mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-07-29 18:46:59 +00:00
bc4dcb1b02
Salvaged from PR #47588 and rebased onto the post-campaign streaming core: the StreamingTTSProvider ABC/registry and the ElevenLabs/OpenAI streamers already live on main (tools/tts_streaming.py), so this ports the pieces main lacked: - GeminiStreamer: streamGenerateContent?alt=sse -> base64 PCM chunks (24 kHz mono int16), reusing main's DEFAULT_GEMINI_TTS_* constants. - XAIStreamer: WebSocket wss://api.x.ai/v1/tts -> binary PCM frames, async->sync bridged via the _collect_async test seam. - tts.streaming.provider config knob: pin one streamer, or 'auto' to walk the priority list elevenlabs -> gemini -> openai -> xai. Unset keeps the never-swap-the-user's-voice default. - docs/streaming-tts.md: architecture, capability matrix, how to add a provider. - Unit tests for the knob, SSE parsing, and the WS bridge; key-gated E2E tests (skipped without credentials). Refs: #47588
437 lines
16 KiB
Python
437 lines
16 KiB
Python
"""Provider-agnostic streaming TTS: sentence text → int16 PCM chunk iterator.
|
|
|
|
The keystone of Hermes' conversational voice UX. `stream_tts_to_speaker`
|
|
(``tools.tts_tool``) owns the sentence buffer, sounddevice output, and
|
|
stop/queue protocol; this module owns the *provider* half — turning one
|
|
sentence into audio the moment it's ready, so playback starts on sentence one
|
|
instead of after the whole reply.
|
|
|
|
Two provider shapes, one contract (int16 mono PCM at ``sample_rate``):
|
|
|
|
* **True streamers** (`StreamingTTSProvider.stream`) — chunked APIs
|
|
(ElevenLabs pcm_24000, OpenAI pcm, …) that yield audio as it synthesizes.
|
|
Lowest time-to-first-audio.
|
|
* **Everyone else** — providers with no chunked API still get per-*sentence*
|
|
playback via the proven sync `text_to_speech_tool` path (handled by the
|
|
dispatcher, not here), so edge (the default) is conversational too.
|
|
|
|
Adding a streamer is `@register("name")` on a `StreamingTTSProvider` subclass;
|
|
the dispatcher, config gate (`tts.<name>.streaming`), and resolver come free.
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import logging
|
|
import re
|
|
import time
|
|
from abc import ABC, abstractmethod
|
|
from typing import Callable, Dict, Iterator, List, Optional
|
|
|
|
from tools.tool_backend_helpers import resolve_openai_audio_api_key
|
|
from tools.tts_tool import _get_provider, _load_tts_config, get_env_value
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Interruption latch — lets the model know it was cut off mid-speech
|
|
# ---------------------------------------------------------------------------
|
|
# When the user barges in on a spoken reply (talks over it, types, hits the
|
|
# record key), the surface marks the latch; the next turn's submit path takes
|
|
# it and prepends SPEECH_INTERRUPTED_NOTE to the model-bound message (API-call
|
|
# local — never persisted, same as the CLI's model-switch notes). The TTL
|
|
# keeps a stale barge from annotating an unrelated message minutes later.
|
|
|
|
SPEECH_INTERRUPTED_NOTE = (
|
|
"[Note: the user interrupted your previous spoken reply before it finished.]"
|
|
)
|
|
_INTERRUPT_TTL_S = 120.0
|
|
_interrupted_at: Optional[float] = None
|
|
|
|
|
|
def mark_speech_interrupted() -> None:
|
|
global _interrupted_at
|
|
_interrupted_at = time.monotonic()
|
|
|
|
|
|
def take_speech_interrupted() -> bool:
|
|
"""Pop the latch; True when a barge happened within the TTL."""
