Apply ZIP update: 135-didactopus-admin-curation-layer.zip [2026-03-14T13:19:17]

pyproject.toml

@@ -5,18 +5,20 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "didactopus"
 version = "0.1.0"
-description = "Didactopus: semantic QA layer for domain packs"
-readme = "README.md"
 requires-python = ">=3.10"
-license = {text = "MIT"}
+dependencies = [
-authors = [{name = "Wesley R. Elsberry"}]
+  "pydantic>=2.7",
-dependencies = ["pydantic>=2.7", "pyyaml>=6.0"]
+  "pyyaml>=6.0",
-
+  "fastapi>=0.115",
-[project.optional-dependencies]
+  "uvicorn>=0.30",
-dev = ["pytest>=8.0", "ruff>=0.6"]
+  "sqlalchemy>=2.0",
+  "psycopg[binary]>=3.1",
+  "passlib[bcrypt]>=1.7",
+  "python-jose[cryptography]>=3.3"
+]
 
 [project.scripts]
-didactopus-review-bridge = "didactopus.review_bridge_server:main"
+didactopus-api = "didactopus.api:main"
 
 [tool.setuptools.packages.find]
 where = ["src"]

src/didactopus/__init__.py

@@ -1 +1 @@
-__version__ = "0.1.0"
+__version__ = '0.1.0'

src/didactopus/api.py

@@ -1,29 +1,22 @@
 from __future__ import annotations
-from fastapi import FastAPI, HTTPException, Header, Depends
+import json
+from fastapi import FastAPI, HTTPException, Header, Depends, BackgroundTasks
 from fastapi.middleware.cors import CORSMiddleware
 import uvicorn
+from .config import load_settings
 from .db import Base, engine
-from .models import (
+from .models import LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState, EvidenceEvent, EvaluatorSubmission, EvaluatorJobStatus, CreatePackRequest
-    LoginRequest, TokenPair, KnowledgeCandidateCreate, KnowledgeCandidateUpdate,
+from .repository import authenticate_user, get_user_by_id, store_refresh_token, refresh_token_active, revoke_refresh_token, list_packs, list_pack_admin_rows, get_pack, get_pack_validation, get_pack_provenance, upsert_pack, set_pack_publication, create_learner, list_learners_for_user, learner_owned_by_user, load_learner_state, save_learner_state, create_evaluator_job, get_evaluator_job, list_evaluator_jobs_for_learner
-    ReviewCreate, PromoteRequest, SynthesisRunRequest, SynthesisPromoteRequest,
+from .engine import apply_evidence, recommend_next
-    CreateLearnerRequest
-)
-from .repository import (
-    authenticate_user, get_user_by_id, create_learner, learner_owned_by_user,
-    create_candidate, list_candidates, get_candidate, update_candidate,
-    create_review, list_reviews, create_promotion, list_promotions,
-    list_synthesis_candidates, get_synthesis_candidate
-)
 from .auth import issue_access_token, issue_refresh_token, decode_token, new_token_id
-from .synthesis import generate_synthesis_candidates
+from .worker import process_job
 
+settings = load_settings()
 Base.metadata.create_all(bind=engine)
 
-app = FastAPI(title="Didactopus Review Workbench API")
+app = FastAPI(title="Didactopus API Prototype")
 app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
 
-_refresh_tokens = {}
-
 def current_user(authorization: str = Header(default="")):
     token = authorization.removeprefix("Bearer ").strip()
     payload = decode_token(token) if token else None
@@ -34,117 +27,134 @@ def current_user(authorization: str = Header(default="")):
         raise HTTPException(status_code=401, detail="Unauthorized")
     return user
 
-def require_reviewer(user = Depends(current_user)):
+def require_admin(user = Depends(current_user)):
-    if user.role not in {"admin", "reviewer"}:
+    if user.role != "admin":
-        raise HTTPException(status_code=403, detail="Reviewer role required")
+        raise HTTPException(status_code=403, detail="Admin role required")
     return user
 
+def ensure_learner_access(user, learner_id: str):
+    if user.role == "admin":
+        return
+    if not learner_owned_by_user(user.id, learner_id):
+        raise HTTPException(status_code=403, detail="Learner not accessible by this user")
+
 @app.post("/api/login", response_model=TokenPair)
 def login(payload: LoginRequest):
     user = authenticate_user(payload.username, payload.password)
     if user is None:
         raise HTTPException(status_code=401, detail="Invalid credentials")
     token_id = new_token_id()
-    _refresh_tokens[token_id] = user.id
+    store_refresh_token(user.id, token_id)
-    return TokenPair(
+    return TokenPair(access_token=issue_access_token(user.id, user.username, user.role), refresh_token=issue_refresh_token(user.id, user.username, user.role, token_id), username=user.username, role=user.role)
-        access_token=issue_access_token(user.id, user.username, user.role),
+
-        refresh_token=issue_refresh_token(user.id, user.username, user.role, token_id),
+@app.post("/api/refresh", response_model=TokenPair)
-        username=user.username,
+def refresh(payload: RefreshRequest):
-        role=user.role
+    data = decode_token(payload.refresh_token)
-    )
+    if not data or data.get("kind") != "refresh":
+        raise HTTPException(status_code=401, detail="Invalid refresh token")
+    token_id = data.get("jti")
+    if not token_id or not refresh_token_active(token_id):
+        raise HTTPException(status_code=401, detail="Refresh token inactive")
+    user = get_user_by_id(int(data["sub"]))
+    if user is None:
+        raise HTTPException(status_code=401, detail="User not found")
+    revoke_refresh_token(token_id)
+    new_jti = new_token_id()
+    store_refresh_token(user.id, new_jti)
+    return TokenPair(access_token=issue_access_token(user.id, user.username, user.role), refresh_token=issue_refresh_token(user.id, user.username, user.role, new_jti), username=user.username, role=user.role)
+
+@app.get("/api/packs")
+def api_list_packs(user = Depends(current_user)):
+    return [p.model_dump() for p in list_packs(include_unpublished=(user.role == "admin"))]
+
+@app.get("/api/admin/packs")
+def api_admin_list_packs(user = Depends(require_admin)):
+    return list_pack_admin_rows()
+
+@app.get("/api/admin/packs/{pack_id}/validation")
+def api_admin_pack_validation(pack_id: str, user = Depends(require_admin)):
+    return get_pack_validation(pack_id)
+
+@app.get("/api/admin/packs/{pack_id}/provenance")
+def api_admin_pack_provenance(pack_id: str, user = Depends(require_admin)):
+    return get_pack_provenance(pack_id)
+
+@app.post("/api/admin/packs")
+def api_upsert_pack(payload: CreatePackRequest, user = Depends(require_admin)):
+    upsert_pack(payload.pack, is_published=payload.is_published)
+    return {"ok": True, "pack_id": payload.pack.id}
+
+@app.post("/api/admin/packs/{pack_id}/publish")
+def api_publish_pack(pack_id: str, is_published: bool, user = Depends(require_admin)):
+    ok = set_pack_publication(pack_id, is_published)
+    if not ok:
+        raise HTTPException(status_code=404, detail="Pack not found")
+    return {"ok": True, "pack_id": pack_id, "is_published": is_published}
 
 @app.post("/api/learners")
 def api_create_learner(payload: CreateLearnerRequest, user = Depends(current_user)):
     create_learner(user.id, payload.learner_id, payload.display_name)
     return {"ok": True, "learner_id": payload.learner_id}
 
-@app.post("/api/knowledge-candidates")
+@app.get("/api/learners")
-def api_create_candidate(payload: KnowledgeCandidateCreate, reviewer = Depends(require_reviewer)):
+def api_list_learners(user = Depends(current_user)):
-    candidate_id = create_candidate(payload)
+    return list_learners_for_user(user.id, is_admin=(user.role == "admin"))
-    return {"candidate_id": candidate_id}
 
-@app.get("/api/knowledge-candidates")
+@app.get("/api/learners/{learner_id}/state")
-def api_list_candidates(reviewer = Depends(require_reviewer)):
+def api_get_learner_state(learner_id: str, user = Depends(current_user)):
-    return list_candidates()
+    ensure_learner_access(user, learner_id)
+    return load_learner_state(learner_id).model_dump()
 
-@app.get("/api/knowledge-candidates/{candidate_id}")
+@app.put("/api/learners/{learner_id}/state")
-def api_get_candidate(candidate_id: int, reviewer = Depends(require_reviewer)):
+def api_put_learner_state(learner_id: str, state: LearnerState, user = Depends(current_user)):
-    row = get_candidate(candidate_id)
+    ensure_learner_access(user, learner_id)
-    if row is None:
+    if learner_id != state.learner_id:
-        raise HTTPException(status_code=404, detail="Candidate not found")
+        raise HTTPException(status_code=400, detail="Learner ID mismatch")
-    return row
+    return save_learner_state(state).model_dump()
 
-@app.post("/api/knowledge-candidates/{candidate_id}/update")
+@app.post("/api/learners/{learner_id}/evidence")
-def api_update_candidate(candidate_id: int, payload: KnowledgeCandidateUpdate, reviewer = Depends(require_reviewer)):
+def api_post_evidence(learner_id: str, event: EvidenceEvent, user = Depends(current_user)):
-    row = update_candidate(candidate_id, triage_lane=payload.triage_lane, current_status=payload.current_status)
+    ensure_learner_access(user, learner_id)
-    if row is None:
+    state = load_learner_state(learner_id)
-        raise HTTPException(status_code=404, detail="Candidate not found")
+    state = apply_evidence(state, event)
-    return {"candidate_id": row.id, "triage_lane": row.triage_lane, "current_status": row.current_status}
+    save_learner_state(state)
+    return state.model_dump()
 
-@app.post("/api/knowledge-candidates/{candidate_id}/reviews")
+@app.get("/api/learners/{learner_id}/recommendations/{pack_id}")
-def api_create_review(candidate_id: int, payload: ReviewCreate, reviewer = Depends(require_reviewer)):
+def api_get_recommendations(learner_id: str, pack_id: str, user = Depends(current_user)):
-    if get_candidate(candidate_id) is None:
+    ensure_learner_access(user, learner_id)
-        raise HTTPException(status_code=404, detail="Candidate not found")
+    state = load_learner_state(learner_id)
-    review_id = create_review(candidate_id, reviewer.id, payload)
+    pack = get_pack(pack_id)
-    return {"review_id": review_id}
+    if pack is None:
+        raise HTTPException(status_code=404, detail="Pack not found")
+    return {"cards": recommend_next(state, pack)}
 
-@app.get("/api/knowledge-candidates/{candidate_id}/reviews")
+@app.post("/api/learners/{learner_id}/evaluator-jobs", response_model=EvaluatorJobStatus)
-def api_list_reviews(candidate_id: int, reviewer = Depends(require_reviewer)):
+def api_submit_evaluator_job(learner_id: str, payload: EvaluatorSubmission, background_tasks: BackgroundTasks, user = Depends(current_user)):
-    return list_reviews(candidate_id)
+    ensure_learner_access(user, learner_id)
+    job_id = create_evaluator_job(learner_id, payload.pack_id, payload.concept_id, payload.submitted_text)
+    background_tasks.add_task(process_job, job_id)
+    return EvaluatorJobStatus(job_id=job_id, status="queued")
 
-@app.post("/api/knowledge-candidates/{candidate_id}/promote")
+@app.get("/api/evaluator-jobs/{job_id}", response_model=EvaluatorJobStatus)
-def api_promote_candidate(candidate_id: int, payload: PromoteRequest, reviewer = Depends(require_reviewer)):
+def api_get_evaluator_job(job_id: int, user = Depends(current_user)):
-    if get_candidate(candidate_id) is None:
+    job = get_evaluator_job(job_id)
-        raise HTTPException(status_code=404, detail="Candidate not found")
+    if job is None:
-    promotion_id = create_promotion(candidate_id, reviewer.id, payload)
+        raise HTTPException(status_code=404, detail="Job not found")
-    return {"promotion_id": promotion_id}
+    return EvaluatorJobStatus(job_id=job.id, status=job.status, result_score=job.result_score, result_confidence_hint=job.result_confidence_hint, result_notes=job.result_notes)
 
