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>
69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
"""LLM-powered article summarization with personalization."""
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from __future__ import annotations
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import logging
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from openai import AsyncOpenAI
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logger = logging.getLogger("article-summary.summarizer")
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WORDS_PER_MINUTE = 150 # Clear narration pace
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async def summarize_article(
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content: str,
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language: str,
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duration_minutes: int,
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topics: list[str],
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llm_client: AsyncOpenAI,
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model: str,
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) -> str:
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"""Generate a narrative summary of article content.
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Args:
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content: Article text (max ~15K chars).
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language: Target language ("en" or "de").
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duration_minutes: Target audio duration (5, 10, or 15).
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topics: Focus topics selected by user.
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llm_client: AsyncOpenAI instance (LiteLLM).
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model: Model name to use.
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Returns:
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Summary text ready for TTS.
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"""
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word_target = duration_minutes * WORDS_PER_MINUTE
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lang_name = "German" if language == "de" else "English"
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topics_str = ", ".join(topics) if topics else "all topics"
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system_prompt = f"""You are a professional audio narrator creating a Blinkist-style summary.
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RULES:
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- Write in {lang_name}.
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- Target approximately {word_target} words (for a {duration_minutes}-minute audio).
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- Focus on: {topics_str}.
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- Use a conversational, engaging narrator tone — as if explaining to a curious friend.
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- Structure: brief intro → key insights → practical takeaways → brief conclusion.
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- Use flowing prose, NOT bullet points or lists.
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- Do NOT include any formatting markers, headers, or markdown.
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- Do NOT say "In this article..." — jump straight into the content.
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- Make it sound natural when read aloud."""
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# Truncate very long content
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if len(content) > 12_000:
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content = content[:12_000] + "\n\n[Article continues...]"
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resp = await llm_client.chat.completions.create(
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model=model,
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": f"Summarize this article:\n\n{content}"},
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],
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max_tokens=word_target * 2, # tokens ≈ 1.3x words, with headroom
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temperature=0.7,
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)
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summary = resp.choices[0].message.content.strip()
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logger.info("Generated summary: %d words (target: %d)", len(summary.split()), word_target)
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return summary
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