"""Provider-agnostic streaming TTS: sentence text → int16 mono PCM chunk iterator. ``stream_tts_to_speaker`` (``tools.tts_tool``) owns the sentence buffer, sounddevice output and stop/queue protocol; this module owns the *provider* half so playback starts on sentence one. True streamers (``StreamingTTSProvider.stream``) wrap chunked APIs; providers with no chunked API (edge, the default) get per-sentence playback via the sync ``text_to_speech_tool`` path. Adding a streamer is ``@register("name")`` on a subclass; the dispatcher, config gate (``tts..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 logger = logging.getLogger(__name__) # Per-sentence PCM byte cap, mirroring the sync providers' 16 MiB bounded-body invariant. _STREAM_SENTENCE_BYTE_CAP = 16 * 1024 * 1024 def _resolve_key(env_var: str, provider_id: str) -> str: """Provider secret lookup (config > env/.env > credential pool); seam over ``tts_tool._resolve_provider_key``. ALL streaming-provider key lookups go through here — never bare ``get_env_value``.""" try: from tools.tts_tool import _resolve_provider_key return _resolve_provider_key(env_var, provider_id) or "" except Exception: from hermes_cli.config import get_env_value return get_env_value(env_var) or "" def _gemini_key() -> str: return _resolve_key("GEMINI_API_KEY", "gemini") or _resolve_key("GOOGLE_API_KEY", "gemini") # Interruption latch: a barge-in on a spoken reply marks it; the next turn's submit path takes it # and prepends SPEECH_INTERRUPTED_NOTE to the model-bound message (API-call local, never # persisted). 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"].*?", flags=re.DOTALL) class SentenceChunker: """Incremental sentence cutter for LLM token deltas, shared by the speaker pipeline and the speak-stream WebSocket so every surface cuts speech identically. Strips ```` blocks (even split across deltas) and merges fragments shorter than *min_len* into the following sentence.""" 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 "" 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, self.buf = _THINK_BLOCK_RE.sub("", self.buf).strip(), "" return [tail] if tail else [] class StreamingTTSProvider(ABC): """Yields raw int16, little-endian, mono PCM chunks at ``sample_rate`` (built-ins: 24 kHz).""" 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); edge is absent (no chunked-PCM API). _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``. ``tts.streaming.provider`` when set: a name pins that exact streamer (``None`` if unusable); ``auto`` returns the first usable in ``_PROVIDER_PRIORITY``. Otherwise the configured TTS provider (or ``preferred``): ``None`` means "no chunked API" — the dispatcher speaks per-sentence via the sync path, preserving the user's chosen voice. We never silently swap providers just to get streaming.""" pinned = str((tts_config.get("streaming") or {}).get("provider") or "").lower().strip() if pinned == "auto": return next((inst for name in _PROVIDER_PRIORITY if (inst := _try_instantiate(name, tts_config))), None) return _try_instantiate(pinned or (preferred or _get_provider(tts_config)).lower().strip(), tts_config) def _capped(chunks: Iterator[bytes], label: str) -> Iterator[bytes]: """Pass chunks through, aborting past the per-sentence byte cap (runaway/hostile upstream).""" total = 0 for chunk in chunks: total += len(chunk) if total > _STREAM_SENTENCE_BYTE_CAP: logger.warning("%s exceeded %d bytes for one sentence; truncating", label, _STREAM_SENTENCE_BYTE_CAP) return yield chunk @register("elevenlabs") class ElevenLabsStreamer(StreamingTTSProvider): """ElevenLabs chunked HTTP → pcm_24000 (the original reference path).""" @staticmethod def available() -> bool: return bool(_resolve_key("ELEVENLABS_API_KEY", "elevenlabs")) def stream(self, text: str) -> Iterator[bytes]: from tools.tts_tool import _import_elevenlabs from tools.tts_tool_providers import ( DEFAULT_ELEVENLABS_STREAMING_MODEL_ID, DEFAULT_ELEVENLABS_VOICE_ID, _elevenlabs_environment_kwargs, ) client = _import_elevenlabs()( api_key=_resolve_key("ELEVENLABS_API_KEY", "elevenlabs"), **_elevenlabs_environment_kwargs(self.section), ) yield