Phase 9 Commit C. Closes the capture loop: Commit A records what
AtoCore fed the LLM and what came back, Commit B bumps confidence on
active memories the response actually references, and this commit
turns structured cues in the response into candidate memories for a
human review queue.
Nothing extracted here is ever automatically promoted into trusted
state. Every candidate sits at status="candidate" until a human (or
later, a confident automatic policy) calls /memory/{id}/promote or
/memory/{id}/reject. This keeps the "bad memory is worse than no
memory" invariant from the operating model intact.
New module: src/atocore/memory/extractor.py
- MemoryCandidate dataclass (type, content, rule, source_span,
project, confidence, source_interaction_id)
- extract_candidates_from_interaction(interaction): runs a fixed set
of regex rules over the response + response_summary and returns
a list of candidates
V0 rule set (deliberately narrow to keep false positives low):
- decision_heading ## Decision: / ## Decision - / ## Decision —
-> adaptation candidate
- constraint_heading ## Constraint: ... -> project candidate
- requirement_heading ## Requirement: ... -> project candidate
- fact_heading ## Fact: ... -> knowledge candidate
- preference_sentence "I prefer X" / "the user prefers X"
-> preference candidate
- decided_to_sentence "decided to X" -> adaptation candidate
- requirement_sentence "the requirement is X" -> project candidate
Extractor post-processing:
- clean_value: collapse whitespace, strip trailing punctuation
- min content length 8 chars, max 280 (keeps candidates reviewable)
- dedupe by (memory_type, normalized value, rule)
- drop candidates whose content already matches an active memory of
the same type+project so the queue doesn't ask humans to re-curate
things they already promoted
Memory service (extends Commit B candidate-status foundation):
- promote_memory(id): candidate -> active (404 if not a candidate)
- reject_candidate_memory(id): candidate -> invalid
- both are no-ops if the target isn't currently a candidate so the
API can surface 404 without the caller needing to pre-check
API endpoints (new):
- POST /interactions/{id}/extract run extractor, preview-only
body: {"persist": false} (default) returns candidates
{"persist": true} creates candidate memories
- POST /memory/{id}/promote candidate -> active
- POST /memory/{id}/reject candidate -> invalid
- GET /memory?status=candidate list review queue explicitly
(existing endpoint now accepts status= override)
- GET /memory now also returns reference_count and last_referenced_at
per memory so the Commit B reinforcement signal is visible to clients
Trust model unchanged:
- candidates NEVER appear in context packs (get_memories_for_context
still filters to active via the active_only default)
- candidates NEVER get reinforced by the Commit B loop (reinforcement
refuses non-active memories)
- trusted project state is untouched end-to-end
Tests (25 new, all green):
- heading pattern: decision, constraint, requirement, fact
- separator variants :, -, em-dash
- sentence patterns: preference, decided_to, requirement
- rejects too-short matches
- dedupes identical matches
- strips trailing punctuation
- carries project and source_interaction_id onto candidates
- drops candidates that duplicate an existing active memory
- returns empty for prose without structural cues
- candidate and active coexist in the memory table
- promote_memory moves candidate -> active
- promote on non-candidate returns False
- reject_candidate_memory moves candidate -> invalid
- reject on non-candidate returns False
- get_memories(status="candidate") returns just the queue
- POST /interactions/{id}/extract preview-only path
- POST /interactions/{id}/extract persist=true path
- POST /interactions/{id}/extract 404 for missing interaction
- POST /memory/{id}/promote success + 404 on non-candidate
- POST /memory/{id}/reject 404 on missing
- GET /memory?status=candidate surfaces the queue
- GET /memory?status=<invalid> returns 400
Full suite: 160 passing (was 135).
