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main.py
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import os
os.environ["COQUI_TOS_AGREED"] = "1"
import re
import subprocess
import torch
import yaml
import numpy as np
import time
import warnings
warnings.filterwarnings("ignore", category=UserWarning)
warnings.filterwarnings("ignore", category=FutureWarning)
from playwright.sync_api import sync_playwright
from socket import AF_INET, socket, SOCK_STREAM
from threading import Thread
from scripts.login_screen import CONFIG
from scripts.utils import HiddenPrints
# Configuration variables
GAME_PATH = CONFIG["GAME_PATH"]
WEBUI_PATH = CONFIG["WEBUI_PATH"]
ST_PATH = CONFIG.get("ST_PATH", "") # Add SillyTavern path
BACKEND_TYPE = CONFIG.get("BACKEND_TYPE", "Text-gen-webui") # Default to text-gen-webui for compatibility
USE_TTS = CONFIG["USE_TTS"]
LAUNCH_YOURSELF = CONFIG["LAUNCH_YOURSELF"]
LAUNCH_YOURSELF_WEBUI = CONFIG["LAUNCH_YOURSELF_WEBUI"]
LAUNCH_YOURSELF_ST = CONFIG.get("LAUNCH_YOURSELF_ST", False) # Add SillyTavern launch flag
USE_ACTIONS = CONFIG["USE_ACTIONS"]
TTS_MODEL = CONFIG["TTS_MODEL"]
USE_SPEECH_RECOGNITION = CONFIG["USE_SPEECH_RECOGNITION"]
VOICE_SAMPLE_COQUI = CONFIG["VOICE_SAMPLE_COQUI"]
VOICE_SAMPLE_TORTOISE = CONFIG["VOICE_SAMPLE_TORTOISE"]
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# Actions model
if USE_ACTIONS:
try:
from transformers import pipeline
except ModuleNotFoundError:
print("Please install transformers to use actions.")
USE_ACTIONS = False
with open("actions.yml", "r") as f:
ACTIONS = yaml.safe_load(f)
REVERT_ACTION_DICT = {}
for key in ACTIONS:
for action in ACTIONS[key]:
REVERT_ACTION_DICT[action] = key
ALL_ACTIONS = []
for key in ACTIONS:
ALL_ACTIONS += ACTIONS[key]
action_classifier = pipeline(
"zero-shot-classification",
model="sileod/deberta-v3-base-tasksource-nli")
# TTS model
with HiddenPrints():
if USE_TTS:
from scripts.play_tts import play_TTS, initialize_xtts
if TTS_MODEL == "Your TTS":
from scripts.tts_api import my_TTS
tts_model = my_TTS(model_name="tts_models/multilingual/multi-dataset/your_tts")
sampling_rate = 16000
voice_samples = None
conditioning_latents = None
elif TTS_MODEL == "XTTS":
tts_model = initialize_xtts()
sampling_rate = 24000
voice_samples = None
conditioning_latents = None
elif TTS_MODEL == "Tortoise TTS":
if device.type == "cuda":
from tortoise.api_fast import TextToSpeech, MODELS_DIR
else:
from tortoise.api import TextToSpeech, MODELS_DIR
from tortoise.utils.audio import load_voices
from voicefixer import VoiceFixer
tts_model = TextToSpeech(
models_dir=MODELS_DIR,
kv_cache=True,
)
voice_samples, conditioning_latents = load_voices([VOICE_SAMPLE_TORTOISE], ["tortoise_audios"])
vfixer = VoiceFixer()
sampling_rate = 24000
else:
print("No TTS model selected")
# Speech recognition model
if USE_SPEECH_RECOGNITION:
try:
import torch
except ModuleNotFoundError:
print("Please install torch to use speech recognition.")
USE_SPEECH_RECOGNITION = False
try:
import speech_recognition as sr
except ModuleNotFoundError:
print("Please install SpeechRecognition to use speech recognition.")
USE_SPEECH_RECOGNITION = False
try:
import whisper
except ModuleNotFoundError:
print("Please install whisper to use speech recognition.")