|
|
global _interrupted_at
|
|
at, _interrupted_at = _interrupted_at, None
|
|
return at is not None and time.monotonic() - at < _INTERRUPT_TTL_S
|
|
|
|
# Sentence boundary: after .!? followed by whitespace, or a blank line.
|
|
SENTENCE_BOUNDARY_RE = re.compile(r"(?<=[.!?])(?:\s|\n)|(?:\n\n)")
|
|
_THINK_BLOCK_RE = re.compile(r"<think[\s>].*?</think>", flags=re.DOTALL)
|
|
|
|
|
|
class SentenceChunker:
|
|
"""Incremental sentence cutter for LLM token deltas.
|
|
|
|
Shared by the speaker pipeline (`stream_tts_to_speaker`) and the
|
|
speak-stream WebSocket so every surface cuts speech identically. Strips
|
|
``<think>`` blocks (even split across deltas) and merges fragments shorter
|
|
than *min_len* into the following sentence, so "Ha!" rides along with the
|
|
sentence after it instead of stalling as a tiny clip.
|
|
"""
|
|
|
|
def __init__(self, min_len: int = 20):
|
|
self.min_len = min_len
|
|
self.buf = ""
|
|
|
|
def feed(self, delta: str) -> List[str]:
|
|
"""Absorb *delta*; return every complete sentence now ready to speak."""
|
|
self.buf = _THINK_BLOCK_RE.sub("", self.buf + delta)
|
|
if "<think" in self.buf and "</think>" not in self.buf:
|
|
return [] # open think tag — the closing tag may arrive next delta
|
|
out: List[str] = []
|
|
start = 0 # skip boundaries that would leave the head too short
|
|
while m := SENTENCE_BOUNDARY_RE.search(self.buf, start):
|
|
head = self.buf[: m.end()]
|
|
if len(head.strip()) < self.min_len:
|
|
start = m.end()
|
|
continue
|
|
out.append(head)
|
|
self.buf = self.buf[m.end():]
|
|
start = 0
|
|
return out
|
|
|
|
def flush(self) -> List[str]:
|
|
"""Drain the tail (end-of-text or long-idle flush)."""
|
|
tail = _THINK_BLOCK_RE.sub("", self.buf).strip()
|
|
self.buf = ""
|
|
return [tail] if tail else []
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# ABC + registry
|
|
# ---------------------------------------------------------------------------
|
|
|
|
class StreamingTTSProvider(ABC):
|
|
"""Yields raw int16, little-endian, mono PCM chunks at ``sample_rate``."""
|
|
|
|
sample_rate: int = 24000
|
|
channels: int = 1
|
|
sample_width: int = 2 # bytes/sample (int16)
|
|
|
|
def __init__(self, tts_config: Dict, section: Dict):
|
|
self.tts_config = tts_config
|
|
self.section = section
|
|
|
|
@staticmethod
|
|
@abstractmethod
|
|
def available() -> bool:
|
|
"""True when this provider's credentials/SDK are usable right now."""
|
|
|
|
@abstractmethod
|
|
def stream(self, text: str) -> Iterator[bytes]:
|
|
"""Yield PCM chunks for ``text``. Raise on failure (caller logs)."""
|
|
|
|
|
|
_REGISTRY: Dict[str, type[StreamingTTSProvider]] = {}
|
|
|
|
|
|
def register(name: str) -> Callable[[type[StreamingTTSProvider]], type[StreamingTTSProvider]]:
|
|
def _wrap(cls: type[StreamingTTSProvider]) -> type[StreamingTTSProvider]:
|
|
_REGISTRY[name] = cls
|
|
return cls
|
|
|
|
return _wrap
|
|
|
|
|
|
def _try_instantiate(name: str, tts_config: Dict) -> Optional[StreamingTTSProvider]:
|
|
"""Construct the registered streamer *name* if it's usable, else None."""
