Apply ZIP update: 170-didactopus-auth-db-async-evaluator-prototype.zip [2026-03-14T13:20:10]

pyproject.toml

@@ -6,10 +6,18 @@ build-backend = "setuptools.build_meta"
 name = "didactopus"
 version = "0.1.0"
 requires-python = ">=3.10"
-dependencies = ["pydantic>=2.7", "pyyaml>=6.0"]
+dependencies = [
+  "pydantic>=2.7",
+  "pyyaml>=6.0",
+  "fastapi>=0.115",
+  "uvicorn>=0.30",
+  "sqlalchemy>=2.0",
+  "passlib[bcrypt]>=1.7"
+]
 
 [project.scripts]
-didactopus-build-attribution = "didactopus.attribution_builder:main"
+didactopus-api = "didactopus.api:main"
+didactopus-seed-db = "didactopus.seed:main"
 
 [tool.setuptools.packages.find]
 where = ["src"]

src/didactopus/api.py

@@ -2,78 +2,77 @@ from __future__ import annotations
 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 LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState, MediaRenderRequest
+from .models import LoginRequest, LoginResponse, CreateLearnerRequest, LearnerState, EvidenceEvent, EvaluatorSubmission, EvaluatorJobStatus
 from .repository import (
-    authenticate_user, get_user_by_id, store_refresh_token, refresh_token_active, revoke_refresh_token,
+    authenticate_user, get_user_by_token, list_packs, get_pack, create_learner,
-    list_packs_for_user, get_pack, get_pack_row, create_learner, learner_owned_by_user, load_learner_state, save_learner_state,
+    learner_owned_by_user, load_learner_state, save_learner_state,
-    create_render_job, update_render_job, list_render_jobs, list_artifacts
+    create_evaluator_job, get_evaluator_job, update_evaluator_job
 )
-from .auth import issue_access_token, issue_refresh_token, decode_token, new_token_id
+from .engine import apply_evidence, recommend_next
-from .engine import build_graph_frames, stable_layout
-from .worker import process_render_job
 
+settings = load_settings()
 Base.metadata.create_all(bind=engine)
 
 app = FastAPI(title="Didactopus API Prototype")
-app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 
 def current_user(authorization: str = Header(default="")):
     token = authorization.removeprefix("Bearer ").strip()
-    payload = decode_token(token) if token else None
+    user = get_user_by_token(token) if token else None
-    if not payload or payload.get("kind") != "access":
+    if user is None:
-        raise HTTPException(status_code=401, detail="Unauthorized")
-    user = get_user_by_id(int(payload["sub"]))
-    if user is None or not user.is_active:
         raise HTTPException(status_code=401, detail="Unauthorized")
     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")
 
-def ensure_pack_access(user, pack_id: str):
+def simulate_evaluator_job(job_id: int):
-    row = get_pack_row(pack_id)
+    job = get_evaluator_job(job_id)
-    if row is None:
+    if job is None:
-        raise HTTPException(status_code=404, detail="Pack not found")
+        return
-    if user.role == "admin":
+    update_evaluator_job(job_id, "running")
-        return row
+    score = 0.78 if len(job.submitted_text.strip()) > 20 else 0.62
-    if row.policy_lane == "community":
+    confidence_hint = 0.72 if len(job.submitted_text.strip()) > 20 else 0.45
-        return row
+    notes = "Prototype evaluator: longer responses scored somewhat higher."
-    if row.owner_user_id == user.id:
+    update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes)
-        return row
+    state = load_learner_state(job.learner_id)
-    raise HTTPException(status_code=403, detail="Pack not accessible by this user")
+    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)
 
-@app.post("/api/login", response_model=TokenPair)
+@app.post("/api/login", response_model=LoginResponse)
 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()
+    return LoginResponse(token=user.token, username=user.username)
-    store_refresh_token(user.id, token_id)
-    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)
-
-@app.post("/api/refresh", response_model=TokenPair)
-def refresh(payload: RefreshRequest):
-    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_for_user(user.id, include_unpublished=(user.role == "admin"))]
+    return [p.model_dump() for p in list_packs()]
+
+@app.get("/api/packs/{pack_id}")
+def api_get_pack(pack_id: str, user = Depends(current_user)):
+    pack = get_pack(pack_id)
+    if pack is None:
+        raise HTTPException(status_code=404, detail="Pack not found")
+    return pack.model_dump()
 
