engines: import f5-tts + kokoro + tortoise sidecars into the tree
The python FastAPI sidecars have lived ad-hoc at /srv/appdata/ <engine>/build/ on the host without version control. Bringing them into the skald repo so the engine code travels with the cross-engine routing it depends on. This commit lands the VANILLA version of each engine on main: engines/f5-tts/ SWivid F5-TTS (CC-BY-NC weights flagged) engines/kokoro/ hexgrad Kokoro-82M (Apache 2.0 top to bottom) engines/tortoise/ neonbjb Tortoise-TTS (Apache 2.0 top to bottom) Engine-specific kludges (question doubling, GPU coordination, pause-duration tuning) get layered on engine/* branches per the README. Main stays the safe-to-read baseline.
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324
engines/kokoro/server.py
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324
engines/kokoro/server.py
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"""Kokoro-82M FastAPI server, sibling to f5_server.
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Same /synthesize contract as F5 so skald can route between engines
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just by which URL it points at. The semantic difference: Kokoro
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voices are NAMED (af_heart, af_bella, am_michael, etc.) — there's no
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reference audio. We repurpose the `ref_audio_path` field to carry
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the voice name; if it starts with '/' we treat as F5-style path and
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error.
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Render-and-stitch:
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The naive "feed the whole chapter to Kokoro" path produces audio
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that runs paragraphs together — no breath between scenes, no beat
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on a hard line break. So this server splits the input on paragraph
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and scene boundaries, renders each chunk, and concatenates with
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explicit silence inserts between chunks.
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Control tags the splitter recognizes (case-insensitive):
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[pause:1.5s] — silence of N seconds at this point
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[pause:500ms] — silence of N milliseconds at this point
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[breath] — short breath beat (~400ms)
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[scene] — major scene break (~1500ms)
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Implicit breaks the splitter inserts:
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Blank line between paragraphs → 700ms
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A line of just `---` → 1500ms (scene break)
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Sentence-internal pacing (commas, periods, em-dashes, ellipses)
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is left to Kokoro's own phonemizer — it handles that well.
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License: Apache 2.0 (code + model weights). Clean stack for the
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sleep-quality narrator use case.
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"""
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import logging
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import re
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import time
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import uuid
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from pathlib import Path
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import numpy as np
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import soundfile as sf
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import torch
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel, Field
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from kokoro import KPipeline
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log = logging.getLogger("kokoro-server")
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s %(message)s")
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# ─── pipeline state ──────────────────────────────────────────────
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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DEFAULT_LANG = "a"
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DEFAULT_VOICE = "af_heart"
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AUDIO_ROOT = Path("/audio")
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SAMPLE_RATE = 24000
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# Default silence durations for implicit breaks. Tags override.
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PARAGRAPH_GAP_S = 0.7
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SCENE_GAP_S = 1.5
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BREATH_GAP_S = 0.4
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_pipelines: dict[str, KPipeline] = {}
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def _get_pipeline(lang_code: str) -> KPipeline:
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if lang_code not in _pipelines:
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log.info("loading kokoro pipeline lang=%s device=%s", lang_code, DEVICE)
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_pipelines[lang_code] = KPipeline(lang_code=lang_code, device=DEVICE)
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log.info("kokoro pipeline loaded lang=%s", lang_code)
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return _pipelines[lang_code]
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# ─── split + render pipeline ─────────────────────────────────────
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# A "node" is one of three kinds; the renderer walks the list,
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# calls Kokoro on each text node with its (possibly per-segment)
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# voice, and emits zeros for each silence node.
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class Node:
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__slots__ = ("kind", "value", "voice")
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def __init__(self, kind: str, value, voice: str | None = None):
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# kind ∈ {"text", "silence"}; value is str for text and
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# float seconds for silence. voice override is only used
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# on text nodes from [voice:X]...[/voice] blocks; outside
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# those blocks the request's default voice is used.
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self.kind = kind
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self.value = value
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self.voice = voice
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# Voice-block delimiters are parsed at a higher level than other
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# tags so dialogue can contain its own [breath]/[pause] beats.
