ducoterra
4971e2859d
Remove the blanket .agent/ gitignore so the phase roadmap, user stories, reports, and PLAN.md are versioned with the code. Only runtime artifacts (.agent/phase-sessions/, .agent/pipeline.log) remain ignored. Update AGENTS.md git protocol rule to match.
79 lines
4.3 KiB
Markdown
79 lines
4.3 KiB
Markdown
# Story: Retrieval Quality — Multi-Format Ingestion + Hybrid Search
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**Phase:** `09_story_retrieval_quality.md` · **E2E:** `tests/e2e/test_retrieval_quality.py`
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## Narrative
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As **a user**, I want to ask questions that name my tools ("How did I
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install gitlab?") and get a grounded answer citing the right document —
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even when the answer lives in a `.yaml`, `.py`, `.json` or `.txt` file —
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so Brain actually covers my notes instead of deflecting around them.
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- **Given** my notes are a mix of markdown write-ups and config/code
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files, and today's index is polluted with vendored-cache docs
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(`.esphome/.espressif/**`, merge-request templates, …) that outrank
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real content, while retrieval is pure cosine top-4
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- **When** the importer covers the full text-format set, skips hidden
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directories, and retrieval fuses vector similarity with Postgres
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full-text search
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- **Then** "How did I install gitlab?" surfaces `active/container_gitlab/
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gitlab.md` as the top document, the junk docs are pruned from the
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index, and genuinely off-topic questions still get the honest
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deflection.
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## Acceptance criteria
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1. **Ingestion scope (A9, revised with owner permission 2026-08-21):**
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default extensions `md, markdown, txt, yaml, yml, json, py`,
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overridable via `BOR_IMPORT_EXTENSIONS`; **hidden (dot) directories
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skipped by default**; the A9 exclusion list stays.
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2. **Format-aware chunking:** md unchanged (heading-aware); yaml/yml
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split on top-level keys and `---` document separators (key kept as
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chunk anchor); json pretty-printed and split on top-level keys; py
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split on top-level defs/classes (stdlib `ast`); txt on paragraphs.
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Every format honors the 1200-char hard cap (aipi ~1024-token request
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cap).
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3. **Hybrid retrieval (A7, revised with owner permission 2026-08-21):**
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cosine top-30 + FTS top-30 (OR tsquery over the question's tokens,
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`ts_rank`-ordered) fused with Reciprocal Rank Fusion (k=60);
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document-level ranking by best fused chunk score; the LLM still
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receives the **full top-2 documents** capped at 24k chars (contract
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preserved).
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4. **Honesty gate (A8, revised with owner permission 2026-08-21):**
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deflect when `best cosine < BOR_RELEVANCE_THRESHOLD` **and** no
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candidate chunk FTS-matches the question; threshold re-tuned for the
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`embed` model's measured 0.41–0.84 score compression (default 0.62,
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documented tuning procedure); `fts_hits` logged per turn and stored in
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`query_log`.
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5. **Live verification:** `scripts/eval_retrieval.py` run against the
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imported KB shows `gitlab.md` as the top document for "How did I
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install gitlab?"; a known off-topic question gates LOW.
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6. **Index hygiene:** after a `--prune` re-import, **zero** documents
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with a dot-prefixed path component exist in `documents`; prune also
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drops docs that no longer match the format filter.
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7. **No regressions:** off-topic deflection (story 04) and grounded
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answers (story 03) still pass their E2E suites in isolation; the E2E
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mock keeps its own threshold calibration via the app fixture.
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8. Unit + integration green, `app/` coverage >90%, story E2E green in
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isolation, one `--no-gpg-sign` commit.
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## UI Visualization & Structure
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No UI change. The Sources page document count drops after the junk prune
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(intended cleanup — noted in the README).
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## Playwright Mapping Rule
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**Test Scenario → `tests/e2e/test_retrieval_quality.py`** (mock LLM, seeded KB):
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1. `test_multiformat_docs_indexed` — fixture tree with `.md`, `.yaml`,
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`.py`, `.json`, `.txt` plus `.hidden/junk.md`: import in-process →
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`/api/docs` lists every non-hidden doc and none of the hidden ones.
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2. `test_named_tool_question_retrieves_right_doc` — "How did I install
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gitlab?" → not deflected, streamed answer, a `.source-chip` containing
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the gitlab doc, `query_log` row `deflected=false` with the gitlab doc
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in sources.
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3. `test_keyword_only_question_beats_vector_ranking` — a question whose
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rare token exists in exactly one fixture doc (weak mock-embedding
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overlap, e.g. "kafkabridge") → grounded answer citing that doc
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(FTS-OR gate + lexical RRF lift, end to end).
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4. `test_off_topic_still_deflects` — "sourdough starter" →
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`.is-deflected` bubble matching /haven't done anything like that/i +
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≥2 "Maybe try:" chips (story 04 behavior under the new gate).
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