Woody 41f59b396f feat: track highlight generation prompt, response, and timing in history (Phase 5.5) ... - Add 3 columns to query_history: highlight_prompt, highlight_response, highlight_time_ms - HistoryService.update_highlights() updates existing row after batch LLM call - ChunkHighlightService measures timing, captures prompt and structured JSON response - SSE completed event includes history_id for frontend to pass back - Frontend captures historyId, passes as ?history_id= query param in batch POST - Highlight time tracked separately (excluded from total_time_ms) - All 153 tests pass (108 backend + 45 frontend)		2026-04-29 11:18:21 +08:00
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__init__.py	feat: Phase 1.1 project setup with config, database, and models	2026-04-22 16:13:52 +08:00
chunk_highlight_service.py	feat: track highlight generation prompt, response, and timing in history (Phase 5.5)	2026-04-29 11:18:21 +08:00
embedding_client.py	feat(backend): add embedding client and update LLM client	2026-04-23 13:26:43 +08:00
highlight_cache.py	feat: add SQLite highlight cache service (Phase 5.4.3)	2026-04-29 09:26:20 +08:00
history_service.py	feat: track highlight generation prompt, response, and timing in history (Phase 5.5)	2026-04-29 11:18:21 +08:00
llm_client.py	feat(llm): log structured LLM response and extra_body	2026-04-28 16:50:26 +08:00
prompt_service.py	feat(prompts): integrate filter_per_subq with PromptService, fix seed bugs, restructure UI	2026-04-27 11:14:27 +08:00
query_decomposer.py	feat: structured LLM output for decompose + citation fuzzy matching (Phase 5)	2026-04-28 15:39:17 +08:00
rag.py	feat: structured LLM output for decompose + citation fuzzy matching (Phase 5)	2026-04-28 15:39:17 +08:00
relevance_filter.py	fix(relevance): tolerate LLM score count mismatches via padding instead of discarding	2026-04-27 14:31:18 +08:00