USE_SPEECH_RECOGNITION = False
try:
import pyaudio
except ModuleNotFoundError:
print("Please install pyaudio to use speech recognition.")
USE_SPEECH_RECOGNITION = False
english = True
def init_stt(model="base", english=True, energy=300, pause=0.8, dynamic_energy=False):
if model != "large" and english:
model = model + ".en"
audio_model = whisper.load_model(model)
r = sr.Recognizer()
r.energy_threshold = energy
r.pause_threshold = pause
r.dynamic_energy_threshold = dynamic_energy
return r, audio_model
r, audio_model = init_stt()
# Chatbot connection
def launch_backend():
global WEBUI_PATH
global ST_PATH
if BACKEND_TYPE == "Text-gen-webui":
WEBUI_PATH = WEBUI_PATH.replace("\\", "/")
if not LAUNCH_YOURSELF_WEBUI:
subprocess.Popen(WEBUI_PATH)
else:
print("Please launch text-generation_webui manually.")
print("Press enter to continue.")
input()
else: # SillyTavern
st_path_normalized = ST_PATH.replace("\\", "/")
if not LAUNCH_YOURSELF_ST:
subprocess.Popen(st_path_normalized)
else:
print("Please launch SillyTavern manually.")
print("Press enter to continue.")
input()
launch_backend()
def launch(context):
print("Launching new browser page...")
page = context.new_page()
if BACKEND_TYPE == "Text-gen-webui":
page.goto("http://127.0.0.1:7860")
page.wait_for_selector("[class='svelte-1f354aw pretty_scrollbar']", timeout=60000)
time.sleep(1)
else: # SillyTavern
page.goto("http://127.0.0.1:8000")
page.wait_for_load_state("networkidle")
print("Page loaded successfully")
context.storage_state(path="storage.json")
return page
def post_message(page, message):
if BACKEND_TYPE == "Text-gen-webui":
if message == "QUIT":
page.fill("[class='svelte-1f354aw pretty_scrollbar']", "I'll be right back")
else:
page.fill("[class='svelte-1f354aw pretty_scrollbar']", message)
time.sleep(0.2)
page.click('[id="Generate"]')
page.wait_for_selector('[id="stop"]')
else: # SillyTavern
if message == "QUIT":
page.fill("#send_textarea", "I'll be right back")
else:
page.fill("#send_textarea", message)
page.press("#send_textarea", "Enter")
page.wait_for_selector(".mes_stop", state="visible")
time.sleep(1) #small delay to be SURE the script won't see the generate button before it has had time to change state
def check_generation_complete(page):
if BACKEND_TYPE == "Text-gen-webui":
stop_buttons = page.locator('[id="stop"]').all()
return not any(button.is_visible() for button in stop_buttons)
else: # SillyTavern
stop_button = page.locator(".mes_stop")
return not stop_button.is_visible()
def get_last_message(page):
if BACKEND_TYPE == "Text-gen-webui":
user = page.locator('[class="message-body"]').locator("nth=-1")
return user.inner_html()
else: # SillyTavern
paragraphs = page.locator(".mes.last_mes .mes_text p").all()
# Combine all paragraphs with /n between them. This avoids the code getting confused by multi-paragraphs answers... something I didn't encounter in my tests.
return "\n".join(p.inner_text() for p in paragraphs)
# Main
GAME_PATH = GAME_PATH.replace("\\", "/")
clients = {}
addresses = {}
HOST = '127.0.0.1'
PORT = 12346
BUFSIZE = 1024
ADDRESS = (HOST, PORT)
SERVER = socket(AF_INET, SOCK_STREAM)
SERVER.bind(ADDRESS)
queued = False
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
uni_chr_re = re.compile(r'\\u[0-9a-fA-F]{4}')
# Launch the game
if not LAUNCH_YOURSELF:
subprocess.Popen(GAME_PATH+'/DDLC.exe')
def listen():
print("Waiting for connection...")