What Phase 9 looks like end to end after this commit
----------------------------------------------------
prompt
-> context pack assembled
-> LLM response
-> POST /interactions (capture)
-> automatic Commit B reinforcement (active memories only)
-> [optional] POST /interactions/{id}/extract
-> Commit C extractor proposes candidates
-> human reviews via GET /memory?status=candidate
-> POST /memory/{id}/promote (candidate -> active)
OR POST /memory/{id}/reject (candidate -> invalid)
Not in this commit (deferred on purpose):
- Decay of unused memories (we keep reference_count and
last_referenced_at so a later decay job has the signal it needs)
- LLM-based extractor as an alternative to the regex rules
- Automatic promotion of high-confidence candidates
- Candidate-to-entity upgrade path (needs the engineering layer
memory-vs-entities decision, planned in a coming architecture doc)
375 lines
13 KiB
Python
375 lines
13 KiB
Python
"""Tests for Phase 9 Commit C rule-based candidate extractor."""
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from fastapi.testclient import TestClient
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from atocore.interactions.service import record_interaction
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from atocore.main import app
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from atocore.memory.extractor import (
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MemoryCandidate,
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extract_candidates_from_interaction,
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)
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from atocore.memory.service import (
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create_memory,
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get_memories,
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promote_memory,
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reject_candidate_memory,
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)
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from atocore.models.database import init_db
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def _capture(**fields):
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return record_interaction(
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prompt=fields.get("prompt", "unused"),
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response=fields.get("response", ""),
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response_summary=fields.get("response_summary", ""),
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project=fields.get("project", ""),
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reinforce=False,
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)
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# --- extractor: heading patterns ------------------------------------------
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def test_extractor_finds_decision_heading(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"We talked about the frame.\n\n"
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"## Decision: switch the lateral supports to GF-PTFE pads\n\n"
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"Rationale: thermal stability."
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),
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1
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assert results[0].memory_type == "adaptation"
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assert "GF-PTFE" in results[0].content
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assert results[0].rule == "decision_heading"
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def test_extractor_finds_constraint_and_requirement_headings(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"### Constraint: total mass must stay under 4.8 kg\n"
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"## Requirement: survives 12g shock in any axis\n"
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),
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)
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results = extract_candidates_from_interaction(interaction)
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rules = {r.rule for r in results}
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assert "constraint_heading" in rules
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assert "requirement_heading" in rules
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constraint = next(r for r in results if r.rule == "constraint_heading")
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requirement = next(r for r in results if r.rule == "requirement_heading")
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assert constraint.memory_type == "project"
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assert requirement.memory_type == "project"
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assert "4.8 kg" in constraint.content
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assert "12g" in requirement.content
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def test_extractor_finds_fact_heading(tmp_data_dir):
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init_db()
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interaction = _capture(
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response="## Fact: the polisher sim uses floating-point deltas in microns\n",
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1
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assert results[0].memory_type == "knowledge"
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assert results[0].rule == "fact_heading"
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def test_extractor_heading_separator_variants(tmp_data_dir):
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"""Decision headings should match with `:`, `-`, or em-dash."""
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init_db()
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for sep in (":", "-", "\u2014"):
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interaction = _capture(
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response=f"## Decision {sep} adopt option B for the mount interface\n",
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1, f"sep={sep!r}"
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assert "option B" in results[0].content
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# --- extractor: sentence patterns -----------------------------------------
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def test_extractor_finds_preference_sentence(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"I prefer rebase-based workflows because history stays linear "
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"and reviewers have an easier time."
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),
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)
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results = extract_candidates_from_interaction(interaction)
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pref_matches = [r for r in results if r.rule == "preference_sentence"]
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assert len(pref_matches) == 1
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assert pref_matches[0].memory_type == "preference"
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assert "rebase" in pref_matches[0].content.lower()
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def test_extractor_finds_decided_to_sentence(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"After going through the options we decided to keep the legacy "
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"calibration routine for the July milestone."
