(self.config) self.personality = self.process.rebuild_personality() if config["debug"]: print(print(f"{self.personality}")) self.config_file_path = config_file_path self.cancel_gen = False # Keeping track of current discussion and message self.current_discussion = None self._current_user_message_id = 0 self._current_ai_message_id = 0 self._message_id = 0 self.db_path = config["db_path"] # Create database object self.db = DiscussionsDB(self.db_path) # If the database is empty, populate it with tables self.db.populate() # This is used to keep track of messages self.full_message_list = [] # ========================================================================================= # Socket IO stuff # ========================================================================================= @socketio.on('connect') def connect(): print('Client connected') @socketio.on('disconnect') def disconnect(): print('Client disconnected') @socketio.on('install_model') def install_model(data): def install_model_(): print("Install model triggered") model_path = data["path"] progress = 0 installation_dir = Path(f'./models/{self.config["binding"]}/') filename = Path(model_path).name installation_path = installation_dir / filename print("Model install requested") print(f"Model path : {model_path}") if installation_path.exists(): print("Error: Model already exists") socketio.emit('install_progress',{'status': 'failed', 'error': 'model already exists'}) socketio.emit('install_progress',{'status': 'progress', 'progress': progress}) def callback(progress): socketio.emit('install_progress',{'status': 'progress', 'progress': progress}) self.download_file(model_path, installation_path, callback) socketio.emit('install_progress',{'status': 'succeeded', 'error': ''}) tpe = threading.Thread(target=install_model_, args=()) tpe.start() @socketio.on('uninstall_model') def uninstall_model(data): model_path = data['path'] installation_dir = Path(f'./models/{self.config["binding"]}/') filename = Path(model_path).name installation_path = installation_dir / filename if not installation_path.exists(): socketio.emit('install_progress',{'status': 'failed', 'error': 'The model does not exist'}) installation_path.unlink() socketio.emit('install_progress',{'status': 'succeeded', 'error': ''}) @socketio.on('generate_msg') def generate_msg(data): if self.process.model_ready.value==1: if self.current_discussion is None: if self.db.does_last_discussion_have_messages(): self.current_discussion = self.db.create_discussion() else: self.current_discussion = self.db.load_last_discussion() message = data["prompt"] message_id = self.current_discussion.add_message( "user", message, parent=self.message_id ) self.current_user_message_id = message_id tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id)) tpe.start() else: self.socketio.emit('infos', { "status":'model_not_ready', "type": "input_message_infos", 'logo': "", "bot": self.personality.name, "user": self.personality.user_name, "message":"", "user_message_id": self.current_user_message_id, "ai_message_id": self.current_ai_message_id, } ) @socketio.on('generate_msg_from') def handle_connection(data): message_id = int(data['id']) message = data["prompt"] self.current_user_message_id = message_id tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id)) tpe.start() # generation status self.generating=False self.process.start() #properties @property def message_id(self): return self._message_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: percentage = (downloaded_size / total_size) * 100 callback(percentage) progress_bar.update(len(chunk)) if callback is not None: callback(100.0) print("File downloaded successfully") except Exception as e: print("Couldn't download file:", str(e)) def condition_chatbot(self): if self.current_discussion is None: self.current_discussion = self.db.load_last_discussion() if self.personality.welcome_message!