 @app.post("/api/learners")
 def api_create_learner(payload: CreateLearnerRequest, user = Depends(current_user)):
@@ -92,54 +91,45 @@ def api_put_learner_state(learner_id: str, state: LearnerState, user = Depends(c
         raise HTTPException(status_code=400, detail="Learner ID mismatch")
     return save_learner_state(state).model_dump()
 
-@app.get("/api/packs/{pack_id}/layout")
+@app.post("/api/learners/{learner_id}/evidence")
-def api_pack_layout(pack_id: str, user = Depends(current_user)):
+def api_post_evidence(learner_id: str, event: EvidenceEvent, user = Depends(current_user)):
-    ensure_pack_access(user, pack_id)
-    pack = get_pack(pack_id)
-    return {"pack_id": pack_id, "layout": stable_layout(pack)} if pack else {"pack_id": pack_id, "layout": {}}
-
-@app.get("/api/learners/{learner_id}/graph-animation/{pack_id}")
-def api_graph_animation(learner_id: str, pack_id: str, user = Depends(current_user)):
     ensure_learner_access(user, learner_id)
-    ensure_pack_access(user, pack_id)
-    pack = get_pack(pack_id)
     state = load_learner_state(learner_id)
-    frames = build_graph_frames(state, pack)
+    state = apply_evidence(state, event)
-    return {
+    save_learner_state(state)
-        "learner_id": learner_id,
+    return state.model_dump()
-        "pack_id": pack_id,
-        "pack_title": pack.title if pack else "",
-        "frames": frames,
-        "concepts": [{"id": c.id, "title": c.title, "prerequisites": c.prerequisites, "cross_pack_links": [l.model_dump() for l in c.cross_pack_links]} for c in pack.concepts] if pack else [],
-    }
 
-@app.post("/api/learners/{learner_id}/render-jobs/{pack_id}")
+@app.get("/api/learners/{learner_id}/recommendations/{pack_id}")
-def api_render_job(learner_id: str, pack_id: str, payload: MediaRenderRequest, background_tasks: BackgroundTasks, user = Depends(current_user)):
+def api_get_recommendations(learner_id: str, pack_id: str, user = Depends(current_user)):
     ensure_learner_access(user, learner_id)
-    ensure_pack_access(user, pack_id)
-    pack = get_pack(pack_id)
     state = load_learner_state(learner_id)
-    animation = {
+    pack = get_pack(pack_id)
-        "learner_id": learner_id,
+    if pack is None:
-        "pack_id": pack_id,
+        raise HTTPException(status_code=404, detail="Pack not found")
-        "pack_title": pack.title if pack else "",
+    return {"cards": recommend_next(state, pack)}
-        "frames": build_graph_frames(state, pack),
-    }
-    job_id = create_render_job(learner_id, pack_id, payload.format, payload.fps, payload.theme)
-    background_tasks.add_task(process_render_job, job_id, learner_id, pack_id, payload.format, payload.fps, payload.theme, animation)
-    return {"job_id": job_id, "status": "queued"}
 
-@app.get("/api/render-jobs")
+@app.post("/api/learners/{learner_id}/evaluator-jobs", response_model=EvaluatorJobStatus)
-def api_list_render_jobs(learner_id: str | None = None, user = Depends(current_user)):
+def api_submit_evaluator_job(learner_id: str, payload: EvaluatorSubmission, background_tasks: BackgroundTasks, user = Depends(current_user)):
-    if learner_id:
     ensure_learner_access(user, learner_id)
-    return list_render_jobs(learner_id)
+    job_id = create_evaluator_job(learner_id, payload.pack_id, payload.concept_id, payload.submitted_text)
+    background_tasks.add_task(simulate_evaluator_job, job_id)
+    return EvaluatorJobStatus(job_id=job_id, status="queued")
 