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_VOICE_OPEN_RE = re.compile(r"\[voice:([A-Za-z0-9_-]+)\]")
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_VOICE_CLOSE = "[/voice]"
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_TAG_RE = re.compile(
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r"\[(pause:(?P<dur>[0-9]+(?:\.[0-9]+)?)(?P<unit>s|ms)?|breath|scene)\]",
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re.IGNORECASE,
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)
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def _parse_tag(match: re.Match) -> float:
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body = match.group(0).lower().strip("[]")
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if body == "breath":
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return BREATH_GAP_S
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if body == "scene":
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return SCENE_GAP_S
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dur = float(match.group("dur"))
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unit = (match.group("unit") or "s").lower()
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return dur / 1000.0 if unit == "ms" else dur
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def _expand_inline(text: str, voice: str | None) -> list[Node]:
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"""Expand inline [breath]/[pause]/[scene] tags inside a chunk
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of text that already has a single voice attribution. Voice
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blocks themselves are handled one level up in split_to_nodes."""
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out: list[Node] = []
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text = text.strip()
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if not text:
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return out
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cursor = 0
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for m in _TAG_RE.finditer(text):
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pre = text[cursor : m.start()].strip()
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if pre:
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out.append(Node("text", pre, voice))
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out.append(Node("silence", _parse_tag(m)))
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cursor = m.end()
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tail = text[cursor:].strip()
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if tail:
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out.append(Node("text", tail, voice))
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return out
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def split_to_nodes(text: str) -> list[Node]:
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"""Walk the source text and split it into text+silence nodes.
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Order of operations:
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1. Split on `---` lines (scene breaks).
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2. Within each scene, split on blank lines (paragraph breaks).
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3. Within each paragraph, split on [voice:X]...[/voice] blocks
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so each dialogue line carries its own voice attribution.
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4. Within each (paragraph, voice-region) chunk, expand inline
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[breath]/[pause:Xs]/[scene] tags.
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"""
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nodes: list[Node] = []
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scenes = re.split(r"(?m)^\s*---\s*$", text)
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for s_idx, scene in enumerate(scenes):
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if s_idx > 0:
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nodes.append(Node("silence", SCENE_GAP_S))
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paragraphs = re.split(r"\n\s*\n", scene)
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first_para = True
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for para in paragraphs:
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para = para.strip()
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if not para:
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continue
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if not first_para:
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nodes.append(Node("silence", PARAGRAPH_GAP_S))
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first_para = False
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nodes.extend(_split_paragraph_voices(para))
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return nodes
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def _split_paragraph_voices(para: str) -> list[Node]:
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"""Split a single paragraph on [voice:X]...[/voice] blocks.
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Outside those blocks the voice is None (request default).
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Unmatched/orphan [/voice] markers are silently stripped.
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"""
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out: list[Node] = []
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cursor = 0
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while cursor < len(para):
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m = _VOICE_OPEN_RE.search(para, cursor)
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if not m:
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out.extend(_expand_inline(para[cursor:], None))
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break
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# Text BEFORE the voice block uses default voice.
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out.extend(_expand_inline(para[cursor : m.start()], None))
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voice = m.group(1)
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body_start = m.end()
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close_idx = para.find(_VOICE_CLOSE, body_start)
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if close_idx < 0:
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# Unclosed voice block; treat rest of paragraph as that
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# voice. Defensive — should be rare.
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out.extend(_expand_inline(para[body_start:], voice))
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break
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out.extend(_expand_inline(para[body_start:close_idx], voice))
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cursor = close_idx + len(_VOICE_CLOSE)
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return out
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def _silence_samples(seconds: float) -> np.ndarray:
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n = int(round(seconds * SAMPLE_RATE))
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return np.zeros(n, dtype=np.float32)
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# ─── FastAPI app ─────────────────────────────────────────────────
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class SynthesizeRequest(BaseModel):
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gen_text: str = Field(min_length=1)
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ref_audio_path: str = DEFAULT_VOICE
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ref_text: str | None = None
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output_filename: str | None = None
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speed: float = Field(default=1.0, ge=0.3, le=2.0)
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lang_code: str = DEFAULT_LANG
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class SynthesizeResponse(BaseModel):
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ok: bool
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output_path: str
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sample_rate_hz: int
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duration_seconds: float
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elapsed_ms: int
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chars_in: int
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engine: str
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voice: str
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text_nodes: int
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silence_nodes: int
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# Every distinct Kokoro voice id that actually got rendered.