|
|
cls = _REGISTRY.get(name)
|
|
if cls is None or not cls.available():
|
|
return None
|
|
try:
|
|
return cls(tts_config, tts_config.get(name) or {})
|
|
except Exception as exc: # pragma: no cover - defensive
|
|
logger.debug("streaming provider %s init failed: %s", name, exc)
|
|
return None
|
|
|
|
|
|
# Fallback priority for ``tts.streaming.provider: auto`` — best chunked
|
|
# latency/quality first. Deliberately hard-coded (a UX decision, not a
|
|
# config knob); edge is absent because it has no chunked-PCM API — the
|
|
# dispatcher's per-sentence sync path keeps it conversational instead.
|
|
_PROVIDER_PRIORITY: List[str] = ["elevenlabs", "gemini", "openai", "xai"]
|
|
|
|
|
|
def resolve_streaming_provider(
|
|
tts_config: Dict,
|
|
preferred: Optional[str] = None,
|
|
) -> Optional[StreamingTTSProvider]:
|
|
"""Return a ready streamer for the *configured* provider, else ``None``.
|
|
|
|
Resolution order:
|
|
|
|
1. ``tts.streaming.provider`` (config knob) when set:
|
|
* a provider name pins that exact streamer (or ``None`` if unusable);
|
|
* ``auto`` walks the priority list (``elevenlabs → gemini → openai
|
|
→ xai``) and returns the first usable streamer — an explicit
|
|
opt-in to "give me the best chunked voice available".
|
|
2. Otherwise the *configured* TTS provider (or ``preferred`` override).
|
|
``None`` means "no chunked API for this provider" — the dispatcher
|
|
then speaks per-sentence via the sync path, preserving the user's
|
|
chosen voice. We never silently swap to a different provider just
|
|
to get streaming.
|
|
"""
|
|
streaming_cfg = tts_config.get("streaming") or {}
|
|
pinned = str(streaming_cfg.get("provider") or "").lower().strip()
|
|
if pinned == "auto":
|
|
for name in _PROVIDER_PRIORITY:
|
|
inst = _try_instantiate(name, tts_config)
|
|
if inst is not None:
|
|
return inst
|
|
return None
|
|
if pinned:
|
|
return _try_instantiate(pinned, tts_config)
|
|
|
|
name = (preferred or _get_provider(tts_config)).lower().strip()
|
|
return _try_instantiate(name, tts_config)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Providers
|
|
# ---------------------------------------------------------------------------
|
|
|
|
@register("elevenlabs")
|
|
class ElevenLabsStreamer(StreamingTTSProvider):
|
|
"""ElevenLabs chunked HTTP → pcm_24000 (the original reference path)."""
|
|
|
|
sample_rate = 24000
|
|
|
|
@staticmethod
|
|
def available() -> bool:
|
|
return bool(get_env_value("ELEVENLABS_API_KEY"))
|
|
|
|
def stream(self, text: str) -> Iterator[bytes]:
|
|
from tools.tts_tool import (
|
|
DEFAULT_ELEVENLABS_STREAMING_MODEL_ID,
|
|
DEFAULT_ELEVENLABS_VOICE_ID,
|
|
_elevenlabs_environment_kwargs,
|
|
_import_elevenlabs,
|
|
)
|
|
|
|
client = _import_elevenlabs()(
|
|
api_key=get_env_value("ELEVENLABS_API_KEY"),
|
|
**_elevenlabs_environment_kwargs(self.section),
|
|
)
|
|
voice_id = self.section.get("voice_id", DEFAULT_ELEVENLABS_VOICE_ID)
|
|
model_id = self.section.get(
|
|
"streaming_model_id",
|
|
self.section.get("model_id", DEFAULT_ELEVENLABS_STREAMING_MODEL_ID),
|
|
)
|
|
yield from client.text_to_speech.convert(
|
|
text=text,
|
|
voice_id=voice_id,
|
|
model_id=model_id,
|
|
output_format="pcm_24000",
|
|
)
|
|
|
|
|
|
def _openai_config_api_key() -> str:
|
|
"""Return ``tts.openai.api_key`` from config.yaml, or empty string."""