-@app.get("/api/artifacts")
+@app.get("/api/evaluator-jobs/{job_id}", response_model=EvaluatorJobStatus)
-def api_list_artifacts(learner_id: str | None = None, user = Depends(current_user)):
+def api_get_evaluator_job(job_id: int, user = Depends(current_user)):
-    if learner_id:
+    job = get_evaluator_job(job_id)
-        ensure_learner_access(user, learner_id)
+    if job is None:
-    return list_artifacts(learner_id)
+        raise HTTPException(status_code=404, detail="Job not found")
+    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,
+    )
 
 def main():
-    uvicorn.run(app, host="127.0.0.1", port=8011)
+    uvicorn.run(app, host=settings.host, port=settings.port)
+
+if __name__ == "__main__":
+    main()

src/didactopus/auth.py

@@ -1,12 +1,8 @@
 from __future__ import annotations
-from datetime import datetime, timedelta, timezone
-from jose import jwt, JWTError
-from passlib.context import CryptContext
 import secrets
-from .config import load_settings
+from passlib.context import CryptContext
 
 pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
-settings = load_settings()
 
 def hash_password(password: str) -> str:
     return pwd_context.hash(password)
@@ -14,22 +10,5 @@ def hash_password(password: str) -> str:
 def verify_password(password: str, password_hash: str) -> bool:
     return pwd_context.verify(password, password_hash)
 
-def _encode_token(payload: dict, expires_delta: timedelta) -> str:
+def issue_token() -> str:
-    to_encode = dict(payload)
-    to_encode["exp"] = datetime.now(timezone.utc) + expires_delta
-    return jwt.encode(to_encode, settings.jwt_secret, algorithm=settings.jwt_algorithm)
-
-def issue_access_token(user_id: int, username: str, role: str) -> str:
-    return _encode_token({"sub": str(user_id), "username": username, "role": role, "kind": "access"}, timedelta(minutes=30))
-
-def issue_refresh_token(user_id: int, username: str, role: str, token_id: str) -> str:
-    return _encode_token({"sub": str(user_id), "username": username, "role": role, "kind": "refresh", "jti": token_id}, timedelta(days=14))
-
-def decode_token(token: str) -> dict | None:
-    try:
-        return jwt.decode(token, settings.jwt_secret, algorithms=[settings.jwt_algorithm])
-    except JWTError:
-        return None
-
-def new_token_id() -> str:
     return secrets.token_urlsafe(24)

src/didactopus/config.py

@@ -1,13 +1,10 @@
-from __future__ import annotations
+from pathlib import Path
-import os
 from pydantic import BaseModel
 
 class Settings(BaseModel):
-    database_url: str = os.getenv("DIDACTOPUS_DATABASE_URL", "sqlite+pysqlite:///:memory:")
+    database_url: str = "sqlite:///./didactopus.db"
-    host: str = os.getenv("DIDACTOPUS_HOST", "127.0.0.1")
+    host: str = "127.0.0.1"
-    port: int = int(os.getenv("DIDACTOPUS_PORT", "8011"))
+    port: int = 8011
-    jwt_secret: str = os.getenv("DIDACTOPUS_JWT_SECRET", "change-me")
-    jwt_algorithm: str = "HS256"
 
 def load_settings() -> Settings:
     return Settings()

src/didactopus/db.py

@@ -3,6 +3,7 @@ from sqlalchemy.orm import declarative_base, sessionmaker
 from .config import load_settings
 
 settings = load_settings()
-engine = create_engine(settings.database_url, future=True)
+connect_args = {"check_same_thread": False} if settings.database_url.startswith("sqlite") else {}
+engine = create_engine(settings.database_url, future=True, connect_args=connect_args)
 SessionLocal = sessionmaker(bind=engine, autoflush=False, autocommit=False, future=True)
 Base = declarative_base()

