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Use GroundRecall query context in learner workbench

This commit is contained in:
welsberr 2026-04-27 11:57:57 -04:00
parent 074999fbe1
commit 35be8a2f39
2 changed files with 103 additions and 5 deletions
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62
src/didactopus/learner_workbench.py
View File

@ -1,5 +1,6 @@
from __future__ import annotations
import json
from pathlib import Path
import yaml
@ -17,6 +18,31 @@ def _load_yaml(path: Path) -> dict:
return yaml.safe_load(path.read_text(encoding="utf-8")) or {}
def _load_groundrecall_summary(pack_dir: Path) -> dict:
path = pack_dir / "groundrecall_query_bundle.json"
if not path.exists():
return {}
payload = json.loads(path.read_text(encoding="utf-8"))
review_candidates = payload.get("review_candidates", []) or []
concept = payload.get("concept", {}) or {}
graph_codes = sorted(
{
code
for item in review_candidates
for code in item.get("finding_codes", []) or []
if "concept" in str(code) or "bridge" in str(code) or "component" in str(code)
}
)
top_rationales = [str(item.get("rationale", "")).strip() for item in review_candidates if str(item.get("rationale", "")).strip()][:3]
return {
"concept_id": concept.get("concept_id", ""),
"concept_title": concept.get("title", ""),
"review_candidate_count": len(review_candidates),
"graph_codes": graph_codes,
"top_rationales": top_rationales,
}
def load_pack_context(pack_id: str) -> dict:
pack_dir = DOMAIN_PACKS / pack_id
if not pack_dir.exists():
@ -24,11 +50,13 @@ def load_pack_context(pack_id: str) -> dict:
pack = _load_yaml(pack_dir / "pack.yaml")
concepts = (_load_yaml(pack_dir / "concepts.yaml")).get("concepts", []) or []
by_id = {concept.get("id"): concept for concept in concepts}
groundrecall = _load_groundrecall_summary(pack_dir)
return {
"pack_dir": pack_dir,
"pack": pack,
"concepts": concepts,
"by_id": by_id,
"groundrecall": groundrecall,
}
@ -56,6 +84,22 @@ def _concept_block(concept: dict, by_id: dict[str, dict]) -> str:
return "\n".join(lines)
def _groundrecall_block(summary: dict) -> str:
if not summary:
return ""
lines = [
"GroundRecall context:",
f"- Query concept: {summary.get('concept_title') or summary.get('concept_id') or 'unknown'}",
f"- Review candidate count: {summary.get('review_candidate_count', 0)}",
]
graph_codes = summary.get("graph_codes", []) or []
if graph_codes:
lines.append(f"- Structural signals: {', '.join(graph_codes)}")
for rationale in summary.get("top_rationales", []) or []:
lines.append(f"- Review cue: {rationale}")
return "\n".join(lines)
def _generate(provider: ModelProvider, *, role: str, prompt: str, temperature: float, max_tokens: int) -> dict:
response = provider.generate(
prompt,
@ -128,6 +172,7 @@ def build_pack_workbench_session(
f"Description: {pack.get('description', '')}\n"
f"Audience level: {pack.get('audience_level', 'novice-friendly')}"
)
groundrecall_block = _groundrecall_block(context.get("groundrecall", {}))
learner_state_block = (
f"Learner goal: {learner_goal}\n"
f"Question: {question}\n"
@ -142,7 +187,9 @@ def build_pack_workbench_session(
role="mentor",
prompt=(
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_concept_block(next_concept, by_id)}\n\n"
f"{_scientific_virtues_block()}\n\n{learner_state_block}\n"
f"{_scientific_virtues_block()}\n\n"
f"{groundrecall_block + chr(10) * 2 if groundrecall_block else ''}"
f"{learner_state_block}\n"
"Respond as Didactopus mentor. Give a short grounded orientation, explain why this concept matters now, "
"and ask one focused question that helps the learner distinguish observation from interpretation."
),
@ -153,7 +200,9 @@ def build_pack_workbench_session(
provider,
role="practice",
prompt=(
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_scientific_virtues_block()}\n\n{learner_state_block}\n"
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_scientific_virtues_block()}\n\n"
f"{groundrecall_block + chr(10) * 2 if groundrecall_block else ''}"
f"{learner_state_block}\n"
"Respond as Didactopus practice designer. Create one compact task that asks for evidence comparison, honest uncertainty, and a revision condition."
),
temperature=0.25,
@ -163,7 +212,9 @@ def build_pack_workbench_session(
provider,
role="evaluator",
prompt=(
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_scientific_virtues_block()}\n\n{learner_state_block}\n"
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_scientific_virtues_block()}\n\n"
f"{groundrecall_block + chr(10) * 2 if groundrecall_block else ''}"
f"{learner_state_block}\n"
"Respond as Didactopus evaluator. Name strengths first, then real gaps, and give one revision target without pretending stated caveats are absent."
),
temperature=0.2,
@ -174,7 +225,9 @@ def build_pack_workbench_session(
role="mentor",
prompt=(
f"{pack_block}\n\n{_concept_block(concept, by_id)}\n\n{_concept_block(next_concept, by_id)}\n\n"
f"{_scientific_virtues_block()}\n\nEvaluator feedback: {evaluator['text']}\n"
f"{_scientific_virtues_block()}\n\n"
f"{groundrecall_block + chr(10) * 2 if groundrecall_block else ''}"
f"Evaluator feedback: {evaluator['text']}\n"
"Respond as Didactopus mentor. Give the next study action and say what new evidence or comparison would most help the learner revise or strengthen the current view."
),
temperature=0.2,
@ -188,6 +241,7 @@ def build_pack_workbench_session(
"concept_title": concept.get("title"),
"next_concept_id": next_concept.get("id"),
"next_concept_title": next_concept.get("title"),
"groundrecall": context.get("groundrecall", {}),
"mentor": mentor,
"practice": practice,
"evaluator": evaluator,