-@app.get("/api/promotions")
+@app.get("/api/evaluator-jobs/{job_id}/trace")
-def api_list_promotions(reviewer = Depends(require_reviewer)):
+def api_get_evaluator_job_trace(job_id: int, user = Depends(current_user)):
-    return list_promotions()
+    job = get_evaluator_job(job_id)
+    if job is None:
+        raise HTTPException(status_code=404, detail="Job not found")
+    return json.loads(job.trace_json or "{}")
 
-@app.post("/api/synthesis/run")
+@app.get("/api/learners/{learner_id}/evaluator-history")
-def api_run_synthesis(payload: SynthesisRunRequest, reviewer = Depends(require_reviewer)):
+def api_get_evaluator_history(learner_id: str, user = Depends(current_user)):
-    created = generate_synthesis_candidates(payload.source_pack_id, payload.target_pack_id, payload.limit)
+    ensure_learner_access(user, learner_id)
-    return {"created_count": len(created), "synthesis_ids": created}
+    jobs = list_evaluator_jobs_for_learner(learner_id)
-
+    return [{"job_id": j.id, "status": j.status, "concept_id": j.concept_id, "result_score": j.result_score, "result_confidence_hint": j.result_confidence_hint, "result_notes": j.result_notes} for j in jobs]
-@app.get("/api/synthesis/candidates")
-def api_list_synthesis(reviewer = Depends(require_reviewer)):
-    return list_synthesis_candidates()
-
-@app.get("/api/synthesis/candidates/{synthesis_id}")
-def api_get_synthesis(synthesis_id: int, reviewer = Depends(require_reviewer)):
-    row = get_synthesis_candidate(synthesis_id)
-    if row is None:
-        raise HTTPException(status_code=404, detail="Synthesis candidate not found")
-    return row
-
-@app.post("/api/synthesis/candidates/{synthesis_id}/promote")
-def api_promote_synthesis(synthesis_id: int, payload: SynthesisPromoteRequest, reviewer = Depends(require_reviewer)):
-    syn = get_synthesis_candidate(synthesis_id)
-    if syn is None:
-        raise HTTPException(status_code=404, detail="Synthesis candidate not found")
-    candidate_id = create_candidate(KnowledgeCandidateCreate(
-        source_type="synthesis_engine",
-        source_artifact_id=None,
-        learner_id="system",
-        pack_id=syn["source_pack_id"],
-        candidate_kind="synthesis_proposal",
-        title=f"Synthesis: {syn['source_concept_id']} ↔ {syn['target_concept_id']}",
-        summary=syn["explanation"],
-        structured_payload=syn,
-        evidence_summary="Promoted from synthesis engine candidate",
-        confidence_hint=syn["score_total"],
-        novelty_score=syn["evidence"].get("novelty", 0.0),
-        synthesis_score=syn["score_total"],
-        triage_lane=payload.promotion_target,
-    ))
-    promotion_id = create_promotion(candidate_id, reviewer.id, PromoteRequest(
-        promotion_target=payload.promotion_target,
-        target_object_id="",
-        promotion_status="approved",
-    ))
-    return {"candidate_id": candidate_id, "promotion_id": promotion_id}
 
 def main():
-    uvicorn.run(app, host="127.0.0.1", port=8011)
+    uvicorn.run(app, host=settings.host, port=settings.port)

src/didactopus/config.py

@@ -1,22 +1,13 @@
-from pathlib import Path
+from __future__ import annotations
-from pydantic import BaseModel, Field
+import os
-import yaml
+from pydantic import BaseModel
 
-class ReviewConfig(BaseModel):
+class Settings(BaseModel):
-    default_reviewer: str = "Unknown Reviewer"
+    database_url: str = os.getenv("DIDACTOPUS_DATABASE_URL", "postgresql+psycopg://didactopus:didactopus-dev-password@localhost:5432/didactopus")
-    write_promoted_pack: bool = True
+    host: str = os.getenv("DIDACTOPUS_HOST", "127.0.0.1")
+    port: int = int(os.getenv("DIDACTOPUS_PORT", "8011"))
+    jwt_secret: str = os.getenv("DIDACTOPUS_JWT_SECRET", "change-me")
+    jwt_algorithm: str = "HS256"
 
-class BridgeConfig(BaseModel):
+def load_settings() -> Settings:
-    host: str = "127.0.0.1"
+    return Settings()
-    port: int = 8765
-    registry_path: str = "workspace_registry.json"
-    default_workspace_root: str = "workspaces"
-
-class AppConfig(BaseModel):
-    review: ReviewConfig = Field(default_factory=ReviewConfig)
-    bridge: BridgeConfig = Field(default_factory=BridgeConfig)
-
-def load_config(path: str | Path) -> AppConfig:
-    with open(path, "r", encoding="utf-8") as handle:
-        data = yaml.safe_load(handle) or {}
-    return AppConfig.model_validate(data)

src/didactopus/engine.py

@@ -1,110 +1,59 @@
 from __future__ import annotations
-from collections import defaultdict
+from .models import LearnerState, EvidenceEvent, MasteryRecord, PackData
-from .models import LearnerState, PackData
 
-def concept_depths(pack: PackData) -> dict[str, int]:
+def get_record(state: LearnerState, concept_id: str, dimension: str = "mastery") -> MasteryRecord | None:
-    concept_map = {c.id: c for c in pack.concepts}
+    for rec in state.records:
-    memo = {}
+        if rec.concept_id == concept_id and rec.dimension == dimension:
-    def depth(cid: str) -> int:
+            return rec
-        if cid in memo:
+    return None
-            return memo[cid]
-        c = concept_map[cid]
-        if not c.prerequisites:
-            memo[cid] = 0
-        else:
-            memo[cid] = 1 + max(depth(pid) for pid in c.prerequisites if pid in concept_map)
-        return memo[cid]
-    for cid in concept_map:
-        depth(cid)
-    return memo
 
-def stable_layout(pack: PackData, width: int = 900, height: int = 520):
+def apply_evidence(state: LearnerState, event: EvidenceEvent, decay: float = 0.05, reinforcement: float = 0.25) -> LearnerState:
-    depths = concept_depths(pack)
+    rec = get_record(state, event.concept_id, event.dimension)
-    layers = defaultdict(list)
+    if rec is None:
-    for c in pack.concepts:
+        rec = MasteryRecord(concept_id=event.concept_id, dimension=event.dimension, score=0.0, confidence=0.0, evidence_count=0, last_updated=event.timestamp)
-        layers[depths.get(c.id, 0)].append(c)
+        state.records.append(rec)
-    positions = {}
+    weight = max(0.05, min(1.0, event.confidence_hint))
-    max_depth = max(layers.keys()) if layers else 0
+    rec.score = ((rec.score * rec.evidence_count) + (event.score * weight)) / max(1, rec.evidence_count + 1)
-    for d in sorted(layers):
+    rec.confidence = min(1.0, max(0.0, rec.confidence * (1.0 - decay) + reinforcement * weight + 0.10 * max(0.0, min(1.0, event.score))))
-        nodes = sorted(layers[d], key=lambda c: c.id)
+    rec.evidence_count += 1
-        y = 90 + d * ((height - 160) / max(1, max_depth))
+    rec.last_updated = event.timestamp
-        for idx, node in enumerate(nodes):
+    state.history.append(event)
-            if node.position is not None:
+    return state
-                positions[node.id] = {"x": node.position.x, "y": node.position.y, "source": "pack_authored"}
-            else:
-                spacing = width / (len(nodes) + 1)
-                x = spacing * (idx + 1)
-                positions[node.id] = {"x": x, "y": y, "source": "auto_layered"}
-    return positions
 
-def prereqs_satisfied(scores: dict[str, float], concept, min_score: float = 0.65) -> bool:
+def prereqs_satisfied(state: LearnerState, concept, min_score: float = 0.65, min_confidence: float = 0.45) -> bool:
     for pid in concept.prerequisites:
-        if scores.get(pid, 0.0) < min_score:
+        rec = get_record(state, pid, concept.masteryDimension)
+        if rec is None or rec.score < min_score or rec.confidence < min_confidence:
             return False
     return True
 
-def concept_status(scores: dict[str, float], concept, min_score: float = 0.65) -> str:
+def concept_status(state: LearnerState, concept, min_score: float = 0.65, min_confidence: float = 0.45) -> str:
-    score = scores.get(concept.id, 0.0)
+    rec = get_record(state, concept.id, concept.masteryDimension)
-    if score >= min_score:
+    if rec and rec.score >= min_score and rec.confidence >= min_confidence:
         return "mastered"
-    if prereqs_satisfied(scores, concept, min_score):
+    if prereqs_satisfied(state, concept, min_score, min_confidence):
-        return "active" if score > 0 else "available"
+        return "active" if rec else "available"
     return "locked"
 
-def build_graph_frames(state: LearnerState, pack: PackData):
+def recommend_next(state: LearnerState, pack: PackData) -> list[dict]:
-    concepts = {c.id: c for c in pack.concepts}
+    cards = []
-    layout = stable_layout(pack)
+    for concept in pack.concepts:
-    scores = {c.id: 0.0 for c in pack.concepts}
+        status = concept_status(state, concept)
-    frames = []
+        rec = get_record(state, concept.id, concept.masteryDimension)
-    history = sorted(state.history, key=lambda x: x.timestamp)
+        if status in {"available", "active"}:
-    static_edges = [{"source": pre, "target": c.id, "kind": "prerequisite"} for c in pack.concepts for pre in c.prerequisites]
+            cards.append({
-    static_cross = [{
+                "id": concept.id,
-        "source": c.id,
+                "title": f"Work on {concept.title}",
-        "target_pack_id": link.target_pack_id,
+                "minutes": 15 if status == "available" else 10,
-        "target_concept_id": link.target_concept_id,
+                "reason": "Prerequisites are satisfied, so this is the best next unlock." if status == "available" else "You have started this concept, but mastery is not yet secure.",
-        "relationship": link.relationship,
+                "why": [
-        "kind": "cross_pack"
+                    "Prerequisite check passed",
-    } for c in pack.concepts for link in c.cross_pack_links]
+                    f"Current score: {rec.score:.2f}" if rec else "No evidence recorded yet",
-    for idx, ev in enumerate(history):
+                    f"Current confidence: {rec.confidence:.2f}" if rec else "Confidence starts after your first exercise",
-        if ev.concept_id in scores:
+                ],
-            scores[ev.concept_id] = ev.score
+                "reward": concept.exerciseReward or f"{concept.title} progress recorded",
-        nodes = []
+                "conceptId": concept.id,
-        for cid, concept in concepts.items():
+                "scoreHint": 0.82 if status == "available" else 0.76,
-            score = scores.get(cid, 0.0)
+                "confidenceHint": 0.72 if status == "available" else 0.55,
-            status = concept_status(scores, concept)
-            pos = layout[cid]
-            nodes.append({
-                "id": cid,
-                "title": concept.title,
-                "score": score,
-                "status": status,
-                "size": 20 + int(score * 30),
-                "x": pos["x"],
-                "y": pos["y"],
-                "layout_source": pos["source"],
             })
-        frames.append({
+    return cards[:4]
-            "index": idx,
-            "timestamp": ev.timestamp,
-            "event_kind": ev.kind,
-            "focus_concept_id": ev.concept_id,
-            "nodes": nodes,
-            "edges": static_edges,
-            "cross_pack_links": static_cross,
-        })
-    if not frames:
-        nodes = []
-        for c in pack.concepts:
-            pos = layout[c.id]
-            nodes.append({
-                "id": c.id,
-                "title": c.title,
-                "score": 0.0,
-                "status": "available" if not c.prerequisites else "locked",
-                "size": 20,
-                "x": pos["x"],
-                "y": pos["y"],
-                "layout_source": pos["source"],
-            })
-        frames.append({"index": 0, "timestamp": "", "event_kind": "empty", "focus_concept_id": "", "nodes": nodes, "edges": static_edges, "cross_pack_links": static_cross})
-    return frames

src/didactopus/models.py

@@ -1,9 +1,8 @@
 from __future__ import annotations
 from pydantic import BaseModel, Field
+from typing import Literal
 
-class LoginRequest(BaseModel):
+EvidenceKind = Literal["checkpoint", "project", "exercise", "review"]
-    username: str
-    password: str
 
 class TokenPair(BaseModel):
     access_token: str
@@ -12,43 +11,39 @@ class TokenPair(BaseModel):
     username: str
     role: str
 
