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import torch
from datetime import datetime
from pathlib import Path
from .voice import quick_mix_voice
def handle_commands(user_input, generator, speed, model_path=None):
"""
Handles bot commands to control the voice generator.
Args:
user_input (str): The command input from the user.
generator: The voice generator object.
speed (float): The current speed of the generator.
model_path (str, optional): The path to the model. Defaults to None.
Returns:
bool: True if a command was handled, False otherwise.
"""
if user_input.lower() == "quit":
print("Goodbye!")
return True
if user_input.lower() == "voices":
voices = generator.list_available_voices()
print("\nAvailable voices:")
for voice in voices:
print(f"- {voice}")
return True
if user_input.startswith("speed="):
try:
new_speed = float(user_input.split("=")[1])
print(f"Speed set to {new_speed}")
return True
except:
print("Invalid speed value. Use format: speed=1.2")
return True
if user_input.startswith("voice="):
try:
voice = user_input.split("=")[1]
if voice in generator.list_available_voices():
generator.initialize(model_path or generator.model_path, voice)
print(f"Switched to voice: {voice}")
else:
print("Voice not found. Use 'voices' to list available voices.")
except Exception as e:
print(f"Error changing voice: {str(e)}")
return True
if user_input.startswith("mix="):
try:
mix_input = user_input.split("=")[1]
voices_weights = mix_input.split(":")
voices = [v.strip() for v in voices_weights[0].split(",")]
if len(voices_weights) > 1:
weights = [float(w.strip()) for w in voices_weights[1].split(",")]
else:
weights = [0.5, 0.5]
if len(voices) != 2 or len(weights) != 2:
print(
"Mix command requires exactly two voices. Format: mix=voice1,voice2[:weight1,weight2]"
)
return True
available_voices = generator.list_available_voices()
if not all(voice in available_voices for voice in voices):
print(
"One or more voices not found. Use 'voices' to list available voices."
)
return True
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
output_name = f"af_mixed_voice_{timestamp}"
voice_tensors = []
for voice_name in voices:
voice_path = Path(generator.voices_dir) / f"{voice_name}.pt"
voice = torch.load(voice_path, weights_only=True)
voice_tensors.append(voice)
mixed = quick_mix_voice(
output_name, generator.voices_dir, *voice_tensors, weights=weights
)
generator.initialize(model_path or generator.model_path, output_name)
print(
f"Mixed voices: {voices[0]} ({weights[0]:.1f}) and {voices[1]} ({weights[1]:.1f})"
)
except Exception as e:
print(f"Error mixing voices: {str(e)}")
return True
return False
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