src/didactopus/engine.py

@@ -1,110 +1,97 @@
 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(
-    depths = concept_depths(pack)
+    state: LearnerState,
-    layers = defaultdict(list)
+    event: EvidenceEvent,
-    for c in pack.concepts:
+    decay: float = 0.05,
-        layers[depths.get(c.id, 0)].append(c)
+    reinforcement: float = 0.25,
-    positions = {}
+) -> LearnerState:
-    max_depth = max(layers.keys()) if layers else 0
+    rec = get_record(state, event.concept_id, event.dimension)
-    for d in sorted(layers):
+    if rec is None:
-        nodes = sorted(layers[d], key=lambda c: c.id)
+        rec = MasteryRecord(
-        y = 90 + d * ((height - 160) / max(1, max_depth))
+            concept_id=event.concept_id,
-        for idx, node in enumerate(nodes):
+            dimension=event.dimension,
-            if node.position is not None:
+            score=0.0,
-                positions[node.id] = {"x": node.position.x, "y": node.position.y, "source": "pack_authored"}
+            confidence=0.0,
-            else:
+            evidence_count=0,
-                spacing = width / (len(nodes) + 1)
+            last_updated=event.timestamp,
-                x = spacing * (idx + 1)
+        )
-                positions[node.id] = {"x": x, "y": y, "source": "auto_layered"}
+        state.records.append(rec)
-    return positions
 
-def prereqs_satisfied(scores: dict[str, float], concept, min_score: float = 0.65) -> bool:
+    weight = max(0.05, min(1.0, event.confidence_hint))
+    rec.score = ((rec.score * rec.evidence_count) + (event.score * weight)) / max(1, rec.evidence_count + 1)
+    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))),
+    )
+    rec.evidence_count += 1
+    rec.last_updated = event.timestamp
+    state.history.append(event)
+    return state
+
+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": (
-        "relationship": link.relationship,
+                    "Prerequisites are satisfied, so this is the best next unlock."
-        "kind": "cross_pack"
+                    if status == "available"
-    } for c in pack.concepts for link in c.cross_pack_links]
+                    else "You have started this concept, but mastery is not yet secure."
-    for idx, ev in enumerate(history):
+                ),
-        if ev.concept_id in scores:
+                "why": [
-            scores[ev.concept_id] = ev.score
+                    "Prerequisite check passed",
-        nodes = []
+                    f"Current score: {rec.score:.2f}" if rec else "No evidence recorded yet",
-        for cid, concept in concepts.items():
+                    f"Current confidence: {rec.confidence:.2f}" if rec else "Confidence starts after your first exercise",
-            score = scores.get(cid, 0.0)
+                ],
-            status = concept_status(scores, concept)
+                "reward": concept.exerciseReward or f"{concept.title} progress recorded",
-            pos = layout[cid]
+                "conceptId": concept.id,
-            nodes.append({
+                "scoreHint": 0.82 if status == "available" else 0.76,
-                "id": cid,
+                "confidenceHint": 0.72 if status == "available" else 0.55,
-                "title": concept.title,
-                "score": score,
-                "status": status,
-                "size": 20 + int(score * 30),
-                "x": pos["x"],
-                "y": pos["y"],
-                "layout_source": pos["source"],
             })
-        frames.append({
+    for rec in state.records:
-            "index": idx,
+        if rec.dimension == "mastery" and rec.confidence < 0.40:
-            "timestamp": ev.timestamp,
+            concept = next((c for c in pack.concepts if c.id == rec.concept_id), None)
-            "event_kind": ev.kind,
+            if concept:
-            "focus_concept_id": ev.concept_id,
+                cards.append({
-            "nodes": nodes,
+                    "id": f"{concept.id}-reinforce",
-            "edges": static_edges,
+                    "title": f"Reinforce {concept.title}",
-            "cross_pack_links": static_cross,
+                    "minutes": 8,
+                    "reason": "Your score is promising, but confidence is still thin.",
+                    "why": [
+                        f"Confidence {rec.confidence:.2f} is below reinforcement threshold",
+                        "A small fresh exercise can stabilize recall",
+                    ],
+                    "reward": "Confidence ring grows",
+                    "conceptId": concept.id,
+                    "scoreHint": max(0.60, rec.score),
+                    "confidenceHint": 0.30,
                 })
-    if not frames:
+    return cards[:4]
-        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

@@ -1,29 +1,8 @@
 from __future__ import annotations
 from pydantic import BaseModel, Field
+from typing import Literal
 