-class KnowledgeCandidateCreate(BaseModel):
+class LoginRequest(BaseModel):
-    source_type: str = "learner_export"
+    username: str
-    source_artifact_id: int | None = None
+    password: str
-    learner_id: str
+
-    pack_id: str
+class RefreshRequest(BaseModel):
-    candidate_kind: str
+    refresh_token: str
+
+class PackConcept(BaseModel):
+    id: str
     title: str
-    summary: str = ""
+    prerequisites: list[str] = Field(default_factory=list)
-    structured_payload: dict = Field(default_factory=dict)
+    masteryDimension: str = "mastery"
-    evidence_summary: str = ""
+    exerciseReward: str = ""
-    confidence_hint: float = 0.0
-    novelty_score: float = 0.0
-    synthesis_score: float = 0.0
-    triage_lane: str = "archive"
 
-class KnowledgeCandidateUpdate(BaseModel):
+class PackCompliance(BaseModel):
-    triage_lane: str | None = None
+    sources: int = 0
-    current_status: str | None = None
+    attributionRequired: bool = False
+    shareAlikeRequired: bool = False
+    noncommercialOnly: bool = False
+    flags: list[str] = Field(default_factory=list)
 
-class ReviewCreate(BaseModel):
+class PackData(BaseModel):
-    review_kind: str = "human_review"
+    id: str
-    verdict: str
+    title: str
-    rationale: str = ""
+    subtitle: str = ""
-    requested_changes: str = ""
+    level: str = "novice-friendly"
+    concepts: list[PackConcept] = Field(default_factory=list)
+    onboarding: dict = Field(default_factory=dict)
+    compliance: PackCompliance = Field(default_factory=PackCompliance)
 
-class PromoteRequest(BaseModel):
+class CreatePackRequest(BaseModel):
-    promotion_target: str
+    pack: PackData
-    target_object_id: str = ""
+    is_published: bool = True
-    promotion_status: str = "approved"
-
-class SynthesisRunRequest(BaseModel):
-    source_pack_id: str | None = None
-    target_pack_id: str | None = None
-    limit: int = 20
-
-class SynthesisPromoteRequest(BaseModel):
-    promotion_target: str = "pack_improvement"
 
 class CreateLearnerRequest(BaseModel):
     learner_id: str
@@ -62,6 +57,29 @@ class MasteryRecord(BaseModel):
     evidence_count: int = 0
     last_updated: str = ""
 
+class EvidenceEvent(BaseModel):
+    concept_id: str
+    dimension: str
+    score: float
+    confidence_hint: float = 0.5
+    timestamp: str
+    kind: EvidenceKind = "exercise"
+    source_id: str = ""
+
 class LearnerState(BaseModel):
     learner_id: str
     records: list[MasteryRecord] = Field(default_factory=list)
+    history: list[EvidenceEvent] = Field(default_factory=list)
+
+class EvaluatorSubmission(BaseModel):
+    pack_id: str
+    concept_id: str
+    submitted_text: str
+    kind: str = "checkpoint"
+
+class EvaluatorJobStatus(BaseModel):
+    job_id: int
+    status: str
+    result_score: float | None = None
+    result_confidence_hint: float | None = None
+    result_notes: str = ""

src/didactopus/orm.py

@@ -10,16 +10,23 @@ class UserORM(Base):
     role: Mapped[str] = mapped_column(String(50), default="learner")
     is_active: Mapped[bool] = mapped_column(Boolean, default=True)
 
+class RefreshTokenORM(Base):
+    __tablename__ = "refresh_tokens"
+    id: Mapped[int] = mapped_column(Integer, primary_key=True)
+    user_id: Mapped[int] = mapped_column(ForeignKey("users.id"), index=True)
+    token_id: Mapped[str] = mapped_column(String(255), unique=True, index=True)
+    is_revoked: Mapped[bool] = mapped_column(Boolean, default=False)
+
 class PackORM(Base):
     __tablename__ = "packs"
     id: Mapped[str] = mapped_column(String(100), primary_key=True)
-    owner_user_id: Mapped[int | None] = mapped_column(ForeignKey("users.id"), nullable=True)
-    policy_lane: Mapped[str] = mapped_column(String(50), default="personal")
     title: Mapped[str] = mapped_column(String(255))
     subtitle: Mapped[str] = mapped_column(Text, default="")
     level: Mapped[str] = mapped_column(String(100), default="novice-friendly")
     data_json: Mapped[str] = mapped_column(Text)
-    is_published: Mapped[bool] = mapped_column(Boolean, default=False)
+    validation_json: Mapped[str] = mapped_column(Text, default="{}")
+    provenance_json: Mapped[str] = mapped_column(Text, default="{}")
+    is_published: Mapped[bool] = mapped_column(Boolean, default=True)
 
 class LearnerORM(Base):
     __tablename__ = "learners"
@@ -38,60 +45,27 @@ class MasteryRecordORM(Base):
     evidence_count: Mapped[int] = mapped_column(Integer, default=0)
     last_updated: Mapped[str] = mapped_column(String(100), default="")
 
-class KnowledgeCandidateORM(Base):
+class EvidenceEventORM(Base):
-    __tablename__ = "knowledge_candidates"
+    __tablename__ = "evidence_events"
     id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    source_type: Mapped[str] = mapped_column(String(50), default="learner_export")
+    learner_id: Mapped[str] = mapped_column(ForeignKey("learners.id"), index=True)
-    source_artifact_id: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    concept_id: Mapped[str] = mapped_column(String(100), index=True)
-    learner_id: Mapped[str] = mapped_column(String(100), index=True)
+    dimension: Mapped[str] = mapped_column(String(100), default="mastery")
-    pack_id: Mapped[str] = mapped_column(String(100), index=True)
+    score: Mapped[float] = mapped_column(Float, default=0.0)
-    candidate_kind: Mapped[str] = mapped_column(String(100), index=True)
+    confidence_hint: Mapped[float] = mapped_column(Float, default=0.5)
-    title: Mapped[str] = mapped_column(String(255))
+    timestamp: Mapped[str] = mapped_column(String(100), default="")
-    summary: Mapped[str] = mapped_column(Text, default="")
+    kind: Mapped[str] = mapped_column(String(50), default="exercise")
-    structured_payload_json: Mapped[str] = mapped_column(Text, default="{}")
+    source_id: Mapped[str] = mapped_column(String(255), default="")
-    evidence_summary: Mapped[str] = mapped_column(Text, default="")
-    confidence_hint: Mapped[float] = mapped_column(Float, default=0.0)
-    novelty_score: Mapped[float] = mapped_column(Float, default=0.0)
-    synthesis_score: Mapped[float] = mapped_column(Float, default=0.0)
-    triage_lane: Mapped[str] = mapped_column(String(50), default="archive")
-    current_status: Mapped[str] = mapped_column(String(50), default="captured")
-    created_at: Mapped[str] = mapped_column(String(100), default="")
 
-class ReviewRecordORM(Base):
+class EvaluatorJobORM(Base):
-    __tablename__ = "review_records"
+    __tablename__ = "evaluator_jobs"
     id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    candidate_id: Mapped[int] = mapped_column(ForeignKey("knowledge_candidates.id"), index=True)
+    learner_id: Mapped[str] = mapped_column(ForeignKey("learners.id"), index=True)
-    reviewer_id: Mapped[int] = mapped_column(ForeignKey("users.id"), index=True)
+    pack_id: Mapped[str] = mapped_column(ForeignKey("packs.id"), index=True)
-    review_kind: Mapped[str] = mapped_column(String(50), default="human_review")
+    concept_id: Mapped[str] = mapped_column(String(100), index=True)
-    verdict: Mapped[str] = mapped_column(String(100), default="")
+    submitted_text: Mapped[str] = mapped_column(Text, default="")
-    rationale: Mapped[str] = mapped_column(Text, default="")
+    status: Mapped[str] = mapped_column(String(50), default="queued")
-    requested_changes: Mapped[str] = mapped_column(Text, default="")
+    result_score: Mapped[float | None] = mapped_column(Float, nullable=True)
-    created_at: Mapped[str] = mapped_column(String(100), default="")
+    result_confidence_hint: Mapped[float | None] = mapped_column(Float, nullable=True)
-
+    result_notes: Mapped[str] = mapped_column(Text, default="")
-class PromotionRecordORM(Base):
+    trace_json: Mapped[str] = mapped_column(Text, default="{}")
-    __tablename__ = "promotion_records"
-    id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    candidate_id: Mapped[int] = mapped_column(ForeignKey("knowledge_candidates.id"), index=True)
-    promotion_target: Mapped[str] = mapped_column(String(50), index=True)
-    target_object_id: Mapped[str] = mapped_column(String(100), default="")
-    promotion_status: Mapped[str] = mapped_column(String(50), default="draft")
-    promoted_by: Mapped[int] = mapped_column(ForeignKey("users.id"), index=True)
-    created_at: Mapped[str] = mapped_column(String(100), default="")
-
-class SynthesisCandidateORM(Base):
-    __tablename__ = "synthesis_candidates"
-    id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    source_concept_id: Mapped[str] = mapped_column(String(100), index=True)
-    target_concept_id: Mapped[str] = mapped_column(String(100), index=True)
-    source_pack_id: Mapped[str] = mapped_column(String(100), index=True)
-    target_pack_id: Mapped[str] = mapped_column(String(100), index=True)
-    synthesis_kind: Mapped[str] = mapped_column(String(100), default="cross_pack_similarity")
-    score_total: Mapped[float] = mapped_column(Float, default=0.0)
-    score_semantic: Mapped[float] = mapped_column(Float, default=0.0)
-    score_structural: Mapped[float] = mapped_column(Float, default=0.0)
-    score_trajectory: Mapped[float] = mapped_column(Float, default=0.0)
-    score_review_history: Mapped[float] = mapped_column(Float, default=0.0)
-    explanation: Mapped[str] = mapped_column(Text, default="")
-    evidence_json: Mapped[str] = mapped_column(Text, default="{}")
-    current_status: Mapped[str] = mapped_column(String(50), default="proposed")
-    created_at: Mapped[str] = mapped_column(String(100), default="")

src/didactopus/repository.py

@@ -1,17 +1,11 @@
 from __future__ import annotations
 import json
-from datetime import datetime, timezone
 from sqlalchemy import select
 from .db import SessionLocal
-from .orm import (
+from .orm import UserORM, RefreshTokenORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM, EvaluatorJobORM
-    UserORM, PackORM, LearnerORM, MasteryRecordORM,
+from .models import PackData, LearnerState, MasteryRecord, EvidenceEvent
-    KnowledgeCandidateORM, ReviewRecordORM, PromotionRecordORM, SynthesisCandidateORM
-)
 from .auth import verify_password
 
-def now_iso() -> str:
-    return datetime.now(timezone.utc).isoformat()
-
 def get_user_by_username(username: str):
     with SessionLocal() as db:
         return db.execute(select(UserORM).where(UserORM.username == username)).scalar_one_or_none()
@@ -26,13 +20,89 @@ def authenticate_user(username: str, password: str):
         return None
     return user
 
