feat(qm_query): add VECTOR_DISTANCE_THRESHOLD per Ch 14 Gulli#86
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feat(qm_query): add VECTOR_DISTANCE_THRESHOLD per Ch 14 Gulli#86AdairBear wants to merge 5 commits into
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QuantMind v0.2 ships ingestion + LLM extraction only; its persistence,
embedding, semantic-query, and Data-MCP layers are unbuilt future PRs. This
adds that missing Stage-2 layer as a self-contained package that reuses
QuantMind's own venv and fetch+format layer:
- store.py filesystem CorpusStore (JSON + .npy vectors, stable-hash dedup)
- embed.py OpenAI embeddings + grounded answer synthesis + summarizer
- ingest.py fetch_arxiv/url/local -> markdown -> summarize -> embed -> store
(skips the brittle paper_flow Paper-tree: gpt-4o-mini emits
non-UUID node ids that the Paper schema rejects)
- query.py embed question -> cosine top-k -> grounded, cited answer
- server.py FastMCP stdio server: qm_ingest_arxiv/url/pdf/text, qm_query,
qm_list_corpus, qm_delete_item
- cli.py seeding + shell use; seed_corpus.txt; _smoke_mcp.py handshake test
Secrets load from ~/.hermes/.env; uses VOICE_TOOLS_OPENAI_KEY (real OpenAI)
since Hermes OPENAI_API_KEY is an OpenRouter key with no embeddings endpoint.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Adds `grpo_suitability: high|medium|low` to every corpus entry at ingest time, implementing the weak-vs-strong discrimination-gap framework from Kulikov et al. (FAIR at Meta, arXiv:2606.25996). V1 is a pure deterministic heuristic (no live model calls): - long + arxiv source + code present → high - short + news/unknown source + no code → low - everything else → medium Changes: - qm_mcp/grpo_suitability.py: GrpoSuitabilityScorer with score_entry(), length_band, domain_band, code_present helpers; V2 solver-gap hooks documented as TODOs - qm_mcp/ingest.py: score computed in _persist() and persisted to both items/<id>.json and ingestion_log.jsonl; backward-compatible (existing entries not touched) - qm_mcp/test_grpo_suitability.py: 22 pytest cases covering heuristic correctness, domain-band edge cases, backward compat, idempotency - docs/grpo_suitability.md: framework reference, V1 rule table, V2 plan Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Keeps the coverage floor enforced by CI (scripts/verify.sh) while allowing sub-package test suites (e.g. qm_mcp/) to run standalone without a false failure when quantmind code is not exercised. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds `distance_threshold: float = 0.7` to `qm_query` (MCP tool) and the underlying `query()` function. After vector search, candidates with cosine distance > threshold are filtered out before synthesis and source assembly. When all candidates fail the filter, the function returns an empty sources list and logs a structured INFO message rather than injecting noise chunks into the LLM context. Threshold semantics: cosine_distance = 1 - cosine_similarity; keep if similarity >= (1 - threshold). Default 0.7 preserves backward compatibility for existing callers (CLI, Hermes, Conductor). Tests: qm_mcp/test_distance_threshold.py — 8 cases covering high-quality pass, poor-match filter, all-filtered empty return + log, and threshold override. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Summary
distance_threshold: float = 0.7parameter toqm_queryMCP tool and underlyingquery()inqm_mcp/query.pyPattern
VECTOR_DISTANCE_THRESHOLD (Ch 14, Gulli — Agentic Design Patterns). Threshold semantics:
cosine_distance = 1 - cosine_similarity; keep candidate ifsimilarity >= (1 - threshold).Test plan
pytest qm_mcp/test_distance_threshold.py -v— 8 tests, all greenruff check+ruff format --check— clean🤖 Generated with Claude Code