import gradio as gr import random import torch from transformers import AutoConfig, AutoTokenizer, AutoModelWithLMHead from transformers import GPT2Tokenizer, GPT2LMHeadModel from itertools import chain import os import tempfile from typing import Optional from TTS.config import load_config import numpy as np from TTS.utils.manage import ModelManager from TTS.utils.synthesizer import Synthesizer #emotion_tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-emotion") #emotion_model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-emotion") def get_emotion(text): input_ids = tokenizer.encode(text + '', return_tensors='pt') output = model.generate(input_ids=input_ids,max_length=2) dec = [tokenizer.decode(ids) for ids in output] label = dec[0] return label.split()[1] 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 = 1.2 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 greet(character,your_voice,message,history): #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) os.system('tts --text "'+response+'" --model_name tts_models/multilingual/multi-dataset/your_tts --speaker_wav '+your_voice+' --language_idx "en"') history["message_history"].append((message, response)) #emotion = get_emotion(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,"tts_output.wav" def greet_textonly(character,message,history): #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) history["message_history"].append((message, response)) #emotion = get_emotion(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 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 = "Movie Chatbot with Coqui YourTTS - File Input" description = "Chat with your favorite movie characters, making characters voice like you. Test it out in metayazar.com/chatbot for more movie/character options. See Coqui Space for more TTS models https://huggingface.co/spaces/coqui/CoquiTTS" 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") examples=[['Gandalf','dragon.wav','Who are you sir?',{}]] history = {"character": "None", "message_history" : [] } interface_file= gr.Interface(fn=greet, inputs=[gr.inputs.Dropdown(personality_choices), gr.inputs.Audio(type="filepath"), "text", "state"], outputs=["html","state",gr.outputs.Audio(type="filepath")], css=css, title=title, description=description,article=article ) if __name__ == "__main__": interface_file.launch()