-def list_packs():
+def store_refresh_token(user_id: int, token_id: str):
     with SessionLocal() as db:
-        return db.execute(select(PackORM).order_by(PackORM.id)).scalars().all()
+        db.add(RefreshTokenORM(user_id=user_id, token_id=token_id, is_revoked=False))
+        db.commit()
+
+def refresh_token_active(token_id: str) -> bool:
+    with SessionLocal() as db:
+        row = db.execute(select(RefreshTokenORM).where(RefreshTokenORM.token_id == token_id)).scalar_one_or_none()
+        return row is not None and not row.is_revoked
+
+def revoke_refresh_token(token_id: str):
+    with SessionLocal() as db:
+        row = db.execute(select(RefreshTokenORM).where(RefreshTokenORM.token_id == token_id)).scalar_one_or_none()
+        if row:
+            row.is_revoked = True
+            db.commit()
+
+def list_packs(include_unpublished: bool = False):
+    with SessionLocal() as db:
+        stmt = select(PackORM)
+        if not include_unpublished:
+            stmt = stmt.where(PackORM.is_published == True)
+        rows = db.execute(stmt).scalars().all()
+        return [PackData.model_validate(json.loads(r.data_json)) for r in rows]
+
+def list_pack_admin_rows():
+    with SessionLocal() as db:
+        rows = db.execute(select(PackORM).order_by(PackORM.id)).scalars().all()
+        return [{"id": r.id, "title": r.title, "is_published": r.is_published, "subtitle": r.subtitle} for r in rows]
 
 def get_pack(pack_id: str):
     with SessionLocal() as db:
-        return db.get(PackORM, pack_id)
+        row = db.get(PackORM, pack_id)
+        return None if row is None else PackData.model_validate(json.loads(row.data_json))
+
+def get_pack_validation(pack_id: str):
+    with SessionLocal() as db:
+        row = db.get(PackORM, pack_id)
+        return {} if row is None else json.loads(row.validation_json or "{}")
+
+def get_pack_provenance(pack_id: str):
+    with SessionLocal() as db:
+        row = db.get(PackORM, pack_id)
+        return {} if row is None else json.loads(row.provenance_json or "{}")
+
+def upsert_pack(pack: PackData, is_published: bool = True):
+    validation = {
+        "ok": len(pack.concepts) > 0,
+        "warnings": [] if len(pack.concepts) > 0 else ["Pack has no concepts."],
+        "errors": [],
+        "summary": {"concept_count": len(pack.concepts), "has_onboarding": bool(pack.onboarding)}
+    }
+    provenance = {
+        "source_count": pack.compliance.sources,
+        "licenses_present": ["CC BY-NC-SA 4.0"] if pack.compliance.shareAlikeRequired or pack.compliance.noncommercialOnly else [],
+        "restrictive_flags": list(pack.compliance.flags),
+        "sources": [
+            {"source_id": "sample-source-1", "title": f"Provenance placeholder for {pack.title}", "license_id": "CC BY-NC-SA 4.0" if pack.compliance.shareAlikeRequired or pack.compliance.noncommercialOnly else "unspecified", "attribution_text": "Sample attribution text placeholder"}
+        ] if pack.compliance.sources else []
+    }
+    with SessionLocal() as db:
+        row = db.get(PackORM, pack.id)
+        payload = json.dumps(pack.model_dump())
+        if row is None:
+            db.add(PackORM(id=pack.id, title=pack.title, subtitle=pack.subtitle, level=pack.level, data_json=payload, validation_json=json.dumps(validation), provenance_json=json.dumps(provenance), is_published=is_published))
+        else:
+            row.title = pack.title
+            row.subtitle = pack.subtitle
+            row.level = pack.level
+            row.data_json = payload
+            row.validation_json = json.dumps(validation)
+            row.provenance_json = json.dumps(provenance)
+            row.is_published = is_published
+        db.commit()
+
+def set_pack_publication(pack_id: str, is_published: bool):
+    with SessionLocal() as db:
+        row = db.get(PackORM, pack_id)
+        if row is None:
+            return False
+        row.is_published = is_published
+        db.commit()
+        return True
 
 def create_learner(owner_user_id: int, learner_id: str, display_name: str = ""):
     with SessionLocal() as db:
@@ -40,244 +110,66 @@ def create_learner(owner_user_id: int, learner_id: str, display_name: str = ""):
             db.add(LearnerORM(id=learner_id, owner_user_id=owner_user_id, display_name=display_name))
             db.commit()
 
+def list_learners_for_user(user_id: int, is_admin: bool = False):
+    with SessionLocal() as db:
+        stmt = select(LearnerORM).order_by(LearnerORM.id)
+        if not is_admin:
+            stmt = stmt.where(LearnerORM.owner_user_id == user_id)
+        rows = db.execute(stmt).scalars().all()
+        return [{"learner_id": r.id, "display_name": r.display_name, "owner_user_id": r.owner_user_id} for r in rows]
+
 def learner_owned_by_user(user_id: int, learner_id: str) -> bool:
     with SessionLocal() as db:
         learner = db.get(LearnerORM, learner_id)
         return learner is not None and learner.owner_user_id == user_id
 
-def list_mastery_records(learner_id: str):
+def load_learner_state(learner_id: str):
     with SessionLocal() as db:
-        rows = db.execute(select(MasteryRecordORM).where(MasteryRecordORM.learner_id == learner_id)).scalars().all()
+        records = db.execute(select(MasteryRecordORM).where(MasteryRecordORM.learner_id == learner_id)).scalars().all()
-        return [{
+        history = db.execute(select(EvidenceEventORM).where(EvidenceEventORM.learner_id == learner_id)).scalars().all()
-            "concept_id": r.concept_id,
+        return LearnerState(
-            "dimension": r.dimension,
+            learner_id=learner_id,
-            "score": r.score,
+            records=[MasteryRecord(concept_id=r.concept_id, dimension=r.dimension, score=r.score, confidence=r.confidence, evidence_count=r.evidence_count, last_updated=r.last_updated) for r in records],
-            "confidence": r.confidence,
+            history=[EvidenceEvent(concept_id=h.concept_id, dimension=h.dimension, score=h.score, confidence_hint=h.confidence_hint, timestamp=h.timestamp, kind=h.kind, source_id=h.source_id) for h in history],
-            "evidence_count": r.evidence_count,
-            "last_updated": r.last_updated,
-        } for r in rows]
-
-def create_candidate(payload):
-    with SessionLocal() as db:
-        row = KnowledgeCandidateORM(
-            source_type=payload.source_type,
-            source_artifact_id=payload.source_artifact_id,
-            learner_id=payload.learner_id,
-            pack_id=payload.pack_id,
-            candidate_kind=payload.candidate_kind,
-            title=payload.title,
-            summary=payload.summary,
-            structured_payload_json=json.dumps(payload.structured_payload),
-            evidence_summary=payload.evidence_summary,
-            confidence_hint=payload.confidence_hint,
-            novelty_score=payload.novelty_score,
-            synthesis_score=payload.synthesis_score,
-            triage_lane=payload.triage_lane,
-            current_status="triaged",
-            created_at=now_iso(),
         )
-        db.add(row)
+
+def save_learner_state(state: LearnerState):
+    with SessionLocal() as db:
+        db.query(MasteryRecordORM).filter(MasteryRecordORM.learner_id == state.learner_id).delete()
+        db.query(EvidenceEventORM).filter(EvidenceEventORM.learner_id == state.learner_id).delete()
+        for r in state.records:
+            db.add(MasteryRecordORM(learner_id=state.learner_id, concept_id=r.concept_id, dimension=r.dimension, score=r.score, confidence=r.confidence, evidence_count=r.evidence_count, last_updated=r.last_updated))
+        for h in state.history:
+            db.add(EvidenceEventORM(learner_id=state.learner_id, concept_id=h.concept_id, dimension=h.dimension, score=h.score, confidence_hint=h.confidence_hint, timestamp=h.timestamp, kind=h.kind, source_id=h.source_id))
         db.commit()
-        db.refresh(row)
+    return state
-        return row.id
 
-def list_candidates():
+def create_evaluator_job(learner_id: str, pack_id: str, concept_id: str, submitted_text: str) -> int:
     with SessionLocal() as db:
-        rows = db.execute(select(KnowledgeCandidateORM).order_by(KnowledgeCandidateORM.id.desc())).scalars().all()
+        trace = {"rubric_dimension_scores": [{"dimension": "mastery", "score": 0.0}], "notes": ["Job queued", "Awaiting evaluator"], "token_count_estimate": len(submitted_text.split())}
-        return [{
+        job = EvaluatorJobORM(learner_id=learner_id, pack_id=pack_id, concept_id=concept_id, submitted_text=submitted_text, status="queued", trace_json=json.dumps(trace))
-            "candidate_id": r.id,
+        db.add(job)
-            "source_type": r.source_type,
-            "source_artifact_id": r.source_artifact_id,
-            "learner_id": r.learner_id,
-            "pack_id": r.pack_id,
-            "candidate_kind": r.candidate_kind,
-            "title": r.title,
-            "summary": r.summary,
-            "structured_payload": json.loads(r.structured_payload_json or "{}"),
-            "evidence_summary": r.evidence_summary,
-            "confidence_hint": r.confidence_hint,
-            "novelty_score": r.novelty_score,
-            "synthesis_score": r.synthesis_score,
-            "triage_lane": r.triage_lane,
-            "current_status": r.current_status,
-            "created_at": r.created_at,
-        } for r in rows]
-
-def get_candidate(candidate_id: int):
-    with SessionLocal() as db:
-        r = db.get(KnowledgeCandidateORM, candidate_id)
-        if r is None:
-            return None
-        return {
-            "candidate_id": r.id,
-            "source_type": r.source_type,
-            "source_artifact_id": r.source_artifact_id,
-            "learner_id": r.learner_id,
-            "pack_id": r.pack_id,
-            "candidate_kind": r.candidate_kind,
-            "title": r.title,
-            "summary": r.summary,
-            "structured_payload": json.loads(r.structured_payload_json or "{}"),
-            "evidence_summary": r.evidence_summary,
-            "confidence_hint": r.confidence_hint,
-            "novelty_score": r.novelty_score,
-            "synthesis_score": r.synthesis_score,
-            "triage_lane": r.triage_lane,
-            "current_status": r.current_status,
-            "created_at": r.created_at,
-        }
-
-def update_candidate(candidate_id: int, triage_lane=None, current_status=None):
-    with SessionLocal() as db:
-        row = db.get(KnowledgeCandidateORM, candidate_id)
-        if row is None:
-            return None
-        if triage_lane is not None:
-            row.triage_lane = triage_lane
-        if current_status is not None:
-            row.current_status = current_status
         db.commit()
-        db.refresh(row)
+        db.refresh(job)
-        return row
+        return job.id
 