from client.text_to_speech.convert( text=text, 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)), output_format="pcm_24000") def _openai_config_api_key() -> str: """Return ``tts.openai.api_key`` from config.yaml, or empty string.""" try: return (_load_tts_config().get("openai") or {}).get("api_key") or "" except Exception: return "" @register("openai") class OpenAIStreamer(StreamingTTSProvider): """OpenAI speech with ``response_format=pcm`` (24 kHz mono int16).""" @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 from hermes_cli.config import get_env_value 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)) with client.audio.speech.with_streaming_response.create( model=self.section.get("model", "gpt-4o-mini-tts"), voice=self.section.get("voice", "alloy"), input=text, response_format="pcm", ) as response: yield from _capped(response.iter_bytes(), "OpenAI streaming TTS") @register("gemini") class GeminiStreamer(StreamingTTSProvider): """Gemini ``streamGenerateContent?alt=sse`` → SSE feed of base64 PCM chunks (24 kHz), bounded streamed body. Salvaged from PR #47588 (@Cdddo) and rebased onto the post-campaign infrastructure: credentials via the provider-secret resolver, requests (not httpx) with a bounded streamed body, and main's provider ABC. """ @staticmethod def available() -> bool: return bool(_gemini_key()) def stream(self, text: str) -> Iterator[bytes]: import base64 import json as _json import requests from tools.tts_tool_providers import ( DEFAULT_GEMINI_TTS_BASE_URL, DEFAULT_GEMINI_TTS_MODEL, DEFAULT_GEMINI_TTS_VOICE) from hermes_cli.config import get_env_value api_key = _gemini_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 from agent.gemini_native_adapter import normalize_gemini_base_url base_url = normalize_gemini_base_url( self.section.get("base_url") or get_env_value("GEMINI_BASE_URL") or DEFAULT_GEMINI_TTS_BASE_URL ) payload = { "contents": [{"parts": [{"text": text}]}], "generationConfig": { "responseModalities": ["AUDIO"], "speechConfig": {"voiceConfig": {"prebuiltVoiceConfig": {"voiceName": voice}}}}} 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: parts = _json.loads(line[len("data: "):])["candidates"][0]["content"]["parts"] except (ValueError, KeyError, IndexError, TypeError): continue for part in parts: b64 = (part.get("inlineData") or part.get("inline_data") or {}).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 _capped(_sse_chunks(), "Gemini streaming TTS") @register("xai") class XAIStreamer(StreamingTTSProvider): """xAI WebSocket TTS (``wss://api.x.ai/v1/tts``) → binary PCM frames (24 kHz mono int16). Credentials route through ``resolve_xai_http_credentials`` (OAuth or XAI_API_KEY), same as the sync path. ``_collect_async`` bridges the async WS loop to the sync iterator contract (test seam). Salvaged from PR #47588 (@Cdddo): xAI's chunked TTS API is WebSocket-only (``wss://api.x.ai/v1/tts``). """ @staticmethod def available() -> bool: try: from tools.xai_http import resolve_xai_http_credentials return bool(str(resolve_xai_http_credentials().get("api_key") or "").strip()) except Exception: return False def stream(self, text: str) -> Iterator[bytes]: yield from _capped(iter(self._collect_async(text)), "xAI streaming TTS") def _collect_async(self, text: str) -> List[bytes]: import asyncio async def _drain() -> List[bytes]: return [frame async for frame in self._async_frames(text)] return asyncio.run(_drain()) async def _async_frames(self, text: str): import json as _json import websockets from tools.tts_tool_providers import DEFAULT_XAI_VOICE_ID from tools.xai_http import resolve_xai_http_credentials api_key = str(resolve_xai_http_credentials().get("api_key") or "").strip() if not api_key: raise RuntimeError("No xAI credentials for 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 == "error": logger.warning( "xAI WS error envelope: %s", envelope.get("error") or envelope.get("message") or envelope, ) if etype in ("done", "error"): return except Exception as exc: if exc.__class__.__name__ != "ConnectionClosed": logger.warning("xAI WS receive failed: %s", exc) return