Duplicate from gorkemgoknar/movie_chat_gpt_yourtts_fileinput

Co-authored-by: Gorkem Goknar <gorkemgoknar@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+title: Moviechatbot - GPT chatbot with Coqui YourTTS - File Input
+emoji: 👀
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+app_file: app.py
+pinned: false
+duplicated_from: gorkemgoknar/movie_chat_gpt_yourtts_fileinput
+---
+
+# Configuration
+
+`title`: _string_  
+Poc with no model first
+
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.

app.py

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+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 + '</s>', 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 = ["<bos>", "<eos>", "<speaker1>", "<speaker2>", "<pad>"]
+
+#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"') 
+  filename = "tts_output.wav"
+  history["message_history"].append((message, response))
+
+  #emotion = get_emotion(response)
+  
+  html = "<div class='chatbot'>"
+  for user_msg, resp_msg in history["message_history"]:
+      html += f"<div class='user_msg'>You: {user_msg}</div>"
+      html += f"<div class='resp_msg'>{character}: {resp_msg}</div>"
+  html += "</div>"
+
+  return html,history,filename
+  
+
+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 = "<div class='chatbot'>"
+  for user_msg, resp_msg in history["message_history"]:
+      html += f"<div class='user_msg'>You: {user_msg}</div>"
+      html += f"<div class='resp_msg'>{character}: {resp_msg}</div>"
+  html += "</div>"
+
+  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 = "<p style='text-align: center'><a href='https://www.linkedin.com/pulse/ai-goes-job-interview-g%C3%B6rkem-g%C3%B6knar/' target='_blank'>AI Goes to Job Interview</a> | <a href='https://www.metayazar.com/' target='_blank'>Metayazar AI Writer</a>  |<a href='https://www.linkedin.com/in/goknar/' target='_blank'>Görkem Göknar</a></p>"
+
+#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="file")],      
+                        css=css, title=title, description=description,article=article )
+
+
+if __name__ == "__main__":
+    interface_file.launch()

requirements.txt

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+torch
+transformers 
+gradio==3.12.0
+tts
+numpy