-def create_review(candidate_id: int, reviewer_id: int, payload):
+def list_evaluator_jobs_for_learner(learner_id: str):
     with SessionLocal() as db:
-        row = ReviewRecordORM(
+        return db.execute(select(EvaluatorJobORM).where(EvaluatorJobORM.learner_id == learner_id).order_by(EvaluatorJobORM.id.desc())).scalars().all()
-            candidate_id=candidate_id,
+
-            reviewer_id=reviewer_id,
+def get_evaluator_job(job_id: int):
-            review_kind=payload.review_kind,
+    with SessionLocal() as db:
-            verdict=payload.verdict,
+        return db.get(EvaluatorJobORM, job_id)
-            rationale=payload.rationale,
+
-            requested_changes=payload.requested_changes,
+def update_evaluator_job(job_id: int, status: str, score: float | None = None, confidence_hint: float | None = None, notes: str = "", trace: dict | None = None):
-            created_at=now_iso(),
+    with SessionLocal() as db:
-        )
+        job = db.get(EvaluatorJobORM, job_id)
-        db.add(row)
+        if job is None:
+            return
+        job.status = status
+        job.result_score = score
+        job.result_confidence_hint = confidence_hint
+        job.result_notes = notes
+        if trace is not None:
+            job.trace_json = json.dumps(trace)
         db.commit()
-        db.refresh(row)
-        return row.id
-
-def list_reviews(candidate_id: int):
-    with SessionLocal() as db:
-        rows = db.execute(select(ReviewRecordORM).where(ReviewRecordORM.candidate_id == candidate_id).order_by(ReviewRecordORM.id.desc())).scalars().all()
-        return [{
-            "review_id": r.id,
-            "candidate_id": r.candidate_id,
-            "reviewer_id": r.reviewer_id,
-            "review_kind": r.review_kind,
-            "verdict": r.verdict,
-            "rationale": r.rationale,
-            "requested_changes": r.requested_changes,
-            "created_at": r.created_at,
-        } for r in rows]
-
-def create_promotion(candidate_id: int, promoted_by: int, payload):
-    with SessionLocal() as db:
-        row = PromotionRecordORM(
-            candidate_id=candidate_id,
-            promotion_target=payload.promotion_target,
-            target_object_id=payload.target_object_id,
-            promotion_status=payload.promotion_status,
-            promoted_by=promoted_by,
-            created_at=now_iso(),
-        )
-        db.add(row)
-        candidate = db.get(KnowledgeCandidateORM, candidate_id)
-        if candidate:
-            candidate.current_status = "promoted"
-            candidate.triage_lane = payload.promotion_target
-        db.commit()
-        db.refresh(row)
-        return row.id
-
-def list_promotions():
-    with SessionLocal() as db:
-        rows = db.execute(select(PromotionRecordORM).order_by(PromotionRecordORM.id.desc())).scalars().all()
-        return [{
-            "promotion_id": r.id,
-            "candidate_id": r.candidate_id,
-            "promotion_target": r.promotion_target,
-            "target_object_id": r.target_object_id,
-            "promotion_status": r.promotion_status,
-            "promoted_by": r.promoted_by,
-            "created_at": r.created_at,
-        } for r in rows]
-
-def create_synthesis_candidate(
-    source_concept_id: str,
-    target_concept_id: str,
-    source_pack_id: str,
-    target_pack_id: str,
-    synthesis_kind: str,
-    score_semantic: float,
-    score_structural: float,
-    score_trajectory: float,
-    score_review_history: float,
-    explanation: str,
-    evidence: dict
-):
-    score_total = 0.35 * score_semantic + 0.25 * score_structural + 0.20 * score_trajectory + 0.10 * score_review_history + 0.10 * evidence.get("novelty", 0.0)
-    with SessionLocal() as db:
-        row = SynthesisCandidateORM(
-            source_concept_id=source_concept_id,
-            target_concept_id=target_concept_id,
-            source_pack_id=source_pack_id,
-            target_pack_id=target_pack_id,
-            synthesis_kind=synthesis_kind,
-            score_total=score_total,
-            score_semantic=score_semantic,
-            score_structural=score_structural,
-            score_trajectory=score_trajectory,
-            score_review_history=score_review_history,
-            explanation=explanation,
-            evidence_json=json.dumps(evidence),
-            current_status="proposed",
-            created_at=now_iso(),
-        )
-        db.add(row)
-        db.commit()
-        db.refresh(row)
-        return row.id
-
-def list_synthesis_candidates():
-    with SessionLocal() as db:
-        rows = db.execute(select(SynthesisCandidateORM).order_by(SynthesisCandidateORM.score_total.desc(), SynthesisCandidateORM.id.desc())).scalars().all()
-        return [{
-            "synthesis_id": r.id,
-            "source_concept_id": r.source_concept_id,
-            "target_concept_id": r.target_concept_id,
-            "source_pack_id": r.source_pack_id,
-            "target_pack_id": r.target_pack_id,
-            "synthesis_kind": r.synthesis_kind,
-            "score_total": r.score_total,
-            "score_semantic": r.score_semantic,
-            "score_structural": r.score_structural,
-            "score_trajectory": r.score_trajectory,
-            "score_review_history": r.score_review_history,
-            "explanation": r.explanation,
-            "evidence": json.loads(r.evidence_json or "{}"),
-            "current_status": r.current_status,
-            "created_at": r.created_at,
-        } for r in rows]
-
-def get_synthesis_candidate(synthesis_id: int):
-    with SessionLocal() as db:
-        r = db.get(SynthesisCandidateORM, synthesis_id)
-        if r is None:
-            return None
-        return {
-            "synthesis_id": r.id,
-            "source_concept_id": r.source_concept_id,
-            "target_concept_id": r.target_concept_id,
-            "source_pack_id": r.source_pack_id,
-            "target_pack_id": r.target_pack_id,
-            "synthesis_kind": r.synthesis_kind,
-            "score_total": r.score_total,
-            "score_semantic": r.score_semantic,
-            "score_structural": r.score_structural,
-            "score_trajectory": r.score_trajectory,
-            "score_review_history": r.score_review_history,
-            "explanation": r.explanation,
-            "evidence": json.loads(r.evidence_json or "{}"),
-            "current_status": r.current_status,
-            "created_at": r.created_at,
-        }

src/didactopus/seed.py

@@ -1,53 +1,27 @@
 from __future__ import annotations
-import json
 from sqlalchemy import select
 from .db import Base, engine, SessionLocal
-from .orm import UserORM, PackORM
+from .orm import UserORM
 from .auth import hash_password
+from .repository import upsert_pack
+from .models import PackData, PackConcept, PackCompliance
 
 def main():
     Base.metadata.create_all(bind=engine)
     with SessionLocal() as db:
         if db.execute(select(UserORM).where(UserORM.username == "wesley")).scalar_one_or_none() is None:
             db.add(UserORM(username="wesley", password_hash=hash_password("demo-pass"), role="admin", is_active=True))
-        if db.execute(select(UserORM).where(UserORM.username == "reviewer")).scalar_one_or_none() is None:
-            db.add(UserORM(username="reviewer", password_hash=hash_password("demo-pass"), role="reviewer", is_active=True))
-        if db.get(PackORM, "biology-pack") is None:
-            db.add(PackORM(
-                id="biology-pack",
-                owner_user_id=1,
-                policy_lane="personal",
-                title="Biology Pack",
-                subtitle="Core biology concepts",
-                level="novice-friendly",
-                is_published=True,
-                data_json=json.dumps({
-                    "id": "biology-pack",
-                    "title": "Biology Pack",
-                    "concepts": [
-                        {"id": "selection", "title": "Natural Selection", "prerequisites": ["variation"]},
-                        {"id": "variation", "title": "Variation", "prerequisites": []},
-                        {"id": "drift", "title": "Genetic Drift", "prerequisites": ["variation"]}
-                    ]
-                })
-            ))
-        if db.get(PackORM, "math-pack") is None:
-            db.add(PackORM(
-                id="math-pack",
-                owner_user_id=1,
-                policy_lane="personal",
-                title="Math Pack",
-                subtitle="Core math concepts",
-                level="novice-friendly",
-                is_published=True,
-                data_json=json.dumps({
-                    "id": "math-pack",
-                    "title": "Math Pack",
-                    "concepts": [
-                        {"id": "random_walk", "title": "Random Walk", "prerequisites": ["variation"]},
-                        {"id": "variation", "title": "Variation in Models", "prerequisites": []},
-                        {"id": "optimization", "title": "Optimization", "prerequisites": []}
-                    ]
-                })
-            ))
         db.commit()
+    upsert_pack(PackData(
+        id="bayes-pack",
+        title="Bayesian Reasoning",
+        subtitle="Probability, evidence, updating, and model criticism.",
+        level="novice-friendly",
+        concepts=[
+            PackConcept(id="prior", title="Prior", prerequisites=[], masteryDimension="mastery", exerciseReward="Prior badge earned"),
+            PackConcept(id="posterior", title="Posterior", prerequisites=["prior"], masteryDimension="mastery", exerciseReward="Posterior path opened"),
+        ],
+        onboarding={"headline":"Start with a fast visible win","body":"Read one short orientation, answer one guided question, and leave with your first mastery marker.","checklist":["Read the one-screen topic orientation","Answer one guided exercise","Write one explanation in your own words"]},
+        compliance=PackCompliance(sources=2, attributionRequired=True, shareAlikeRequired=True, noncommercialOnly=True, flags=["share-alike","noncommercial","excluded-third-party-content"])
+    ), is_published=True)
+    print("Seeded database. Demo user: wesley / demo-pass")

src/didactopus/worker.py

@@ -1,43 +1,24 @@
 from __future__ import annotations
-import json, tempfile
+from .repository import get_evaluator_job, update_evaluator_job, load_learner_state, save_learner_state
-from pathlib import Path
+from .engine import apply_evidence
-from datetime import datetime, timedelta, timezone
+from .models import EvidenceEvent
-from .repository import update_render_job, register_artifact
+import time
-from .render_bundle import make_render_bundle
 
-def future_iso(days: int) -> str:
+def process_job(job_id: int):
-    return (datetime.now(timezone.utc) + timedelta(days=days)).isoformat()
+    job = get_evaluator_job(job_id)
+    if job is None:
+        return
+    update_evaluator_job(job_id, "running", trace={"rubric_dimension_scores": [{"dimension": "mastery", "score": 0.35}], "notes": ["Job running", "Prototype trace generated"], "token_count_estimate": len(job.submitted_text.split())})
+    score = 0.78 if len(job.submitted_text.strip()) > 20 else 0.62
+    confidence_hint = 0.72 if len(job.submitted_text.strip()) > 20 else 0.45
+    notes = "Prototype evaluator: longer responses scored somewhat higher."
+    trace = {"rubric_dimension_scores": [{"dimension": "mastery", "score": score}], "notes": ["Prototype evaluator completed", notes], "token_count_estimate": len(job.submitted_text.split()), "decision_basis": ["response length heuristic", "single-dimension mastery proxy"]}
+    update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes, trace=trace)
+    state = load_learner_state(job.learner_id)
+    state = apply_evidence(state, EvidenceEvent(concept_id=job.concept_id, dimension="mastery", score=score, confidence_hint=confidence_hint, timestamp="2026-03-13T12:00:00+00:00", kind="review", source_id=f"evaluator-job-{job_id}"))
+    save_learner_state(state)
 
-def process_render_job(job_id: int, learner_id: str, pack_id: str, fmt: str, fps: int, theme: str, retention_class: str, retention_days: int, animation_payload: dict):
+def main():
-    update_render_job(job_id, status="running")
+    print("Didactopus worker scaffold running. Replace this with a real queue worker.")
-    try:
+    while True:
-        base = Path(tempfile.mkdtemp(prefix=f"didactopus_job_{job_id}_"))
+        time.sleep(60)
-        payload_json = base / "animation_payload.json"
-        payload_json.write_text(json.dumps(animation_payload, indent=2), encoding="utf-8")
-        out_dir = base / "bundle"
-        make_render_bundle(str(payload_json), str(out_dir), fps=fps, fmt=fmt)
-        manifest_path = out_dir / "render_manifest.json"
-        script_path = out_dir / "render.sh"
-        update_render_job(
-            job_id,
-            status="completed",
-            bundle_dir=str(out_dir),
-            payload_json=str(payload_json),
-            manifest_path=str(manifest_path),
-            script_path=str(script_path),
-            error_text="",
-        )
-        register_artifact(
-            render_job_id=job_id,
-            learner_id=learner_id,
-            pack_id=pack_id,
-            artifact_type="render_bundle",
-            fmt=fmt,
-            title=f"{pack_id} animation bundle",
-            path=str(out_dir),
-            metadata={"fps": fps, "theme": theme, "manifest_path": str(manifest_path), "script_path": str(script_path)},
-            retention_class=retention_class,
-            expires_at=future_iso(retention_days),
-        )
-    except Exception as e:
-        update_render_job(job_id, status="failed", error_text=str(e))

tests/test_scaffold_files.py

@@ -3,5 +3,5 @@ from pathlib import Path
 def test_scaffold_files_exist():
     assert Path("src/didactopus/api.py").exists()
     assert Path("src/didactopus/repository.py").exists()
-    assert Path("src/didactopus/synthesis.py").exists()
     assert Path("webui/src/App.jsx").exists()
+    assert Path("webui/src/api.js").exists()

webui/index.html

@@ -3,10 +3,8 @@
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Didactopus Review UI</title>
+    <title>Didactopus Admin Curation Layer</title>
     <script type="module" src="/src/main.jsx"></script>
   </head>
-  <body>
+  <body><div id="root"></div></body>
-    <div id="root"></div>
-  </body>
 </html>

webui/package.json

@@ -1,17 +1,9 @@
 {
-  "name": "didactopus-review-ui",
+  "name": "didactopus-admin-curation-ui",
   "private": true,
   "version": "0.1.0",
   "type": "module",
-  "scripts": {
+  "scripts": { "dev": "vite", "build": "vite build" },
-    "dev": "vite",
+  "dependencies": { "react": "^18.3.1", "react-dom": "^18.3.1" },
-    "build": "vite build"
+  "devDependencies": { "vite": "^5.4.0" }
-  },
-  "dependencies": {
-    "react": "^18.3.1",
-    "react-dom": "^18.3.1"
-  },
-  "devDependencies": {
-    "vite": "^5.4.0"
-  }
 }

webui/src/App.jsx

@@ -1,269 +1,317 @@
-import React, { useEffect, useMemo, useState } from "react";
+import React, { useEffect, useState } from "react";
+import { login, refresh, fetchPacks, fetchAdminPacks, fetchPackValidation, fetchPackProvenance, upsertPack, publishPack, listLearners, createLearner, fetchLearnerState, fetchRecommendations, postEvidence, submitEvaluatorJob, fetchEvaluatorHistory, fetchEvaluatorTrace } from "./api";
+import { loadAuth, saveAuth, clearAuth } from "./authStore";
 