|
|
try:
|
|
openai_cfg = (_load_tts_config().get("openai") or {})
|
|
except Exception:
|
|
return ""
|
|
return openai_cfg.get("api_key") or ""
|
|
|
|
|
|
@register("openai")
|
|
class OpenAIStreamer(StreamingTTSProvider):
|
|
"""OpenAI speech with ``response_format=pcm`` (24 kHz mono int16)."""
|
|
|
|
sample_rate = 24000
|
|
|
|
@staticmethod
|
|
def available() -> bool:
|
|
return bool(_openai_config_api_key() or resolve_openai_audio_api_key())
|
|
|
|
def stream(self, text: str) -> Iterator[bytes]:
|
|
from openai import OpenAI
|
|
|
|
client = OpenAI(
|
|
api_key=(self.section.get("api_key") or resolve_openai_audio_api_key()),
|
|
base_url=(
|
|
self.section.get("base_url")
|
|
or get_env_value("OPENAI_BASE_URL")
|
|
or None
|
|
),
|
|
)
|
|
model = self.section.get("model", "gpt-4o-mini-tts")
|
|
voice = self.section.get("voice", "alloy")
|
|
with client.audio.speech.with_streaming_response.create(
|
|
model=model,
|
|
voice=voice,
|
|
input=text,
|
|
response_format="pcm",
|
|
) as response:
|
|
yield from response.iter_bytes()
|
|
|
|
|
|
@register("gemini")
|
|
class GeminiStreamer(StreamingTTSProvider):
|
|
"""Gemini ``streamGenerateContent?alt=sse`` → base64 PCM chunks (24 kHz).
|
|
|
|
Each SSE event carries one base64-encoded PCM chunk under
|
|
``candidates[0].content.parts[*].inlineData.data``; we decode and yield
|
|
each one as it arrives.
|
|
"""
|
|
|
|
sample_rate = 24000
|
|
|
|
@staticmethod
|
|
def available() -> bool:
|
|
return bool(
|
|
get_env_value("GEMINI_API_KEY") or get_env_value("GOOGLE_API_KEY")
|
|
)
|
|
|
|
def stream(self, text: str) -> Iterator[bytes]:
|
|
import base64
|
|
import json as _json
|
|
|
|
import requests
|
|
|
|
from tools.tts_tool import (
|
|
DEFAULT_GEMINI_TTS_BASE_URL,
|
|
DEFAULT_GEMINI_TTS_MODEL,
|
|
DEFAULT_GEMINI_TTS_VOICE,
|
|
)
|
|
|
|
api_key = (
|
|
get_env_value("GEMINI_API_KEY") or get_env_value("GOOGLE_API_KEY")
|
|
)
|
|
model = str(self.section.get("model", DEFAULT_GEMINI_TTS_MODEL)).strip() or DEFAULT_GEMINI_TTS_MODEL
|
|
voice = str(self.section.get("voice", DEFAULT_GEMINI_TTS_VOICE)).strip() or DEFAULT_GEMINI_TTS_VOICE
|
|
base_url = str(
|
|
self.section.get("base_url")
|
|
or get_env_value("GEMINI_BASE_URL")
|
|
or DEFAULT_GEMINI_TTS_BASE_URL
|
|
).strip().rstrip("/")