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# Single-element when no [voice:X] tags were in the input;
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# multiple when multi-voice dialogue was attributed.
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voices_used: list[str]
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app = FastAPI(title="kokoro-server", version="0.2.0")
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@app.on_event("startup")
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def _startup() -> None:
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_get_pipeline(DEFAULT_LANG)
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@app.get("/healthz")
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def healthz() -> dict:
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# Shape matches f5_server's so the same Rust HealthResponse
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# struct deserializes both: model/vocoder/loaded fields are
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# required by skald-core::narrate::HealthResponse.
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return {
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"ok": True,
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"device": DEVICE,
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"model": "kokoro-82m",
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"vocoder": "kokoro-internal",
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"loaded": bool(_pipelines),
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"engine": "kokoro-82m",
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"default_voice": DEFAULT_VOICE,
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"default_lang": DEFAULT_LANG,
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"loaded_langs": list(_pipelines.keys()),
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"version": "0.2.0",
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}
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@app.post("/synthesize", response_model=SynthesizeResponse)
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def synthesize(req: SynthesizeRequest) -> SynthesizeResponse:
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if req.ref_audio_path.startswith("/"):
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raise HTTPException(
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400,
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"ref_audio_path looks like a filesystem path; Kokoro takes a voice "
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"name like 'af_heart' or 'am_michael'. Did you mean to route to the "
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"f5-tts engine?",
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)
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voice = req.ref_audio_path
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output_filename = req.output_filename or f"{uuid.uuid4().hex}.wav"
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if "/" in output_filename or ".." in output_filename:
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raise HTTPException(400, "output_filename must be a bare name, no path parts")
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output_path = AUDIO_ROOT / output_filename
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output_path.parent.mkdir(parents=True, exist_ok=True)
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pipeline = _get_pipeline(req.lang_code)
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# Split the text into a node list. Empty nodes get filtered.
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nodes = [n for n in split_to_nodes(req.gen_text) if n.kind == "silence" or n.value]
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text_count = sum(1 for n in nodes if n.kind == "text")
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silence_count = sum(1 for n in nodes if n.kind == "silence")
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if text_count == 0:
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raise HTTPException(400, "gen_text expanded to zero text nodes")
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started = time.monotonic()
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pieces: list[np.ndarray] = []
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voices_used: set[str] = set()
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for node in nodes:
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if node.kind == "silence":
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pieces.append(_silence_samples(node.value))
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continue
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# text: hand to Kokoro. The node's voice override (set by
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# [voice:X]...[/voice] blocks) wins; otherwise the request's
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# default narrator voice.
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seg_voice = node.voice or voice
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voices_used.add(seg_voice)
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chunk_audio: list[np.ndarray] = []
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for _, _, audio in pipeline(node.value, voice=seg_voice, speed=req.speed):
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arr = audio.cpu().numpy() if hasattr(audio, "cpu") else np.asarray(audio)
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chunk_audio.append(arr.astype(np.float32))
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if chunk_audio:
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pieces.append(np.concatenate(chunk_audio))
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elapsed_ms = int((time.monotonic() - started) * 1000)
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if not pieces:
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raise HTTPException(500, "kokoro returned no audio")
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full_audio = np.concatenate(pieces)
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sf.write(str(output_path), full_audio, SAMPLE_RATE, subtype="PCM_16")
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duration_s = float(len(full_audio)) / float(SAMPLE_RATE)
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log.info(
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"synthesized chars=%d voice=%s text_nodes=%d silence_nodes=%d "
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"voices_used=%s -> %s (dur=%.2fs, elapsed=%dms)",
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len(req.gen_text), voice, text_count, silence_count,
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sorted(voices_used), output_path, duration_s, elapsed_ms,
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)
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return SynthesizeResponse(
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ok=True,
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output_path=str(output_path),
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sample_rate_hz=SAMPLE_RATE,
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duration_seconds=duration_s,
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elapsed_ms=elapsed_ms,
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chars_in=len(req.gen_text),
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engine="kokoro-82m",
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voice=voice,
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text_nodes=text_count,
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silence_nodes=silence_count,
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voices_used=sorted(voices_used),
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)
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