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dff1e71 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 | # kokoro_tts.py
import base64
import io
import json
import os
import warnings
import asyncio
import soundfile as sf
from pathlib import Path
from python.helpers.print_style import PrintStyle
from python.helpers.notification import (
NotificationManager,
NotificationType,
NotificationPriority,
)
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.filterwarnings("ignore", category=UserWarning)
_pipeline = None
_default_voice = "am_puck,am_onyx"
_voice = _default_voice # Will be overridden by persona manifest if available
_speed = 1.1
is_updating_model = False
# Voice mapping based on persona characteristics
# Kokoro voices: am_* = American male, af_* = American female, bf_* = British female, etc.
VOICE_MAPPINGS = {
# Archetype-based mappings
"sardonic": "am_onyx",
"confident": "am_puck",
"authoritative": "am_onyx",
"playful": "am_puck",
"serious": "am_onyx",
"warm": "af_bella",
"professional": "bf_emma",
"mysterious": "af_sky",
"calm": "af_nicole",
# Gender hints (from persona names or explicit tags)
"male": "am_puck,am_onyx",
"female": "af_bella,af_sky",
}
from typing import Optional
def get_voice_for_persona(persona_path: Optional[str] = None) -> str:
"""
Load voice settings from persona's tts_voice_manifest.json.
Args:
persona_path: Path to persona directory containing tts_voice_manifest.json
Returns:
Kokoro voice string (e.g., "am_puck,am_onyx")
"""
global _voice
if not persona_path:
# Try to get from environment variable
persona_path = os.environ.get("AGENT_PERSONA_PATH")
if not persona_path:
return _default_voice
manifest_path = Path(persona_path) / "tts_voice_manifest.json"
if not manifest_path.exists():
PrintStyle.hint(
f"No TTS manifest found at {manifest_path}, using default voice"
)
return _default_voice
try:
with open(manifest_path, "r", encoding="utf-8") as f:
manifest = json.load(f)
# Extract style tokens to determine voice characteristics
style_tokens = manifest.get("style_tokens", [])
# Build voice based on style tokens
voices = set()
for token in style_tokens:
# Parse tokens like "tone:sardonic" or "quirk:deflects with humor"
if ":" in token:
_, value = token.split(":", 1)
value = value.strip().lower()
else:
value = token.lower()
# Match against our voice mappings
for key, voice in VOICE_MAPPINGS.items():
if key in value:
voices.add(voice.split(",")[0]) # Take primary voice
break
if voices:
voice_string = ",".join(sorted(voices)[:2]) # Max 2 voices for blending
PrintStyle.standard(
f"Loaded persona voice: {voice_string} (from {manifest_path.name})"
)
return voice_string
# Fallback: check archetype for hints
archetype = manifest.get("archetype", "").lower()
for key, voice in VOICE_MAPPINGS.items():
if key in archetype:
PrintStyle.standard(f"Matched voice from archetype: {voice}")
return voice
PrintStyle.hint(f"No voice mapping found in manifest, using default")
return _default_voice
except Exception as e:
PrintStyle.error(f"Error loading TTS manifest: {e}")
return _default_voice
def set_persona_voice(persona_path: Optional[str] = None) -> str:
"""
Set the global voice based on persona manifest.
Call this during agent initialization.
"""
global _voice
_voice = get_voice_for_persona(persona_path)
return _voice
async def preload():
try:
# return await runtime.call_development_function(_preload)
return await _preload()
except Exception as e:
# if not runtime.is_development():
raise e
# Fallback to direct execution if RFC fails in development
# PrintStyle.standard("RFC failed, falling back to direct execution...")
# return await _preload()
async def _preload():
global _pipeline, is_updating_model
while is_updating_model:
await asyncio.sleep(0.1)
try:
is_updating_model = True
if not _pipeline:
NotificationManager.send_notification(
NotificationType.INFO,
NotificationPriority.NORMAL,
"Loading Kokoro TTS model...",
display_time=99,
group="kokoro-preload",
)
PrintStyle.standard("Loading Kokoro TTS model...")
from kokoro import KPipeline
_pipeline = KPipeline(lang_code="a", repo_id="hexgrad/Kokoro-82M")
NotificationManager.send_notification(
NotificationType.INFO,
NotificationPriority.NORMAL,
"Kokoro TTS model loaded.",
display_time=2,
group="kokoro-preload",
)
finally:
is_updating_model = False
async def is_downloading():
try:
# return await runtime.call_development_function(_is_downloading)
return _is_downloading()
except Exception as e:
# if not runtime.is_development():
raise e
# Fallback to direct execution if RFC fails in development
# return _is_downloading()
def _is_downloading():
return is_updating_model
async def is_downloaded():
try:
# return await runtime.call_development_function(_is_downloaded)
return _is_downloaded()
except Exception as e:
# if not runtime.is_development():
raise e
# Fallback to direct execution if RFC fails in development
# return _is_downloaded()
def _is_downloaded():
return _pipeline is not None
async def synthesize_sentences(sentences: list[str]):
"""Generate audio for multiple sentences and return concatenated base64 audio"""
try:
# return await runtime.call_development_function(_synthesize_sentences, sentences)
return await _synthesize_sentences(sentences)
except Exception as e:
# if not runtime.is_development():
raise e
# Fallback to direct execution if RFC fails in development
# return await _synthesize_sentences(sentences)
async def _synthesize_sentences(sentences: list[str]):
await _preload()
combined_audio = []
try:
for sentence in sentences:
if sentence.strip():
segments = _pipeline(sentence.strip(), voice=_voice, speed=_speed) # type: ignore
segment_list = list(segments)
for segment in segment_list:
audio_tensor = segment.audio
audio_numpy = audio_tensor.detach().cpu().numpy() # type: ignore
combined_audio.extend(audio_numpy)
# Convert combined audio to bytes
buffer = io.BytesIO()
sf.write(buffer, combined_audio, 24000, format="WAV")
audio_bytes = buffer.getvalue()
# Return base64 encoded audio
return base64.b64encode(audio_bytes).decode("utf-8")
except Exception as e:
PrintStyle.error(f"Error in Kokoro TTS synthesis: {e}")
raise
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