46
tests/test_learner_workbench.py
View File

@ -1,3 +1,7 @@
import json
import shutil
from pathlib import Path
from didactopus import learner_workbench as learner_workbench_module
@ -18,7 +22,7 @@ class _FakeProvider:
"Response",
(),
{
"text": f"{role}: {prompt.splitlines()[0]}",
"text": f"{role}: {' | '.join(prompt.splitlines()[:30])}",
"provider": "fake",
"model_name": "fake-model",
},
@ -45,3 +49,43 @@ def test_build_pack_workbench_session_uses_evidence_trail_pack(monkeypatch) -> N
assert payload["mentor"]["provider"] == "fake"
assert payload["feedback"]["strengths"]
assert payload["feedback"]["gaps"] == []
def test_build_pack_workbench_session_includes_groundrecall_context(monkeypatch, tmp_path: Path) -> None:
monkeypatch.setattr(learner_workbench_module, "ModelProvider", _FakeProvider)
source_pack = learner_workbench_module.DOMAIN_PACKS / "evidence-trail"
copied_root = tmp_path / "domain-packs"
copied_pack = copied_root / "evidence-trail"
shutil.copytree(source_pack, copied_pack)
(copied_pack / "groundrecall_query_bundle.json").write_text(
json.dumps(
{
"bundle_kind": "groundrecall_query_bundle",
"concept": {"concept_id": "concept::question-framing", "title": "Question Framing"},
"review_candidates": [
{
"candidate_id": "concept::question-framing",
"finding_codes": ["bridge_concept"],
"rationale": "Question Framing | lane=conflict_resolution | priority=12 | graph=bridge_concept",
}
],
}
),
encoding="utf-8",
)
monkeypatch.setattr(learner_workbench_module, "DOMAIN_PACKS", copied_root)
payload = learner_workbench_module.build_pack_workbench_session(
pack_id="evidence-trail",
concept_id="question-framing",
learner_goal="Understand how to compare evidence.",
question="Which question should guide the study step?",
observation="The pack starts with question framing.",
interpretation="Question framing organizes the next evidence move.",
uncertainty="I do not yet know which source will best test the interpretation.",
revision_trigger="A stronger source trail could change the current framing.",
)
assert payload["groundrecall"]["review_candidate_count"] == 1
assert payload["groundrecall"]["graph_codes"] == ["bridge_concept"]
assert "GroundRecall context:" in payload["mentor"]["text"]