-const API = "http://127.0.0.1:8765";
+function LoginView({ onAuth }) {
-const statuses = ["needs_review", "trusted", "provisional", "rejected"];
+  const [username, setUsername] = useState("wesley");
+  const [password, setPassword] = useState("demo-pass");
+  const [error, setError] = useState("");
+  async function doLogin() {
+    try {
+      const result = await login(username, password);
+      saveAuth(result);
+      onAuth(result);
+    } catch { setError("Login failed"); }
+  }
+  return (
+    <div className="page narrow-page">
+      <section className="card narrow">
+        <h1>Didactopus login</h1>
+        <label>Username<input value={username} onChange={(e) => setUsername(e.target.value)} /></label>
+        <label>Password<input type="password" value={password} onChange={(e) => setPassword(e.target.value)} /></label>
+        <button className="primary" onClick={doLogin}>Login</button>
+        {error ? <div className="error">{error}</div> : null}
+      </section>
+    </div>
+  );
+}
+
+function NavTabs({ tab, setTab, role }) {
+  return (
+    <div className="tab-row">
+      <button className={tab==="learner" ? "active-tab" : ""} onClick={() => setTab("learner")}>Learner</button>
+      <button className={tab==="history" ? "active-tab" : ""} onClick={() => setTab("history")}>Evaluator history</button>
+      <button className={tab==="manage" ? "active-tab" : ""} onClick={() => setTab("manage")}>Learners</button>
+      {role === "admin" ? <>
+        <button className={tab==="admin" ? "active-tab" : ""} onClick={() => setTab("admin")}>Pack admin</button>
+        <button className={tab==="review" ? "active-tab" : ""} onClick={() => setTab("review")}>Curation review</button>
+      </> : null}
+    </div>
+  );
+}
+
+function PackAuthorForm({ value, onChange, onSave }) {
+  function setField(field, val) { onChange({ ...value, [field]: val }); }
+  function setCompliance(field, val) { onChange({ ...value, compliance: { ...value.compliance, [field]: val } }); }
+  return (
+    <div className="form-grid">
+      <label>Pack ID<input value={value.id} onChange={(e) => setField("id", e.target.value)} /></label>
+      <label>Title<input value={value.title} onChange={(e) => setField("title", e.target.value)} /></label>
+      <label className="full">Subtitle<input value={value.subtitle} onChange={(e) => setField("subtitle", e.target.value)} /></label>
+      <label>Level<input value={value.level} onChange={(e) => setField("level", e.target.value)} /></label>
+      <label>Source count<input type="number" value={value.compliance.sources} onChange={(e) => setCompliance("sources", Number(e.target.value))} /></label>
+      <label className="full">Onboarding headline<input value={value.onboarding.headline} onChange={(e) => onChange({ ...value, onboarding: { ...value.onboarding, headline: e.target.value } })} /></label>
+      <label className="full">Onboarding body<textarea value={value.onboarding.body} onChange={(e) => onChange({ ...value, onboarding: { ...value.onboarding, body: e.target.value } })} /></label>
+      <div className="checkrow full">
+        <label><input type="checkbox" checked={value.compliance.attributionRequired} onChange={(e) => setCompliance("attributionRequired", e.target.checked)} /> Attribution required</label>
+        <label><input type="checkbox" checked={value.compliance.shareAlikeRequired} onChange={(e) => setCompliance("shareAlikeRequired", e.target.checked)} /> Share-alike</label>
+        <label><input type="checkbox" checked={value.compliance.noncommercialOnly} onChange={(e) => setCompliance("noncommercialOnly", e.target.checked)} /> Noncommercial only</label>
+      </div>
+      <div className="full"><button className="primary" onClick={onSave}>Save pack</button></div>
+    </div>
+  );
+}
 
 export default function App() {
-  const [registry, setRegistry] = useState({ workspaces: [], recent_workspace_ids: [] });
+  const [auth, setAuth] = useState(loadAuth());
-  const [workspaceId, setWorkspaceId] = useState("");
+  const [tab, setTab] = useState("learner");
-  const [workspaceTitle, setWorkspaceTitle] = useState("");
+  const [packs, setPacks] = useState([]);
-  const [importSource, setImportSource] = useState("");
+  const [adminPacks, setAdminPacks] = useState([]);
-  const [importPreview, setImportPreview] = useState(null);
+  const [learners, setLearners] = useState([]);
-  const [allowOverwrite, setAllowOverwrite] = useState(false);
+  const [selectedLearnerId, setSelectedLearnerId] = useState("wesley-learner");
-  const [session, setSession] = useState(null);
+  const [selectedPackId, setSelectedPackId] = useState("");
-  const [selectedId, setSelectedId] = useState("");
+  const [learnerState, setLearnerState] = useState(null);
-  const [pendingActions, setPendingActions] = useState([]);
+  const [cards, setCards] = useState([]);
-  const [message, setMessage] = useState("Connecting to local Didactopus bridge...");
+  const [history, setHistory] = useState([]);
+  const [selectedTrace, setSelectedTrace] = useState(null);
+  const [validation, setValidation] = useState(null);
+  const [provenance, setProvenance] = useState(null);
+  const [newLearnerId, setNewLearnerId] = useState("wesley-learner");
+  const [formPack, setFormPack] = useState({ id: "new-pack", title: "New Pack", subtitle: "Editable admin pack scaffold", level: "novice-friendly", concepts: [], onboarding: { headline: "Start here", body: "Begin", checklist: [] }, compliance: { sources: 0, attributionRequired: false, shareAlikeRequired: false, noncommercialOnly: false, flags: [] } });
+  const [message, setMessage] = useState("");
 
-  async function loadRegistry() {
+  async function refreshAuthToken() {
-    const res = await fetch(`${API}/api/workspaces`);
+    if (!auth?.refresh_token) return null;
-    const data = await res.json();
+    try {
-    setRegistry(data);
+      const result = await refresh(auth.refresh_token);
-    if (!session) setMessage("Choose, create, preview, or import a workspace.");
+      saveAuth(result);
+      setAuth(result);
+      return result;
+    } catch {
+      clearAuth();
+      setAuth(null);
+      return null;
+    }
+  }
+
+  async function guarded(fn) {
+    try { return await fn(auth.access_token); }
+    catch {
+      const next = await refreshAuthToken();
+      if (!next) throw new Error("auth failed");
+      return await fn(next.access_token);
+    }
   }
 
   useEffect(() => {
-    loadRegistry().catch(() => setMessage("Could not connect to local review bridge. Start the Python bridge service first."));
+    if (!auth) return;
-  }, []);
+    async function load() {
+      const p = await guarded((token) => fetchPacks(token));
+      setPacks(p);
+      setSelectedPackId((prev) => prev || p[0]?.id || "");
+      let ls = await guarded((token) => listLearners(token));
+      if (ls.length === 0) {
+        await guarded((token) => createLearner(token, selectedLearnerId, selectedLearnerId));
+        ls = await guarded((token) => listLearners(token));
+      }
+      setLearners(ls);
+      if (auth.role === "admin") {
+        const ap = await guarded((token) => fetchAdminPacks(token));
+        setAdminPacks(ap);
+      }
+    }
+    load();
+  }, [auth]);
 
-  async function createWorkspace() {
+  useEffect(() => {
-    if (!workspaceId || !workspaceTitle) return;
+    if (!auth || !selectedLearnerId || !selectedPackId) return;
-    await fetch(`${API}/api/workspaces/create`, {
+    async function loadLearnerStuff() {
-      method: "POST",
+      setLearnerState(await guarded((token) => fetchLearnerState(token, selectedLearnerId)));
-      headers: {"Content-Type": "application/json"},
+      const recs = await guarded((token) => fetchRecommendations(token, selectedLearnerId, selectedPackId));
-      body: JSON.stringify({ workspace_id: workspaceId, title: workspaceTitle })
+      setCards(recs.cards || []);
-    });
+      setHistory(await guarded((token) => fetchEvaluatorHistory(token, selectedLearnerId)));
-    await loadRegistry();
+      if (auth.role === "admin") {
-    await openWorkspace(workspaceId);
+        setValidation(await guarded((token) => fetchPackValidation(token, selectedPackId)));
+        setProvenance(await guarded((token) => fetchPackProvenance(token, selectedPackId)));
+      }
+    }
+    loadLearnerStuff();
+  }, [auth, selectedLearnerId, selectedPackId]);
+
+  async function simulateCard(card) {
+    await guarded((token) => postEvidence(token, selectedLearnerId, { concept_id: card.conceptId, dimension: "mastery", score: card.scoreHint, confidence_hint: card.confidenceHint, timestamp: new Date().toISOString(), kind: "checkpoint", source_id: `ui-${card.id}` }));
+    setLearnerState(await guarded((token) => fetchLearnerState(token, selectedLearnerId)));
+    const recs = await guarded((token) => fetchRecommendations(token, selectedLearnerId, selectedPackId));
+    setCards(recs.cards || []);
+    setMessage(card.reward);
   }
 
-  async function previewImport() {
+  async function runEvaluator() {
-    if (!workspaceId || !importSource) return;
+    const conceptId = packs.find((p) => p.id === selectedPackId)?.concepts?.[0]?.id || "prior";
-    const res = await fetch(`${API}/api/workspaces/import-preview`, {
+    await guarded((token) => submitEvaluatorJob(token, selectedLearnerId, { pack_id: selectedPackId, concept_id: conceptId, submitted_text: "This is a moderately detailed learner response intended to trigger a somewhat better prototype evaluator score.", kind: "checkpoint" }));
-      method: "POST",
+    setTimeout(async () => {
-      headers: {"Content-Type": "application/json"},
+      setHistory(await guarded((token) => fetchEvaluatorHistory(token, selectedLearnerId)));
-      body: JSON.stringify({ workspace_id: workspaceId, source_dir: importSource })
+      setLearnerState(await guarded((token) => fetchLearnerState(token, selectedLearnerId)));
-    });
+      const recs = await guarded((token) => fetchRecommendations(token, selectedLearnerId, selectedPackId));
-    const data = await res.json();
+      setCards(recs.cards || []);
-    setImportPreview(data);
+    }, 1200);
-    setMessage(data.ok ? "Import preview ready." : "Import preview found blocking errors.");
   }
 
-  async function importWorkspace() {
+  async function createLearnerNow() {
-    if (!workspaceId || !importSource) return;
+    await guarded((token) => createLearner(token, newLearnerId, newLearnerId));
-    const res = await fetch(`${API}/api/workspaces/import`, {
+    const ls = await guarded((token) => listLearners(token));
-      method: "POST",
+    setLearners(ls);
-      headers: {"Content-Type": "application/json"},
+    setSelectedLearnerId(newLearnerId);
-      body: JSON.stringify({
-        workspace_id: workspaceId,
-        title: workspaceTitle || workspaceId,
-        source_dir: importSource,
-        allow_overwrite: allowOverwrite
-      })
-    });
-    const data = await res.json();
-    if (!data.ok) {
-      setMessage(data.error || "Import failed.");
-      return;
-    }
-    await loadRegistry();
-    await openWorkspace(workspaceId);
-    setMessage(`Imported draft pack from ${importSource} into workspace ${workspaceId}.`);
   }
 
-  async function openWorkspace(id) {
+  async function savePack() {
-    const res = await fetch(`${API}/api/workspaces/open`, {
+    await guarded((token) => upsertPack(token, { pack: formPack, is_published: false }));
-      method: "POST",
+    setAdminPacks(await guarded((token) => fetchAdminPacks(token)));
-      headers: {"Content-Type": "application/json"},
+    setPacks(await guarded((token) => fetchPacks(token)));
-      body: JSON.stringify({ workspace_id: id })
+    setMessage("Pack saved");
-    });
-    const opened = await res.json();
-    if (!opened.ok) {
-      setMessage("Could not open workspace.");
-      return;
-    }
-    const sessionRes = await fetch(`${API}/api/load`);
-    const sessionData = await sessionRes.json();
-    setSession(sessionData.session);
-    setSelectedId(sessionData.session?.draft_pack?.concepts?.[0]?.concept_id || "");
-    setPendingActions([]);
-    setMessage(`Opened workspace ${id}.`);
-    await loadRegistry();
   }
 
