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import queue
import random
import numpy as np
import os
import json
import uuid
from typing import Iterator
import asyncio
import platform
import time
#from .computer_utils import get_clipboard_content, copy_selected_content, input_text as utils_input_text
if platform.system() == 'Darwin':
from .computer_utils import control_computer as utils_control_computer
import re
class ConversationManager:
def __init__(self, config, llm, asr, tts, live2d, translator, audio_manager, interrupt_manager, claude_api_key = None, verbose=False, loop=None):
self.config = config
self.llm = llm
self.asr = asr
self.tts = tts
self.live2d = live2d
self.translator = translator
self.audio_manager = audio_manager
self.interrupt_manager = interrupt_manager
self.claude_api_key = claude_api_key
self.loop = loop
assert self.loop is not None, "loop is None"
self.verbose = verbose
self.heard_sentence = ""
# self.functions = self.get_tool_functions()
def get_prompt_and_image(self, user_input: str | np.ndarray | None = None, clipboard_data: dict | None = None) -> tuple[str, str | None]:
image_base64 = None
if clipboard_data:
if "text" in clipboard_data:
user_input += f"\nThe text from my clipboard (between two delimiter):###\n{clipboard_data['text']}###\n"
if "image" in clipboard_data:
image_base64 = clipboard_data["image"]
return user_input, image_base64
async def conversation_chain(self, user_input=None, clipboard_data=None):
"""
Đã sửa thành Async Generator để tương thích với WebSocket Handler.
"""
if not self.interrupt_manager.wait_continue_flag():
print(
">> Execution flag not set. In interruption state for too long. Exiting conversation chain."
)
raise InterruptedError(
"Conversation chain interrupted. Wait flag timeout reached."
)
color_code = random.randint(0, 3)
c = [None] * 4
c[0] = "\033[91m"
c[1] = "\033[94m"
c[2] = "\033[92m"
c[3] = "\033[0m"
print(f"{c[color_code]}New Conversation Chain started!")
if user_input is None:
user_input = self.get_user_input()
elif isinstance(user_input, np.ndarray):
print("transcribing...")
user_input = self.asr.transcribe_np(user_input)
if user_input.strip().lower() == self.config.get("EXIT_PHRASE", "exit").lower():
print("Exiting...")
exit()
print(f"User input: {user_input}")
prompt, image_base64 = self.get_prompt_and_image(user_input, clipboard_data)
# LLM bắt đầu tạo câu trả lời
chat_completion: Iterator[str] = self.llm.chat_iter(prompt, image_base64)
# TRƯỜNG HỢP 1: KHÔNG DÙNG TTS (Chỉ gửi text)
if not self.config.get("TTS_ON", False):
full_response = ""
for char in chat_completion:
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("\nInterrupted!")
return # Trong generator, return không giá trị để đóng stream
full_response += char
print(char, end="", flush=True)
# Gửi từng ký tự về WebSocket qua yield
yield {
"type": "text",
"data": char
}
print(f"{c[color_code]}Conversation completed.")
return
# TRƯỜNG HỢP 2: CÓ DÙNG TTS
# Lưu ý: speak() của bạn đang chạy Threading bên trong.
# Chúng ta sẽ chạy nó và yield kết quả cuối cùng.
# Gửi thông báo đang xử lý âm thanh
yield {
"type": "info",
"data": "Đang tạo giọng nói..."
}
# Gọi hàm speak (hàm này hiện đang đồng bộ và tự quản lý thread bên trong)
full_response = self.speak(chat_completion, user_input)
if self.verbose:
print(f"\nComplete response: [\n{full_response}\n]")
# Gửi toàn bộ câu phản hồi về để hiển thị trên UI
yield {
"type": "full_text",
"data": full_response
}
print(f"{c[color_code]}Conversation completed.")
def get_user_input(self) -> str:
if self.config.get("VOICE_INPUT_ON", False):
print("Listening from the microphone...")
return self.asr.transcribe_with_local_vad()
else:
return input("\n>> ")
def speak(self, chat_completion: Iterator[str], user_input: str) -> str:
full_response = ""
if self.config.get("SAY_SENTENCE_SEPARATELY", True):
full_response = self.speak_by_sentence_chain(
chat_completion, user_input
)
else:
full_response = ""
for char in chat_completion:
if self.interrupt_manager.in_interrupt():
print("\nInterrupted!")