while True:
client, client_address = SERVER.accept()
print("%s:%s has connected." % client_address)
addresses[client] = client_address
Thread(target=call, args=(client,)).start()
def call(client):
thread = Thread(target=listenToClient, args=(client,), daemon=True)
thread.start()
def sendMessage(msg, name=""):
""" send message to all users present in
the chat room"""
for client in clients:
client.send(bytes(name, "utf8") + msg)
def send_answer(received_msg, msg):
if received_msg != "" and USE_ACTIONS:
sequence_to_classify = f"The player is speaking with Monika, his virtual \
girlfriend. Now he says: {received_msg}. What is the label of this sentence?"
action_to_take = action_classifier(sequence_to_classify, ALL_ACTIONS)
action_to_take = action_to_take["labels"][0]
print("Action: " + action_to_take)
action_to_take = REVERT_ACTION_DICT[action_to_take]
else:
action_to_take = "none"
action_to_take = action_to_take.encode("utf-8")
emotion = "".encode("utf-8")
msg = msg.encode("utf-8")
msg_to_send = msg + b"/g" + emotion + b"/g" + action_to_take
sendMessage(msg_to_send)
def listenToClient(client):
""" Get client username """
name = "User"
clients[client] = name
launched = False
play_obj = None
while True:
try:
received_msg = client.recv(BUFSIZE).decode("utf-8")
except:
print("Connection lost.")
os._exit(0)
received_msg = received_msg.split("/m")
rest_msg = received_msg[1]
received_msg = received_msg[0]
if received_msg == "chatbot":
if '/g' in rest_msg:
received_msg, step = rest_msg.split("/g")
else:
received_msg = client.recv(BUFSIZE).decode("utf-8")
received_msg, step = received_msg.split("/g")
step = int(step)
if received_msg == "begin_record":
if USE_SPEECH_RECOGNITION:
with sr.Microphone(sample_rate=16000) as source:
sendMessage("yes".encode("utf-8"))
audio = r.listen(source)
torch_audio = torch.from_numpy(
np.frombuffer(
audio.get_raw_data(),
np.int16
).flatten().astype(np.float32) / 32768.0)
audio_data = torch_audio
if english:
result = audio_model.transcribe(audio_data, language='english')
else:
result = audio_model.transcribe(audio_data)
received_msg = result['text']
else:
sendMessage("no".encode("utf-8"))
continue
print("User: "+received_msg)
if not launched:
pw = sync_playwright().start()
try:
browser = pw.firefox.launch(headless=False)
context = browser.new_context()
page = launch(context)
except:
print(f"Launch failed. Please check if {BACKEND_TYPE} is running.")
_ = client.recv(BUFSIZE).decode("utf-8")
sendMessage("server_error".encode("utf-8"))
launched = False
pw.stop()
continue
launched = True
_ = client.recv(BUFSIZE).decode("utf-8")
sendMessage("server_ok".encode("utf-8"))
try:
post_message(page, received_msg)
except Exception as e:
print(f"Error while sending message. Please check if {BACKEND_TYPE} is running: {str(e)}")
_ = client.recv(BUFSIZE).decode("utf-8")
sendMessage("server_error".encode("utf-8"))
launched = False
pw.stop()
continue
while True:
try:
if check_generation_complete(page):
text = get_last_message(page)
if len(text) > 0:
msg = text
msg = re.sub(r'<[^>]+>', '', msg)
msg = msg.replace('\n', '')
msg = os.linesep.join([s for s in msg.splitlines() if s])
msg = re.sub(' +', ' ', msg)
msg = re.sub(r'&[^;]+;', '', msg)
msg = msg.replace("END", "")
else:
continue
if received_msg != "QUIT":
if USE_TTS:
print("Using TTS")
play_obj = play_TTS(
step,
msg,
play_obj,
sampling_rate,
tts_model,
voice_samples,
conditioning_latents,
TTS_MODEL,
VOICE_SAMPLE_COQUI,
uni_chr_re)
print("Sent: " + msg)
send_answer(received_msg, msg)
break
except Exception as e:
print("Error checking generation status:", e)
launched = False
pw.stop()
break
if __name__ == "__main__":
SERVER.listen(5)
ACCEPT_THREAD = Thread(target=listen)
ACCEPT_THREAD.start()
ACCEPT_THREAD.join()
SERVER.close()