-  const selected = useMemo(() => {
+  async function togglePublish(packId, isPublished) {
-    if (!session) return null;
+    await guarded((token) => publishPack(token, packId, isPublished));
-    return session.draft_pack.concepts.find((c) => c.concept_id === selectedId) || null;
+    setAdminPacks(await guarded((token) => fetchAdminPacks(token)));
-  }, [session, selectedId]);
+    setPacks(await guarded((token) => fetchPacks(token)));
-
-  function queueAction(action) {
-    setPendingActions((prev) => [...prev, action]);
   }
 
-  function patchConcept(conceptId, patch, rationale) {
+  async function loadTrace(jobId) {
-    if (!session) return;
+    setSelectedTrace(await guarded((token) => fetchEvaluatorTrace(token, jobId)));
-    const concepts = session.draft_pack.concepts.map((c) =>
-      c.concept_id === conceptId ? { ...c, ...patch } : c
-    );
-    setSession({ ...session, draft_pack: { ...session.draft_pack, concepts } });
-
-    if (patch.status !== undefined) queueAction({ action_type: "set_status", target: conceptId, payload: { status: patch.status }, rationale });
-    if (patch.title !== undefined) queueAction({ action_type: "edit_title", target: conceptId, payload: { title: patch.title }, rationale });
-    if (patch.description !== undefined) queueAction({ action_type: "edit_description", target: conceptId, payload: { description: patch.description }, rationale });
-    if (patch.prerequisites !== undefined) queueAction({ action_type: "edit_prerequisites", target: conceptId, payload: { prerequisites: patch.prerequisites }, rationale });
-    if (patch.notes !== undefined) queueAction({ action_type: "edit_notes", target: conceptId, payload: { notes: patch.notes }, rationale });
   }
 
-  function resolveConflict(conflict) {
+  if (!auth) return <LoginView onAuth={setAuth} />;
-    if (!session) return;
-    setSession({
-      ...session,
-      draft_pack: { ...session.draft_pack, conflicts: session.draft_pack.conflicts.filter((c) => c !== conflict) }
-    });
-    queueAction({ action_type: "resolve_conflict", target: "", payload: { conflict }, rationale: "Resolved in UI" });
-  }
-
-  async function saveChanges() {
-    if (!pendingActions.length) {
-      setMessage("No pending changes to save.");
-      return;
-    }
-    const res = await fetch(`${API}/api/save`, {
-      method: "POST",
-      headers: {"Content-Type": "application/json"},
-      body: JSON.stringify({ actions: pendingActions })
-    });
-    const data = await res.json();
-    setSession(data.session);
-    setPendingActions([]);
-    setMessage("Saved review state.");
-  }
-
-  async function exportPromoted() {
-    const res = await fetch(`${API}/api/export`, {
-      method: "POST",
-      headers: {"Content-Type": "application/json"},
-      body: JSON.stringify({})
-    });
-    const data = await res.json();
-    setMessage(`Exported promoted pack to ${data.promoted_pack_dir}`);
-  }
 
   return (
     <div className="page">
       <header className="hero">
         <div>
-          <h1>Didactopus Semantic QA</h1>
+          <h1>Didactopus admin curation layer</h1>
-          <p>
+          <p>Pack validation review, provenance inspection, evaluator traces, and form-driven pack authoring.</p>
-            Reduce the activation-energy hump from generated draft packs to curated review workspaces
+          <div className="muted">Signed in as {auth.username} ({auth.role})</div>
-            by surfacing semantic curation issues before import.
+          {message ? <div className="message">{message}</div> : null}
-          </p>
-          <div className="small">{message}</div>
         </div>
-        <div className="hero-actions">
+        <div className="hero-controls">
-          <button onClick={saveChanges}>Save Review State</button>
+          <label>Learner<select value={selectedLearnerId} onChange={(e) => setSelectedLearnerId(e.target.value)}>{learners.map((l) => <option key={l.learner_id} value={l.learner_id}>{l.display_name || l.learner_id}</option>)}</select></label>
-          <button onClick={exportPromoted} disabled={!session}>Export Promoted Pack</button>
+          <label>Pack<select value={selectedPackId} onChange={(e) => setSelectedPackId(e.target.value)}>{packs.map((p) => <option key={p.id} value={p.id}>{p.title}</option>)}</select></label>
+          <button onClick={() => { clearAuth(); setAuth(null); }}>Logout</button>
         </div>
       </header>
 
-      <section className="summary-grid">
+      <NavTabs tab={tab} setTab={setTab} role={auth.role} />
-        <div className="card">
-          <h2>Create Workspace</h2>
-          <label>Workspace ID<input value={workspaceId} onChange={(e) => setWorkspaceId(e.target.value)} /></label>
-          <label>Title<input value={workspaceTitle} onChange={(e) => setWorkspaceTitle(e.target.value)} /></label>
-          <button onClick={createWorkspace}>Create</button>
-        </div>
-        <div className="card">
-          <h2>Preview / Import Draft Pack</h2>
-          <label>Workspace ID<input value={workspaceId} onChange={(e) => setWorkspaceId(e.target.value)} /></label>
-          <label>Draft Pack Source Directory<input value={importSource} onChange={(e) => setImportSource(e.target.value)} placeholder="e.g. generated-pack" /></label>
-          <label className="checkline"><input type="checkbox" checked={allowOverwrite} onChange={(e) => setAllowOverwrite(e.target.checked)} /> Allow overwrite of existing workspace draft_pack</label>
-          <div className="button-row">
-            <button onClick={previewImport}>Preview</button>
-            <button onClick={importWorkspace}>Import</button>
-          </div>
-        </div>
-        <div className="card">
-          <h2>Recent</h2>
-          <ul>{registry.recent_workspace_ids.map((id) => <li key={id}><button onClick={() => openWorkspace(id)}>{id}</button></li>)}</ul>
-        </div>
-        <div className="card">
-          <h2>All Workspaces</h2>
-          <ul>{registry.workspaces.map((ws) => <li key={ws.workspace_id}><button onClick={() => openWorkspace(ws.workspace_id)}>{ws.title} ({ws.workspace_id})</button></li>)}</ul>
-        </div>
-      </section>
 
-      {importPreview && (
+      {tab === "learner" && (
-        <section className="preview-grid">
+        <main className="layout onecol">
-          <div className="card">
+          <section className="card">
-            <h2>Import Preview</h2>
+            <h2>Learner dashboard</h2>
-            <div><strong>OK:</strong> {String(importPreview.ok)}</div>
+            <button onClick={runEvaluator}>Submit demo evaluator job</button>
-            <div><strong>Overwrite Required:</strong> {String(importPreview.overwrite_required)}</div>
+            <div className="steps-stack">
-            <div><strong>Pack:</strong> {importPreview.summary?.display_name || importPreview.summary?.pack_name || "-"}</div>
+              {cards.length ? cards.map((card) => (
-            <div><strong>Version:</strong> {importPreview.summary?.version || "-"}</div>
+                <div key={card.id} className="step-card">
-            <div><strong>Concepts:</strong> {importPreview.summary?.concept_count ?? "-"}</div>
+                  <div className="step-header">
-            <div><strong>Roadmap Stages:</strong> {importPreview.summary?.roadmap_stage_count ?? "-"}</div>
+                    <div><h4>{card.title}</h4><div className="muted">{card.minutes} minutes</div></div>
-            <div><strong>Projects:</strong> {importPreview.summary?.project_count ?? "-"}</div>
+                    <div className="reward-pill">{card.reward}</div>
-            <div><strong>Rubrics:</strong> {importPreview.summary?.rubric_count ?? "-"}</div>
                   </div>
-          <div className="card">
+                  <p>{card.reason}</p>
-            <h2>Validation Errors</h2>
+                  <details><summary>Why this is recommended</summary><ul>{card.why.map((w, idx) => <li key={idx}>{w}</li>)}</ul></details>
-            <ul>{(importPreview.errors || []).length ? importPreview.errors.map((x, i) => <li key={i}>{x}</li>) : <li>none</li>}</ul>
+                  <button className="primary" onClick={() => simulateCard(card)}>Simulate step</button>
                 </div>
-          <div className="card">
+              )) : <div className="muted">No recommendations available.</div>}
-            <h2>Validation Warnings</h2>
-            <ul>{(importPreview.warnings || []).length ? importPreview.warnings.map((x, i) => <li key={i}>{x}</li>) : <li>none</li>}</ul>
-          </div>
-          <div className="card semantic-card">
-            <h2>Semantic QA Warnings</h2>
-            <ul>{(importPreview.semantic_warnings || []).length ? importPreview.semantic_warnings.map((x, i) => <li key={i}>{x}</li>) : <li>none</li>}</ul>
             </div>
+            <h3>Learner state snapshot</h3>
+            <pre className="prebox">{JSON.stringify(learnerState, null, 2)}</pre>
           </section>
+        </main>
       )}
 
-      {session && (
+      {tab === "history" && (
-        <main className="layout">
+        <main className="layout twocol">
-          <aside className="sidebar">
+          <section className="card">
-            <h2>Concepts</h2>
+            <h2>Evaluator history</h2>
-            {session.draft_pack.concepts.map((c) => (
+            {history.length ? (
-              <button key={c.concept_id} className={`concept-btn ${c.concept_id === selectedId ? "active" : ""}`} onClick={() => setSelectedId(c.concept_id)}>
+              <table className="table">
-                <span>{c.title}</span>
+                <thead><tr><th>Job</th><th>Status</th><th>Concept</th><th>Score</th><th>Trace</th></tr></thead>
-                <span className={`status-pill status-${c.status}`}>{c.status}</span>
+                <tbody>
-              </button>
+                  {history.map((row) => (
+                    <tr key={row.job_id}>
+                      <td>{row.job_id}</td>
+                      <td>{row.status}</td>
+                      <td>{row.concept_id}</td>
+                      <td>{row.result_score ?? "-"}</td>
+                      <td><button onClick={() => loadTrace(row.job_id)}>Inspect trace</button></td>
+                    </tr>
                   ))}
-          </aside>
+                </tbody>
-
+              </table>
-          <section className="content">
+            ) : <div className="muted">No evaluator jobs yet.</div>}
-            {selected && (
-              <div className="card">
-                <h2>Concept Editor</h2>
-                <label>Title<input value={selected.title} onChange={(e) => patchConcept(selected.concept_id, { title: e.target.value }, "Edited title")} /></label>
-                <label>Status
-                  <select value={selected.status} onChange={(e) => patchConcept(selected.concept_id, { status: e.target.value }, "Changed trust status")}>
-                    {statuses.map((s) => <option key={s} value={s}>{s}</option>)}
-                  </select>
-                </label>
-                <label>Description<textarea rows="6" value={selected.description} onChange={(e) => patchConcept(selected.concept_id, { description: e.target.value }, "Edited description")} /></label>
-                <label>Prerequisites (comma-separated ids)<input value={(selected.prerequisites || []).join(", ")} onChange={(e) => patchConcept(selected.concept_id, { prerequisites: e.target.value.split(",").map((x) => x.trim()).filter(Boolean) }, "Edited prerequisites")} /></label>
-                <label>Notes (one per line)<textarea rows="4" value={(selected.notes || []).join("\n")} onChange={(e) => patchConcept(selected.concept_id, { notes: e.target.value.split("\n").filter(Boolean) }, "Edited notes")} /></label>
-              </div>
-            )}
           </section>
+          <section className="card">
+            <h2>Evaluator trace</h2>
+            <pre className="prebox">{JSON.stringify(selectedTrace, null, 2)}</pre>
+          </section>
+        </main>
+      )}
 