self.interrupt_manager.interrupt_post_processing()
return None
print(char, end="")
full_response += char
print("\n")
if self.live2d:
tts_target_sentence = self.live2d.remove_emotion_keywords(full_response[0])
else:
tts_target_sentence = full_response[0]
if self.translator and self.config.get("TRANSLATE_AUDIO", False):
print("Translating...")
tts_target_sentence = self.translator.translate(tts_target_sentence)
print(f"Translated: {tts_target_sentence}")
filename = self.audio_manager.generate_audio_file(tts_target_sentence, "temp")
if self.interrupt_manager.in_interrupt():
self.audio_manager.play_audio_file(
sentence=full_response,
filepath=filename,
instrument_filepath=None
)
else:
self.interrupt_manager.interrupt_post_processing()
return full_response
def speak_by_sentence_chain(self, chat_completion: Iterator[str], user_input: str) -> str:
full_response = [""]
sentence_queue = queue.Queue()
audio_queue = queue.Queue()
index = 0
def producer_worker():
nonlocal index
try:
sentence_buffer = ""
for char in chat_completion:
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("Producer interrupted")
return None
if char:
print(char, end="", flush=True)
sentence_buffer += char
full_response[0] += char
check_result = self.check(sentence_buffer)
if check_result == "sing-song":
match = re.search(r'\{.*?\}', sentence_buffer)
if match:
self.sing_song(match.group(0))
sentence_buffer = re.sub(r'\{.*?\}', '', sentence_buffer)
else:
print("Invalid JSON format in sing mode")
# elif check_result == "computer-control":
# match = re.search(r'\{.*?\}', sentence_buffer)
# if match:
# future = asyncio.run_coroutine_threadsafe(
# self.control_computer(match.group(0)),
# self.loop
# )
# try:
# _ = future.result()
# except Exception as e:
# print(f"Error running control_computer coroutine: {e}")
# sentence_buffer = re.sub(r'\{.*?\}', '', sentence_buffer)
# else:
# print("Invalid JSON format in computer control mode")
# elif check_result == "input-text":
# match = re.search(r'\[text_input_start\](.*?)\[text_input_end\]', sentence_buffer, re.DOTALL)
# if match:
# text_to_input = match.group(1)
# self.input_text(text_to_input)
# sentence_buffer = ""
# else:
# match = re.search(r'\[text_input_start\](.*)', sentence_buffer, re.DOTALL)
# if match:
# text_to_input = match.group(1)
# self.input_text(text_to_input)
# sentence_buffer = "[text_input_start]"
elif check_result:
if self.verbose:
print("\n")
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("Producer interrupted")
return None
sentence_queue.put((index, sentence_buffer))
index += 1
sentence_buffer = ""
if sentence_buffer:
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("Producer interrupted")
return None
print("\n")
sentence_queue.put((index, sentence_buffer))
index += 1
except Exception as e:
print(
f"Producer error: Error processing sentence.\n{e}",
"Producer stopped\n",
)
return
finally:
sentence_queue.put((None, None))
def tts_worker():
try:
while True:
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("TTS worker interrupted")
return None
idx, sentence = sentence_queue.get()
if idx is None:
sentence_queue.put((None, None))
break
if self.live2d:
tts_target_sentence = self.live2d.remove_emotion_keywords(sentence)
else:
tts_target_sentence = sentence
if self.translator and self.config.get("TRANSLATE_AUDIO", False):
try:
print("Translating...")
tts_target_sentence = self.translator.translate(tts_target_sentence)
print(f"Translated: {tts_target_sentence}")
except Exception as e:
print(f"Error translating: {e}")
print(f"Text: {tts_target_sentence}")
print("Skipping...")