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),
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)
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results = extract_candidates_from_interaction(interaction)
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decision_matches = [r for r in results if r.rule == "decided_to_sentence"]
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assert len(decision_matches) == 1
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assert decision_matches[0].memory_type == "adaptation"
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assert "legacy calibration" in decision_matches[0].content.lower()
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def test_extractor_finds_requirement_sentence(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"One of the findings: the requirement is that the interferometer "
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"must resolve 50 picometer displacements at 1 kHz bandwidth."
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),
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)
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results = extract_candidates_from_interaction(interaction)
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req_matches = [r for r in results if r.rule == "requirement_sentence"]
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assert len(req_matches) == 1
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assert req_matches[0].memory_type == "project"
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assert "picometer" in req_matches[0].content.lower()
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# --- extractor: content rules ---------------------------------------------
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def test_extractor_rejects_too_short_matches(tmp_data_dir):
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init_db()
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interaction = _capture(response="## Decision: yes\n") # too short after clean
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results = extract_candidates_from_interaction(interaction)
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assert results == []
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def test_extractor_deduplicates_identical_matches(tmp_data_dir):
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init_db()
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interaction = _capture(
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response=(
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"## Decision: use the modular frame variant for prototyping\n"
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"## Decision: use the modular frame variant for prototyping\n"
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),
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1
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def test_extractor_strips_trailing_punctuation(tmp_data_dir):
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init_db()
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interaction = _capture(
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response="## Decision: defer the laser redesign to Q3.\n",
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1
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assert results[0].content.endswith("Q3")
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def test_extractor_includes_project_and_source_interaction_id(tmp_data_dir):
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init_db()
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interaction = _capture(
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project="p05-interferometer",
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response="## Decision: freeze the optical path for the prototype run\n",
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)
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results = extract_candidates_from_interaction(interaction)
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assert len(results) == 1
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assert results[0].project == "p05-interferometer"
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assert results[0].source_interaction_id == interaction.id
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def test_extractor_drops_candidates_matching_existing_active(tmp_data_dir):
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init_db()
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# Seed an active memory that the extractor would otherwise re-propose
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create_memory(
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memory_type="preference",
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content="prefers small reviewable diffs",
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)
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interaction = _capture(
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response="Remember that I prefer small reviewable diffs because they merge faster.",
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)
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results = extract_candidates_from_interaction(interaction)
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# The only candidate would have been the preference, now dropped
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assert not any(r.content.lower() == "small reviewable diffs" for r in results)
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def test_extractor_returns_empty_for_no_patterns(tmp_data_dir):
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init_db()
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interaction = _capture(response="Nothing structural here, just prose.")
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results = extract_candidates_from_interaction(interaction)
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assert results == []
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# --- service: candidate lifecycle -----------------------------------------
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def test_candidate_and_active_can_coexist(tmp_data_dir):
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init_db()
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active = create_memory(
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memory_type="preference",
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content="logs every config change to the change log",
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status="active",
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)
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candidate = create_memory(
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memory_type="preference",
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content="logs every config change to the change log",
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status="candidate",
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)
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# The two are distinct rows because status is part of the dedup key
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assert active.id != candidate.id
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def test_promote_memory_moves_candidate_to_active(tmp_data_dir):
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init_db()
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candidate = create_memory(
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memory_type="adaptation",
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content="moved the staging scripts into deploy/staging",
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status="candidate",
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)
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ok = promote_memory(candidate.id)
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assert ok is True
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active_list = get_memories(memory_type="adaptation", status="active")
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assert any(m.id == candidate.id for m in active_list)
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def test_promote_memory_on_non_candidate_returns_false(tmp_data_dir):
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init_db()
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active = create_memory(
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memory_type="adaptation",
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content="already active adaptation entry",
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status="active",
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)
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assert promote_memory(active.id) is False
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def test_reject_candidate_moves_it_to_invalid(tmp_data_dir):
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init_db()
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candidate = create_memory(