-          <section className="rightbar">
+      {tab === "manage" && (
-            <div className="card">
+        <main className="layout twocol">
-              <h2>Conflicts</h2>
+          <section className="card">
-              {session.draft_pack.conflicts.length ? session.draft_pack.conflicts.map((conflict, idx) => (
+            <h2>Learner management</h2>
-                <div key={idx} className="conflict">
+            <label>New learner ID<input value={newLearnerId} onChange={(e) => setNewLearnerId(e.target.value)} /></label>
-                  <div>{conflict}</div>
+            <button className="primary" onClick={createLearnerNow}>Create learner</button>
-                  <button onClick={() => resolveConflict(conflict)}>Resolve</button>
+          </section>
-                </div>
+          <section className="card">
-              )) : <div className="small">No remaining conflicts.</div>}
+            <h2>Existing learners</h2>
-            </div>
+            <table className="table">
-            <div className="card">
+              <thead><tr><th>Learner ID</th><th>Display name</th><th>Owner</th></tr></thead>
-              <h2>Review Flags</h2>
+              <tbody>
-              <ul>{session.draft_pack.review_flags.map((flag, idx) => <li key={idx}>{flag}</li>)}</ul>
+                {learners.map((row) => (
-            </div>
+                  <tr key={row.learner_id}>
+                    <td>{row.learner_id}</td>
+                    <td>{row.display_name}</td>
+                    <td>{row.owner_user_id}</td>
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </section>
+        </main>
+      )}
+
+      {tab === "admin" && auth.role === "admin" && (
+        <main className="layout twocol">
+          <section className="card">
+            <h2>Richer pack authoring</h2>
+            <PackAuthorForm value={formPack} onChange={setFormPack} onSave={savePack} />
+          </section>
+          <section className="card">
+            <h2>Pack administration</h2>
+            <table className="table">
+              <thead><tr><th>ID</th><th>Title</th><th>Published</th><th>Action</th></tr></thead>
+              <tbody>
+                {adminPacks.map((row) => (
+                  <tr key={row.id}>
+                    <td>{row.id}</td>
+                    <td>{row.title}</td>
+                    <td>{String(row.is_published)}</td>
+                    <td><button onClick={() => togglePublish(row.id, !row.is_published)}>{row.is_published ? "Unpublish" : "Publish"}</button></td>
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </section>
+        </main>
+      )}
+
+      {tab === "review" && auth.role === "admin" && (
+        <main className="layout twocol">
+          <section className="card">
+            <h2>Pack validation review</h2>
+            <pre className="prebox">{JSON.stringify(validation, null, 2)}</pre>
+          </section>
+          <section className="card">
+            <h2>Attribution / provenance inspection</h2>
+            <pre className="prebox">{JSON.stringify(provenance, null, 2)}</pre>
           </section>
         </main>
       )}

webui/src/api.js

@@ -12,44 +12,23 @@ export async function login(username, password) {
   return await res.json();
 }
 
-export async function listCandidates(token) {
+export async function refresh(refreshToken) {
-  const res = await fetch(`${API}/knowledge-candidates`, { headers: authHeaders(token, false) });
+  const res = await fetch(`${API}/refresh`, { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ refresh_token: refreshToken }) });
-  if (!res.ok) throw new Error("listCandidates failed");
+  if (!res.ok) throw new Error("refresh failed");
   return await res.json();
 }
 
-export async function createCandidate(token, payload) {
+export async function fetchPacks(token) { const res = await fetch(`${API}/packs`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchPacks failed"); return await res.json(); }
-  const res = await fetch(`${API}/knowledge-candidates`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) });
+export async function fetchAdminPacks(token) { const res = await fetch(`${API}/admin/packs`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchAdminPacks failed"); return await res.json(); }
-  if (!res.ok) throw new Error("createCandidate failed");
+export async function fetchPackValidation(token, packId) { const res = await fetch(`${API}/admin/packs/${packId}/validation`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchPackValidation failed"); return await res.json(); }
-  return await res.json();
+export async function fetchPackProvenance(token, packId) { const res = await fetch(`${API}/admin/packs/${packId}/provenance`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchPackProvenance failed"); return await res.json(); }
-}
+export async function upsertPack(token, payload) { const res = await fetch(`${API}/admin/packs`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) }); if (!res.ok) throw new Error("upsertPack failed"); return await res.json(); }
-
+export async function publishPack(token, packId, isPublished) { const res = await fetch(`${API}/admin/packs/${packId}/publish?is_published=${isPublished}`, { method: "POST", headers: authHeaders(token, false) }); if (!res.ok) throw new Error("publishPack failed"); return await res.json(); }
-export async function createReview(token, candidateId, payload) {
+export async function listLearners(token) { const res = await fetch(`${API}/learners`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("listLearners failed"); return await res.json(); }
-  const res = await fetch(`${API}/knowledge-candidates/${candidateId}/reviews`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) });
+export async function createLearner(token, learnerId, displayName) { const res = await fetch(`${API}/learners`, { method: "POST", headers: authHeaders(token), body: JSON.stringify({ learner_id: learnerId, display_name: displayName }) }); if (!res.ok) throw new Error("createLearner failed"); return await res.json(); }
-  if (!res.ok) throw new Error("createReview failed");
+export async function fetchLearnerState(token, learnerId) { const res = await fetch(`${API}/learners/${learnerId}/state`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchLearnerState failed"); return await res.json(); }
-  return await res.json();
+export async function fetchRecommendations(token, learnerId, packId) { const res = await fetch(`${API}/learners/${learnerId}/recommendations/${packId}`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchRecommendations failed"); return await res.json(); }
-}
+export async function postEvidence(token, learnerId, event) { const res = await fetch(`${API}/learners/${learnerId}/evidence`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(event) }); if (!res.ok) throw new Error("postEvidence failed"); return await res.json(); }
-
+export async function submitEvaluatorJob(token, learnerId, payload) { const res = await fetch(`${API}/learners/${learnerId}/evaluator-jobs`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) }); if (!res.ok) throw new Error("submitEvaluatorJob failed"); return await res.json(); }
-export async function promoteCandidate(token, candidateId, payload) {
+export async function fetchEvaluatorHistory(token, learnerId) { const res = await fetch(`${API}/learners/${learnerId}/evaluator-history`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchEvaluatorHistory failed"); return await res.json(); }
-  const res = await fetch(`${API}/knowledge-candidates/${candidateId}/promote`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) });
+export async function fetchEvaluatorTrace(token, jobId) { const res = await fetch(`${API}/evaluator-jobs/${jobId}/trace`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchEvaluatorTrace failed"); return await res.json(); }
-  if (!res.ok) throw new Error("promoteCandidate failed");
-  return await res.json();
-}
-
-export async function runSynthesis(token, payload) {
-  const res = await fetch(`${API}/synthesis/run`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) });
-  if (!res.ok) throw new Error("runSynthesis failed");
-  return await res.json();
-}
-
-export async function listSynthesisCandidates(token) {
-  const res = await fetch(`${API}/synthesis/candidates`, { headers: authHeaders(token, false) });
-  if (!res.ok) throw new Error("listSynthesisCandidates failed");
-  return await res.json();
-}
-
-export async function promoteSynthesis(token, synthesisId, payload) {
-  const res = await fetch(`${API}/synthesis/candidates/${synthesisId}/promote`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) });
-  if (!res.ok) throw new Error("promoteSynthesis failed");
-  return await res.json();
-}

webui/src/main.jsx

@@ -2,5 +2,4 @@ import React from "react";
 import { createRoot } from "react-dom/client";
 import App from "./App";
 import "./styles.css";
-
 createRoot(document.getElementById("root")).render(<App />);

webui/src/styles.css

@@ -1,42 +1,37 @@
 :root {
-  --bg: #f7f8fb;
+  --bg:#f6f8fb; --card:#ffffff; --text:#1f2430; --muted:#60697a; --border:#dbe1ea; --accent:#2d6cdf; --soft:#eef4ff;
-  --card: #ffffff;
-  --text: #1f2430;
-  --muted: #5d6678;
-  --border: #d7dce5;
-  --accent: #2d6cdf;
 }
 * { box-sizing:border-box; }
 body { margin:0; font-family:Arial, Helvetica, sans-serif; background:var(--bg); color:var(--text); }
-.page { max-width: 1500px; margin: 0 auto; padding: 20px; }
+.page { max-width:1500px; margin:0 auto; padding:24px; }
-.hero { background: var(--card); border: 1px solid var(--border); border-radius: 20px; padding: 20px; display: flex; justify-content: space-between; gap: 20px; align-items: flex-start; }
+.narrow-page { max-width:520px; }
-.hero h1 { margin-top: 0; }
+.hero { background:var(--card); border:1px solid var(--border); border-radius:22px; padding:24px; display:flex; justify-content:space-between; gap:16px; }
-.hero-actions { display: flex; gap: 10px; flex-wrap: wrap; }
+.hero-controls { min-width:280px; display:flex; flex-direction:column; gap:12px; }
-button { border: 1px solid var(--border); background: white; border-radius: 12px; padding: 10px 14px; cursor: pointer; }
+label { display:block; font-weight:600; }
-button:hover { border-color: var(--accent); }
+input, select, textarea { width:100%; margin-top:6px; border:1px solid var(--border); border-radius:10px; padding:10px; font:inherit; background:white; }
-.summary-grid { margin-top: 16px; display: grid; grid-template-columns: repeat(4, 1fr); gap: 16px; }
+.card { background:var(--card); border:1px solid var(--border); border-radius:18px; padding:18px; }
-.preview-grid { margin-top: 16px; display: grid; grid-template-columns: repeat(4, 1fr); gap: 16px; }
+.narrow { margin-top:60px; }
-.layout { margin-top: 16px; display: grid; grid-template-columns: 290px 1fr 360px; gap: 16px; }
+.tab-row { display:flex; gap:10px; margin:16px 0; flex-wrap:wrap; }
-.card { background: var(--card); border: 1px solid var(--border); border-radius: 18px; padding: 16px; }
+.tab-row button, button { border:1px solid var(--border); background:white; border-radius:12px; padding:10px 14px; cursor:pointer; }
-.semantic-card { grid-column: span 4; }
+.active-tab, .primary { background:var(--accent); color:white; border-color:var(--accent); }
-.sidebar, .content, .rightbar { display: flex; flex-direction: column; gap: 16px; }
+.layout { display:grid; gap:16px; }
-.concept-btn { width: 100%; text-align: left; display: flex; justify-content: space-between; gap: 8px; margin-bottom: 10px; }
+.twocol { grid-template-columns:1fr 1fr; }
-.concept-btn.active { border-color: var(--accent); box-shadow: 0 0 0 2px rgba(45,108,223,0.08); }
+.onecol { grid-template-columns:1fr; }
-.status-pill { font-size: 12px; padding: 4px 8px; border-radius: 999px; border: 1px solid var(--border); white-space: nowrap; }
+.steps-stack { display:grid; gap:14px; }
-.status-trusted { background: #e7f7ec; }
+.step-card { border:1px solid var(--border); border-radius:16px; padding:14px; background:#fcfdff; }
-.status-provisional { background: #fff6df; }
+.step-header { display:flex; justify-content:space-between; gap:12px; align-items:start; }
-.status-rejected { background: #fde9e9; }
+.reward-pill { background:var(--soft); border:1px solid var(--border); border-radius:999px; padding:8px 10px; font-size:12px; }
-.status-needs_review { background: #eef2f7; }
+.muted { color:var(--muted); }
-label { display: block; font-weight: 600; margin-bottom: 12px; }
+.error { color:#b42318; margin-top:10px; }
-input, textarea, select { width: 100%; margin-top: 6px; border: 1px solid var(--border); border-radius: 10px; padding: 10px; font: inherit; background: white; }
+.message { margin-top:10px; padding:10px 12px; border:1px solid var(--border); background:#fff7dd; border-radius:12px; }
-.small { color: var(--muted); }
+.table { width:100%; border-collapse:collapse; }
-.conflict { border-top: 1px solid var(--border); padding-top: 12px; margin-top: 12px; }
+.table th, .table td { border-bottom:1px solid var(--border); text-align:left; padding:8px; vertical-align:top; }
-ul { padding-left: 18px; }
+.prebox { background:#f7f8fa; border:1px solid var(--border); border-radius:12px; padding:12px; overflow:auto; max-height:420px; }
-.button-row { display: flex; gap: 10px; }
+.form-grid { display:grid; grid-template-columns:1fr 1fr; gap:12px; }
-.checkline { display: flex; gap: 10px; align-items: center; }
+.full { grid-column:1 / -1; }
-.checkline input { width: auto; margin-top: 0; }
+.checkrow { display:flex; gap:16px; flex-wrap:wrap; align-items:center; }
+details summary { cursor:pointer; color:var(--accent); }
 @media (max-width:1100px) {
-  .summary-grid, .preview-grid { grid-template-columns: repeat(2, 1fr); }
+  .hero { flex-direction:column; }
-  .semantic-card { grid-column: span 2; }
+  .twocol, .form-grid { grid-template-columns:1fr; }
-  .layout { grid-template-columns: 1fr; }
 }