-class TokenPair(BaseModel):
+EvidenceKind = Literal["checkpoint", "project", "exercise", "review"]
-    access_token: str
-    refresh_token: str
-    token_type: str = "bearer"
-    username: str
-    role: str
-
-class LoginRequest(BaseModel):
-    username: str
-    password: str
-
-class RefreshRequest(BaseModel):
-    refresh_token: str
-
-class GraphPosition(BaseModel):
-    x: float
-    y: float
-
-class CrossPackLink(BaseModel):
-    source_concept_id: str
-    target_pack_id: str
-    target_concept_id: str
-    relationship: str = "related"
 
 class PackConcept(BaseModel):
     id: str
@@ -31,8 +10,13 @@ class PackConcept(BaseModel):
     prerequisites: list[str] = Field(default_factory=list)
     masteryDimension: str = "mastery"
     exerciseReward: str = ""
-    position: GraphPosition | None = None
+
-    cross_pack_links: list[CrossPackLink] = Field(default_factory=list)
+class PackCompliance(BaseModel):
+    sources: int = 0
+    attributionRequired: bool = False
+    shareAlikeRequired: bool = False
+    noncommercialOnly: bool = False
+    flags: list[str] = Field(default_factory=list)
 
 class PackData(BaseModel):
     id: str
@@ -41,11 +25,7 @@ class PackData(BaseModel):
     level: str = "novice-friendly"
     concepts: list[PackConcept] = Field(default_factory=list)
     onboarding: dict = Field(default_factory=dict)
-    compliance: dict = Field(default_factory=dict)
+    compliance: PackCompliance = Field(default_factory=PackCompliance)
-
-class CreateLearnerRequest(BaseModel):
-    learner_id: str
-    display_name: str = ""
 
 class MasteryRecord(BaseModel):
     concept_id: str
@@ -61,7 +41,7 @@ class EvidenceEvent(BaseModel):
     score: float
     confidence_hint: float = 0.5
     timestamp: str
-    kind: str = "exercise"
+    kind: EvidenceKind = "exercise"
     source_id: str = ""
 
 class LearnerState(BaseModel):
@@ -69,9 +49,27 @@ class LearnerState(BaseModel):
     records: list[MasteryRecord] = Field(default_factory=list)
     history: list[EvidenceEvent] = Field(default_factory=list)
 
-class MediaRenderRequest(BaseModel):
+class LoginRequest(BaseModel):
+    username: str
+    password: str
+
+class LoginResponse(BaseModel):
+    token: str
+    username: str
+
+class CreateLearnerRequest(BaseModel):
     learner_id: str
+    display_name: str = ""
+
+class EvaluatorSubmission(BaseModel):
     pack_id: str
-    format: str = "gif"
+    concept_id: str
-    fps: int = 2
+    submitted_text: str
-    theme: str = "default"
+    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

@@ -1,5 +1,5 @@
-from sqlalchemy import String, Integer, Float, ForeignKey, Text, Boolean
+from sqlalchemy import String, Integer, Float, Boolean, ForeignKey, Text
-from sqlalchemy.orm import Mapped, mapped_column
+from sqlalchemy.orm import Mapped, mapped_column, relationship
 from .db import Base
 
 class UserORM(Base):
@@ -7,32 +7,22 @@ class UserORM(Base):
     id: Mapped[int] = mapped_column(Integer, primary_key=True)
     username: Mapped[str] = mapped_column(String(100), unique=True, index=True)
     password_hash: Mapped[str] = mapped_column(String(255))
-    role: Mapped[str] = mapped_column(String(50), default="learner")
+    token: Mapped[str] = mapped_column(String(255), unique=True, index=True)
-    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)
 
 class LearnerORM(Base):
     __tablename__ = "learners"
     id: Mapped[str] = mapped_column(String(100), primary_key=True)
     owner_user_id: Mapped[int] = mapped_column(ForeignKey("users.id"), index=True)
     display_name: Mapped[str] = mapped_column(String(255), default="")
+    owner = relationship("UserORM")
 
 class MasteryRecordORM(Base):
     __tablename__ = "mastery_records"
@@ -44,6 +34,7 @@ class MasteryRecordORM(Base):
     confidence: Mapped[float] = mapped_column(Float, default=0.0)
     evidence_count: Mapped[int] = mapped_column(Integer, default=0)
     last_updated: Mapped[str] = mapped_column(String(100), default="")
+    learner = relationship("LearnerORM")
 
 class EvidenceEventORM(Base):
     __tablename__ = "evidence_events"
@@ -56,30 +47,18 @@ class EvidenceEventORM(Base):
     timestamp: Mapped[str] = mapped_column(String(100), default="")
     kind: Mapped[str] = mapped_column(String(50), default="exercise")
     source_id: Mapped[str] = mapped_column(String(255), default="")
+    learner = relationship("LearnerORM")
 