audio_filepath = self.audio_manager.generate_audio_file(
tts_target_sentence, file_name_no_ext=f"temp-{idx}"
)
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("TTS worker interrupted")
return None
audio_info = {
"index": idx,
"sentence": sentence,
"audio_filepath": audio_filepath,
}
audio_queue.put(audio_info)
except Exception as e:
print(
f"TTS worker error: Error generating audio for sentence.\n{e}",
"TTS worker stopped\n",
)
return
finally:
audio_queue.put(None)
def consumer_worker():
expected_index = 0
audio_buffer = {}
self.heard_sentence = ""
try:
while True:
if self.interrupt_manager.in_interrupt():
self.interrupt_manager.interrupt_post_processing()
print("Consumer interrupted")
return None
audio_info = audio_queue.get()
if audio_info is None:
break
if audio_info:
self.heard_sentence += audio_info["sentence"]
idx = audio_info["index"]
audio_buffer[idx] = audio_info
while expected_index in audio_buffer:
info = audio_buffer.pop(expected_index)
if self.verbose:
print("\n")
self.audio_manager.play_audio_file(
sentence=info["sentence"],
filepath=info["audio_filepath"],
instrument_filepath=None
)
expected_index += 1
except Exception as e:
print(
f"Consumer error: Error playing audio.\n{e}",
"Consumer stopped\n",
)
return
producer_thread = threading.Thread(target=producer_worker)
tts_thread = threading.Thread(target=tts_worker)
consumer_thread = threading.Thread(target=consumer_worker)
producer_thread.start()
tts_thread.start()
consumer_thread.start()
producer_thread.join()
tts_thread.join()
consumer_thread.join()
return full_response[0]
def check(self, text: str):
"""
Check if the text contains a tool call / is the end of a sentence.
"""
if ("sing_song" in text and "}" in text):
return "sing-song"
# if ("computer_control" in text and "}" in text):
# return "computer-control"
# if ("[text_input_start]" in text):
# return False if text.count('[') >= 2 and text.count(']') < 2 else "input-text"
white_list = ["...", "Dr.", "Mr.", "Ms.", "Mrs.", "Jr.", "Sr.", "St.", "Ave.", "Rd.",
"Blvd.", "Dept.", "Univ.", "Prof.", "Ph.D.", "M.D.", "U.S.", "U.K.",
"U.N.", "E.U.", "U.S.A.", "U.K.", "U.S.S.R.", "U.A.E."]
if any(text.strip().endswith(item) for item in white_list):
return False
punctuation_blacklist = [".", "?", "!", "。", "；", "？", "！", "…", "〰", "〜", "～", "！"]
return any(text.strip().endswith(punct) for punct in punctuation_blacklist) # and not "sing_song" in text and not "computer_control" in text and not "input_text" in text
def sing_song(self, sentence):
print("sing mode activated")
try:
data = json.loads(sentence)
song_name = data.get("song_name")
except json.JSONDecodeError:
print("Invalid JSON format in response")
return
if not song_name:
self.audio_manager.play_text("This song, even I have yet to master.")
return
converted_vocal_path = os.path.join('./sing/converted_vocal', f'{song_name}.wav')
instrument_path = os.path.join('./sing/instrument', f'{song_name}.wav')
if not os.path.exists(converted_vocal_path) or not os.path.exists(instrument_path):
self.audio_manager.play_text("This song, even I have yet to master.")
return
self.audio_manager.play_text(f"Please enjoy {song_name}")
self.audio_manager.play_audio_file(
sentence = song_name,
filepath=converted_vocal_path,
instrument_filepath = instrument_path
)
# async def control_computer(self, sentence):
# print("computer control mode activated")
# if platform.system() != 'Darwin':
# self.audio_manager.play_text("This system is currently not supported.")
# return
# try:
# data = json.loads(sentence)
# instruction = data.get("computer_control")
# except json.JSONDecodeError:
# print("Invalid JSON format in response")
# return
# print("computer control mode activated")
# async def api_response_callback(response):
# data = json.loads(response.text)["content"]
# # print(json.dumps(data, indent=4))
# for item in data:
# if item["type"] == "text":
# text = item["text"]
# print(text)
# self.audio_manager.play_text(text)
# await utils_control_computer(self.claude_api_key, instruction, api_response_callback)
# def input_text(self, text):
# # print("input text mode activated")
# utils_input_text(text)
# def get_tool_functions(self):
# return {
# "sing_song" : self.sing_song,
# "control_computer" : self.control_computer
# }
# def call_tool_function(self, function_name, *args):
# if function_name in self.functions:
# self.functions[function_name](*args)
# else:
# print(f"Function {function_name} not found")
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