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memory_type="knowledge",
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content="the calibration uses barometric pressure compensation",
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status="candidate",
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)
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ok = reject_candidate_memory(candidate.id)
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assert ok is True
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invalid_list = get_memories(memory_type="knowledge", status="invalid")
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assert any(m.id == candidate.id for m in invalid_list)
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def test_reject_on_non_candidate_returns_false(tmp_data_dir):
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init_db()
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active = create_memory(memory_type="preference", content="always uses structured logging")
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assert reject_candidate_memory(active.id) is False
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def test_get_memories_filters_by_candidate_status(tmp_data_dir):
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init_db()
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create_memory(memory_type="preference", content="active one", status="active")
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create_memory(memory_type="preference", content="candidate one", status="candidate")
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create_memory(memory_type="preference", content="another candidate", status="candidate")
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candidates = get_memories(status="candidate", memory_type="preference")
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assert len(candidates) == 2
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assert all(c.status == "candidate" for c in candidates)
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# --- API: extract / promote / reject / list -------------------------------
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def test_api_extract_interaction_without_persist(tmp_data_dir):
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init_db()
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interaction = record_interaction(
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prompt="review",
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response="## Decision: flip the default budget to 4000 for p05\n",
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reinforce=False,
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)
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client = TestClient(app)
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response = client.post(f"/interactions/{interaction.id}/extract", json={})
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assert response.status_code == 200
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body = response.json()
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assert body["candidate_count"] == 1
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assert body["persisted"] is False
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assert body["persisted_ids"] == []
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# The candidate should NOT have been written to the memory table
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queue = get_memories(status="candidate")
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assert queue == []
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def test_api_extract_interaction_with_persist(tmp_data_dir):
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init_db()
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interaction = record_interaction(
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prompt="review",
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response=(
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"## Decision: pin the embedding model to v2.3 for Wave 2\n"
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"## Constraint: context budget must stay under 4000 chars\n"
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),
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reinforce=False,
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)
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client = TestClient(app)
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response = client.post(
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f"/interactions/{interaction.id}/extract", json={"persist": True}
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)
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assert response.status_code == 200
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body = response.json()
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assert body["candidate_count"] == 2
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assert body["persisted"] is True
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assert len(body["persisted_ids"]) == 2
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queue = get_memories(status="candidate", limit=50)
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assert len(queue) == 2
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def test_api_extract_returns_404_for_missing_interaction(tmp_data_dir):
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init_db()
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client = TestClient(app)
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response = client.post("/interactions/nope/extract", json={})
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assert response.status_code == 404
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def test_api_promote_and_reject_endpoints(tmp_data_dir):
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init_db()
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candidate = create_memory(
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memory_type="adaptation",
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content="restructured the ingestion pipeline into layered stages",
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status="candidate",
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)
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client = TestClient(app)
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promote_response = client.post(f"/memory/{candidate.id}/promote")
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assert promote_response.status_code == 200
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assert promote_response.json()["status"] == "promoted"
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# Promoting it again should 404 because it's no longer a candidate
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second_promote = client.post(f"/memory/{candidate.id}/promote")
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assert second_promote.status_code == 404
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reject_response = client.post("/memory/does-not-exist/reject")
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assert reject_response.status_code == 404
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def test_api_get_memory_candidate_status_filter(tmp_data_dir):
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init_db()
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create_memory(memory_type="preference", content="prefers explicit types", status="active")
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create_memory(
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memory_type="preference",
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content="prefers pull requests sized by diff lines not files",
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status="candidate",
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)
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client = TestClient(app)
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response = client.get("/memory", params={"status": "candidate"})
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assert response.status_code == 200
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body = response.json()
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assert "candidate" in body["statuses"]
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assert len(body["memories"]) == 1
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assert body["memories"][0]["status"] == "candidate"
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def test_api_get_memory_invalid_status_returns_400(tmp_data_dir):
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init_db()
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client = TestClient(app)
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response = client.get("/memory", params={"status": "not-a-status"})
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assert response.status_code == 400
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