- Add expert_cache.py: TTL-based in-memory cache (1 hour default)
- Add expert_source_service.py: WikidataProvider and ConceptNetProvider
- Wikidata SPARQL queries for occupations with Chinese labels
- ConceptNet API queries for occupation-related concepts
- Random selection from cached pool
- Update schemas.py: Add ExpertSource enum (llm/wikidata/conceptnet)
- Update ExpertTransformationRequest with expert_source and expert_language
- Update router: Conditionally use external sources with LLM fallback
- New SSE events: expert_source, expert_fallback
- Update frontend types with ExpertSource
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add random seed and diversity hints to expert generation prompt
- Explicitly avoid common professions (醫生、工程師、教師、律師等)
- Change description generation from batch to one-by-one for reliability
- Increase default temperature from 0.7 to 0.95 for more creative output
- Add description_progress SSE event for real-time feedback
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>