="": message_id = self.current_discussion.add_message( self.personality.name, self.personality.welcome_message, DiscussionsDB.MSG_TYPE_NORMAL, 0, -1 ) self.current_ai_message_id = message_id else: message_id = 0 return message_id def prepare_reception(self): self.bot_says = "" self.full_text = "" self.is_bot_text_started = False def create_new_discussion(self, title): self.current_discussion = self.db.create_discussion(title) # Get the current timestamp timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") # Chatbot conditionning self.condition_chatbot() return timestamp def prepare_query(self, message_id=-1): messages = self.current_discussion.get_messages() self.full_message_list = [] for message in messages: if message["id"]< message_id or message_id==-1: if message["type"]==self.db.MSG_TYPE_NORMAL: if message["sender"]==self.personality.name: self.full_message_list.append(self.personality.ai_message_prefix+message["content"]) else: self.full_message_list.append(self.personality.user_message_prefix + message["content"]) else: break if self.personality.processor is not None: preprocessed_prompt = self.personality.processor.process_model_input(message["content"]) else: preprocessed_prompt = message["content"] if preprocessed_prompt is not None: self.full_message_list.append(self.personality.user_message_prefix+preprocessed_prompt+self.personality.link_text+self.personality.ai_message_prefix) else: self.full_message_list.append(self.personality.user_message_prefix+message["content"]+self.personality.link_text+self.personality.ai_message_prefix) link_text = self.personality.link_text if len(self.full_message_list) > self.config["nb_messages_to_remember"]: discussion_messages = self.personality.personality_conditioning+ link_text.join(self.full_message_list[-self.config["nb_messages_to_remember"]:]) else: discussion_messages = self.personality.personality_conditioning+ link_text.join(self.full_message_list) return discussion_messages, message["content"] def get_discussion_to(self, message_id=-1): messages = self.current_discussion.get_messages() self.full_message_list = [] for message in messages: if message["id"]<= message_id or message_id==-1: if message["type"]!=self.db.MSG_TYPE_CONDITIONNING: if message["sender"]==self.personality.name: self.full_message_list.append(self.personality.ai_message_prefix+message["content"]) else: self.full_message_list.append(self.personality.user_message_prefix + message["content"]) link_text = self.personality.link_text if len(self.full_message_list) > self.config["nb_messages_to_remember"]: discussion_messages = self.personality.personality_conditioning+ link_text.join(self.full_message_list[-self.config["nb_messages_to_remember"]:]) else: discussion_messages = self.personality.personality_conditioning+ link_text.join(self.full_message_list) return discussion_messages # Removes the last return def process_chunk(self, chunk, message_type): if message_type == 0: self.bot_says += chunk if message_type < 2: self.socketio.emit('message', { 'data': self.bot_says, 'user_message_id':self.current_user_message_id, 'ai_message_id':self.current_ai_message_id, 'discussion_id':self.current_discussion.discussion_id, 'message_type': message_type } ) if self.cancel_gen: print("Generation canceled") self.process.cancel_generation() self.cancel_gen = False self.current_discussion.update_message(self.current_ai_message_id, self.bot_says) def start_message_generation(self, message, message_id): bot_says = "" # send the message to the bot print(f"Received message : {message}") if self.current_discussion: # First we need to send the new message ID to the client self.current_ai_message_id = self.current_discussion.add_message( self.personality.name, "", parent = self.current_user_message_id ) # first the content is empty, but we'll fill it at the end self.socketio.emit('infos', { "status":'generation_started', "type": "input_message_infos", "bot": self.personality.name, "user": self.personality.user_name, "message":message,#markdown.markdown(message), "user_message_id": self.current_user_message_id, "ai_message_id": self.current_ai_message_id, } ) # prepare query and reception self.discussion_messages, self.current_message = self.prepare_query(message_id) self.prepare_reception() self.generating = True self.process.generate(self.discussion_messages, self.current_message, message_id, n_predict = self.config['n_predict']) while(not self.process.completion_signal.is_set() or not self.process.generation_queue.empty()): # Simulating other commands being issued try: chunk, tok, message_type = self.process.generation_queue.get(False, 2) if chunk!="": self.process_chunk(chunk, message_type) except Exception as ex: time.sleep(0.1) print() print("## Done ##") print() # Send final message self.socketio.emit('final', { 'data': self.bot_says, 'ai_message_id':self.current_ai_message_id, 'parent':self.current_user_message_id, 'discussion_id':self.current_discussion.discussion_id } ) self.current_discussion.update_message(self.current_ai_message_id, self.bot_says) self.full_message_list.append(self.bot_says) self.cancel_gen = False return bot_says else: #No discussion available print("No discussion selected!!!") print("## Done ##") print() self.cancel_gen = False return ""