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Hunyuan Prompt Engineering for Summarization
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Real-time Social Listening Assistant
Format
Text-first
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1
Sections
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Linked challenge
Real-time Social Listening Assistant
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Craft a detailed prompt for the Hunyuan LLM (or your chosen LLM accessed via BentoML) that takes a JSON object representing a friend's activity (e.g., {'user_id': 'friend', 'activity': 'listening', 'details': {'song': '...', 'artist': '...'}}) and generates a concise, friendly summary. The summary should be short enough for real-time updates but informative. Explain how you'd handle varying activity types (e.g., article reading, game playing).Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Hold the task contract and output shape stable so generated implementations remain comparable.
Tune next
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Verify after
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.