import gradio as gr import random import torch from transformers import AutoConfig from transformers import GPT2Tokenizer, GPT2LMHeadModel from itertools import chain import tempfile from typing import Optional from TTS.config import load_config import gradio as gr import numpy as np from TTS.utils.manage import ModelManager from TTS.utils.synthesizer import Synthesizer config = AutoConfig.from_pretrained('gorkemgoknar/gpt2chatbotenglish') model = GPT2LMHeadModel.from_pretrained('gorkemgoknar/gpt2chatbotenglish', config=config) tokenizer = GPT2Tokenizer.from_pretrained('gorkemgoknar/gpt2chatbotenglish') tokenizer.model_max_length = 1024 #Dynamic Temperature #See experiment https://www.linkedin.com/pulse/ai-goes-job-interview-g%25C3%25B6rkem-g%25C3%25B6knar base_temperature = 1.3 dynamic_temperature_range = 0.15 rand_range = random.uniform(-1 * dynamic_temperature_range , dynamic_temperature_range ) temperature = base_temperature + rand_range SPECIAL_TOKENS = ["", "", "", "", ""] #See document for experiment https://www.linkedin.com/pulse/ai-goes-job-interview-g%C3%B6rkem-g%C3%B6knar/ def get_chat_response(name,history=[], input_txt = "Hello , what is your name?"): ai_history = history.copy() #ai_history.append(input_txt) ai_history_e = [tokenizer.encode(e) for e in ai_history] personality = "My name is " + name bos, eos, speaker1, speaker2 = tokenizer.convert_tokens_to_ids(SPECIAL_TOKENS[:-1]) #persona first, history next, input text must be at the end #[[bos, persona] , [history] , [input]] sequence = [[bos] + tokenizer.encode(personality)] + ai_history_e + [tokenizer.encode(input_txt)] ##[[bos, persona] , [speaker1 .., speakser2 .., speaker1 ... speaker2 ... , [input]] sequence = [sequence[0]] + [[speaker2 if (len(sequence)-i) % 2 else speaker1] + s for i, s in enumerate(sequence[1:])] sequence = list(chain(*sequence)) #bot_input_ids = tokenizer.encode(personality + tokenizer.eos_token + input_txt + tokenizer.eos_token , return_tensors='pt') sequence_len = len(sequence) #optimum response and speed chat_history_ids = model.generate( torch.tensor(sequence).unsqueeze(0), max_length=50, pad_token_id=tokenizer.eos_token_id, no_repeat_ngram_size=3, do_sample=True, top_k=60, top_p=0.8, temperature = 1.3 ) out_str = tokenizer.decode(chat_history_ids[0][sequence_len:], skip_special_tokens=True) #out_str = tokenizer.decode(chat_history_ids[:, sequence.shape[-1]:][0], skip_special_tokens=False) return out_str ##you can use anyone from below ''' | Macleod | Moran | Brenda | Ramirez | Peter Parker | Quentin Beck | Andy | Red | Norton | Willard | Chief | Chef | Kilgore | Kurtz | Westley | Buttercup | Vizzini | Fezzik | Inigo | Man In Black | Taylor | Zira | Zaius | Cornelius | Bud | Lindsey | Hippy | Erin | Ed | George | Donna | Trinity | Agent Smith | Morpheus | Neo | Tank | Meryl | Truman | Marlon | Christof | Stromboli | Bumstead | Schreber | Walker | Korben | Cornelius | Loc Rhod | Anakin | Obi-Wan | Palpatine | Padme | Superman | Luthor | Dude | Walter | Donny | Maude | General | Starkiller | Indiana | Willie | Short Round | John | Sarah | Terminator | Miller | Sarge | Reiben | Jackson | Upham | Chuckie | Will | Lambeau | Sean | Skylar | Saavik | Spock | Kirk | Bones | Khan | Kirk | Spock | Sybok | Scotty | Bourne | Pamela | Abbott | Nicky | Marshall | Korshunov | Troy | Vig | Archie Gates | Doc | Interrogator | Ellie | Ted | Peter | Drumlin | Joss | Macready | Childs | Nicholas | Conrad | Feingold | Christine | Adam | Barbara | Delia | Lydia | Cathy | Charles | Otho | Schaefer | Han | Luke | Leia | Threepio | Vader | Yoda | Lando | Elaine | Striker | Dr. Rumack | Kramer | David | Saavik | Kirk | Kruge | Holden | Deckard | Rachael | Batty | Sebastian | Sam | Frodo | Pippin | Gandalf | Kay | Edwards | Laurel | Edgar | Zed | Jay | Malloy | Plissken | Steve Rogers | Tony