4ec4054db4
Add interactive article summary feature: user pastes URL → bot asks language/duration/topics → generates audio summary via LLM + ElevenLabs TTS → posts MP3 inline with transcript and follow-up Q&A. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
109 lines
2.9 KiB
Python
109 lines
2.9 KiB
Python
"""ElevenLabs TTS — direct API calls to generate MP3 audio."""
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from __future__ import annotations
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import io
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import logging
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import httpx
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logger = logging.getLogger("article-summary.tts")
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ELEVENLABS_API = "https://api.elevenlabs.io/v1"
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CHUNK_SIZE = 5000 # Max chars per TTS request
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async def generate_audio(
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text: str,
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api_key: str,
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voice_id: str,
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language: str = "en",
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) -> tuple[bytes, float]:
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"""Generate MP3 audio from text via ElevenLabs API.
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Args:
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text: Text to convert to speech.
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api_key: ElevenLabs API key.
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voice_id: ElevenLabs voice ID.
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language: Language code ("en" or "de").
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Returns:
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Tuple of (mp3_bytes, estimated_duration_seconds).
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"""
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chunks = _split_text(text, CHUNK_SIZE)
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mp3_parts: list[bytes] = []
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for i, chunk in enumerate(chunks):
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logger.info("Generating TTS chunk %d/%d (%d chars)", i + 1, len(chunks), len(chunk))
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mp3_data = await _tts_request(chunk, api_key, voice_id, language)
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mp3_parts.append(mp3_data)
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combined = b"".join(mp3_parts)
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# Estimate duration: ~150 words per minute
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word_count = len(text.split())
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est_duration = (word_count / 150) * 60
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logger.info("TTS complete: %d bytes, ~%.0fs estimated", len(combined), est_duration)
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return combined, est_duration
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async def _tts_request(
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text: str,
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api_key: str,
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voice_id: str,
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language: str,
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) -> bytes:
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"""Single TTS API call."""
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url = f"{ELEVENLABS_API}/text-to-speech/{voice_id}"
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headers = {
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"xi-api-key": api_key,
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"Content-Type": "application/json",
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"Accept": "audio/mpeg",
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}
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payload = {
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"text": text,
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"model_id": "eleven_multilingual_v2",
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"voice_settings": {
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"stability": 0.5,
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"similarity_boost": 0.75,
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},
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}
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# Add language hint for non-English
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if language == "de":
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payload["language_code"] = "de"
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async with httpx.AsyncClient(timeout=120.0) as client:
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resp = await client.post(url, json=payload, headers=headers)
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resp.raise_for_status()
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return resp.content
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def _split_text(text: str, max_chars: int) -> list[str]:
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"""Split text at sentence boundaries for TTS chunking."""
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if len(text) <= max_chars:
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return [text]
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chunks: list[str] = []
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current = ""
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for sentence in _sentence_split(text):
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if len(current) + len(sentence) > max_chars and current:
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chunks.append(current.strip())
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current = sentence
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else:
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current += sentence
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if current.strip():
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chunks.append(current.strip())
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return chunks or [text[:max_chars]]
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def _sentence_split(text: str) -> list[str]:
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"""Split text into sentences, keeping delimiters attached."""
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import re
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parts = re.split(r'(?<=[.!?])\s+', text)
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# Re-add trailing space for joining
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return [p + " " for p in parts]
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