|
|
|
|
payload = {
|
|
"contents": [{"parts": [{"text": text}]}],
|
|
"generationConfig": {
|
|
"responseModalities": ["AUDIO"],
|
|
"speechConfig": {
|
|
"voiceConfig": {
|
|
"prebuiltVoiceConfig": {"voiceName": voice},
|
|
},
|
|
},
|
|
},
|
|
}
|
|
# ``?alt=sse`` flips the response from a single JSON blob to an SSE
|
|
# feed of base64 PCM chunks — the whole point of this provider.
|
|
url = f"{base_url}/models/{model}:streamGenerateContent"
|
|
|
|
def _sse_chunks() -> Iterator[bytes]:
|
|
with requests.post(
|
|
url,
|
|
params={"alt": "sse", "key": api_key},
|
|
json=payload,
|
|
timeout=60,
|
|
stream=True,
|
|
) as response:
|
|
response.raise_for_status()
|
|
for line in response.iter_lines(decode_unicode=True):
|
|
if not line or not line.startswith("data: "):
|
|
continue
|
|
try:
|
|
event = _json.loads(line[len("data: "):])
|
|
parts = event["candidates"][0]["content"]["parts"]
|
|
except (ValueError, KeyError, IndexError, TypeError):
|
|
continue
|
|
for part in parts:
|
|
inline = part.get("inlineData") or part.get("inline_data") or {}
|
|
b64 = inline.get("data", "")
|
|
if not b64:
|
|
continue
|
|
try:
|
|
yield base64.b64decode(b64)
|
|
except (ValueError, TypeError) as exc:
|
|
logger.warning("Gemini SSE: bad base64 audio: %s", exc)
|
|
|
|
yield from _sse_chunks()
|
|
|
|
|
|
@register("xai")
|
|
class XAIStreamer(StreamingTTSProvider):
|
|
"""xAI WebSocket TTS → binary PCM frames (24 kHz mono int16).
|
|
|
|
xAI's chunked TTS API is WebSocket-only (``wss://api.x.ai/v1/tts``).
|
|
The async WS loop is bridged to the sync iterator contract via
|
|
``_collect_async`` — the seam unit tests monkeypatch.
|
|
"""
|
|
|
|
sample_rate = 24000
|
|
|
|
@staticmethod
|
|
def available() -> bool:
|
|
return bool(get_env_value("XAI_API_KEY"))
|
|
|
|
def stream(self, text: str) -> Iterator[bytes]:
|
|
yield from self._collect_async(text)
|
|
|
|
# -- async→sync bridge (test seam) ------------------------------------
|
|
|
|
def _collect_async(self, text: str) -> List[bytes]:
|
|
import asyncio
|
|
|
|
return asyncio.run(self._drain_async(text))
|
|
|
|
async def _drain_async(self, text: str) -> List[bytes]:
|
|
frames: List[bytes] = []
|
|
async for frame in self._async_frames(text):
|
|
frames.append(frame)
|
|
return frames
|
|
|
|
async def _async_frames(self, text: str):
|
|
import json as _json
|
|
|
|
import websockets
|
|
|
|
from tools.tts_tool import DEFAULT_XAI_VOICE_ID
|
|
|
|
api_key = (get_env_value("XAI_API_KEY") or "").strip()
|
|
if not api_key:
|
|
raise RuntimeError("XAI_API_KEY not set; cannot use xAI streaming TTS")
|
|
voice = str(self.section.get("voice_id", DEFAULT_XAI_VOICE_ID)).strip() or DEFAULT_XAI_VOICE_ID
|
|
ws_url = str(
|
|
self.section.get("streaming_url") or "wss://api.x.ai/v1/tts"
|
|
).strip()
|
|
|
|
async with websockets.connect(
|
|
ws_url, extra_headers={"Authorization": f"Bearer {api_key}"}
|
|
) as ws:
|
|
await ws.send(_json.dumps({
|
|
"text": text,
|
|
"voice_id": voice,
|
|
"response_format": "pcm",
|
|
}))
|
|
try:
|
|
while True:
|
|
message = await ws.recv()
|
|
if isinstance(message, (bytes, bytearray, memoryview)):
|
|
yield bytes(message)
|
|
continue
|
|
try:
|
|
envelope = _json.loads(message)
|
|
except (ValueError, TypeError):
|
|
if message == "done":
|
|
return
|
|
continue
|
|
etype = envelope.get("type")
|
|
if etype == "done":
|
|
return
|
|
if etype == "error":
|
|
logger.warning("xAI WS error envelope: %s",
|
|
envelope.get("error") or envelope.get("message") or envelope)
|
|
return
|
|
except Exception as exc:
|
|
if exc.__class__.__name__ == "ConnectionClosed":
|
|
return
|
|
logger.warning("xAI WS receive failed: %s", exc)
|
|
return
|