Stark | Scott Lang | Bruce Banner | Bruce | Edward | Two-Face | Batman | Chase | Alfred | Dick | Riddler | Din Djarin | Greef Karga | Kuiil | Ig-11 | Cara Dune | Peli Motto | Toro Calican | Ripley | Meredith | Dickie | Marge | Peter | Lambert | Kane | Dallas | Ripley | Ash | Parker | Threepio | Luke | Leia | Ben | Han | Common Bob | Common Alice | Jack | Tyler | Marla | Dana | Stantz | Venkman | Spengler | Louis | Fry | Johns | Riddick | Kirk | Decker | Spock | "Ilia | Indy | Belloq | Marion | Brother | Allnut | Rose | Qui-Gon | Jar Jar ''' MODEL_NAME= "tts_models/multilingual/multi-dataset/your_tts" def tts(text: str, speaker_idx: str=None): if len(text) > MAX_TXT_LEN: text = text[:MAX_TXT_LEN] print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.") print(text, model_name) # download model model_path, config_path, model_item = manager.download_model(f"tts_models/{MODEL_NAME}") vocoder_name: Optional[str] = model_item["default_vocoder"] # download vocoder vocoder_path = None vocoder_config_path = None if vocoder_name is not None: vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name) # init synthesizer synthesizer = Synthesizer( model_path, config_path, None, None, vocoder_path, vocoder_config_path, ) # synthesize if synthesizer is None: raise NameError("model not found") wavs = synthesizer.tts(text, speaker_idx) # return output with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: synthesizer.save_wav(wavs, fp) return fp.name def greet(character,message,history,voice): #gradios set_state/get_state had problems on embedded html! history = history or {"character": character, "message_history" : [] } #gradios set_state/get_state does not persist session for now using global #global history if history["character"] != character: #switching character history = {"character": character, "message_history" : [] } response = get_chat_response(character,history=history["message_history"],input_txt=message) voice = tts(response) history["message_history"].append((message, response)) html = "
" for user_msg, resp_msg in history["message_history"]: html += f"
You: {user_msg}
" html += f"
{character}: {resp_msg}
" html += "
" return html,history,voice personality_choices = ["Gandalf", "Riddick", "Macleod", "Morpheus", "Neo","Spock","Vader","Indy"] examples= ["Gandalf", "What is your name?"] css=""" .chatbox {display:flex;flex-direction:column} .user_msg, .resp_msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%} .user_msg {background-color:cornflowerblue;color:white;align-self:start} .resp_msg {background-color:lightgray;align-self:self-end} """ #some selected ones are in for demo use personality_choices = ["Gandalf", "Riddick", "Macleod", "Morpheus", "Neo","Spock","Vader","Indy", "Ig-11","Threepio","Tony Stark","Batman","Vizzini"] title = "Metayazar - Movie Chatbot" description = "Chat with your favorite movie characters. This space demo has simple interface and simple history as gradio's state did not work need to make a global history, you will have different responses as same gradio machine will be used! Test it out in metayazar.com/chatbot for more movie/character options and history memorized." article = "

AI Goes to Job Interview | Metayazar AI Writer |Görkem Göknar

" #History not implemented in this demo, use metayazar.com/chatbot for a movie and character dropdown chat interface ##interface = gr.Interface(fn=greet, inputs=[gr.inputs.Dropdown(personality_choices) ,"text"], title=title, description=description, outputs="text") history = {"character": "None", "message_history" : [] } interface= gr.Interface(fn=greet, inputs=[gr.inputs.Dropdown(personality_choices) ,"text", "state"], outputs=["html","state", gr.outputs.Audio(label="voice"),], css=css, title=title, description=description,article=article ) if __name__ == "__main__": interface.launch()