-class RenderJobORM(Base):
+class EvaluatorJobORM(Base):
-    __tablename__ = "render_jobs"
+    __tablename__ = "evaluator_jobs"
     id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    learner_id: Mapped[str] = mapped_column(String(100), index=True)
+    learner_id: Mapped[str] = mapped_column(ForeignKey("learners.id"), index=True)
-    pack_id: Mapped[str] = mapped_column(String(100), index=True)
+    pack_id: Mapped[str] = mapped_column(ForeignKey("packs.id"), index=True)
-    requested_format: Mapped[str] = mapped_column(String(20), default="gif")
+    concept_id: Mapped[str] = mapped_column(String(100), index=True)
-    fps: Mapped[int] = mapped_column(Integer, default=2)
+    submitted_text: Mapped[str] = mapped_column(Text, default="")
-    theme: Mapped[str] = mapped_column(String(100), default="default")
     status: Mapped[str] = mapped_column(String(50), default="queued")
-    bundle_dir: Mapped[str] = mapped_column(Text, default="")
+    result_score: Mapped[float | None] = mapped_column(Float, nullable=True)
-    payload_json: Mapped[str] = mapped_column(Text, default="")
+    result_confidence_hint: Mapped[float | None] = mapped_column(Float, nullable=True)
-    manifest_path: Mapped[str] = mapped_column(Text, default="")
+    result_notes: Mapped[str] = mapped_column(Text, default="")
-    script_path: Mapped[str] = mapped_column(Text, default="")
+    learner = relationship("LearnerORM")
-    error_text: Mapped[str] = mapped_column(Text, default="")
+    pack = relationship("PackORM")
-
-class ArtifactORM(Base):
-    __tablename__ = "artifacts"
-    id: Mapped[int] = mapped_column(Integer, primary_key=True)
-    render_job_id: Mapped[int] = mapped_column(ForeignKey("render_jobs.id"), index=True)
-    learner_id: Mapped[str] = mapped_column(String(100), index=True)
-    pack_id: Mapped[str] = mapped_column(String(100), index=True)
-    artifact_type: Mapped[str] = mapped_column(String(50), default="render_bundle")
-    format: Mapped[str] = mapped_column(String(20), default="gif")
-    title: Mapped[str] = mapped_column(String(255), default="")
-    path: Mapped[str] = mapped_column(Text, default="")
-    metadata_json: Mapped[str] = mapped_column(Text, default="{}")

src/didactopus/repository.py

@@ -2,92 +2,36 @@ from __future__ import annotations
 import json
 from sqlalchemy import select
 from .db import SessionLocal
-from .orm import UserORM, RefreshTokenORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM
+from .orm import UserORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM, EvaluatorJobORM
 from .models import PackData, LearnerState, MasteryRecord, EvidenceEvent
 from .auth import verify_password
 
-def get_user_by_username(username: str):
+def get_user_by_token(token: str) -> UserORM | None:
     with SessionLocal() as db:
-        return db.execute(select(UserORM).where(UserORM.username == username)).scalar_one_or_none()
+        return db.execute(select(UserORM).where(UserORM.token == token)).scalar_one_or_none()
 
-def get_user_by_id(user_id: int):
+def authenticate_user(username: str, password: str) -> UserORM | None:
     with SessionLocal() as db:
-        return db.get(UserORM, user_id)
+        user = db.execute(select(UserORM).where(UserORM.username == username)).scalar_one_or_none()
-
+        if user is None:
-def authenticate_user(username: str, password: str):
+            return None
-    user = get_user_by_username(username)
+        if not verify_password(password, user.password_hash):
-    if user is None or not verify_password(password, user.password_hash) or not user.is_active:
             return None
         return user
 
-def store_refresh_token(user_id: int, token_id: str):
+def list_packs() -> list[PackData]:
     with SessionLocal() as db:
-        db.add(RefreshTokenORM(user_id=user_id, token_id=token_id, is_revoked=False))
+        rows = db.execute(select(PackORM)).scalars().all()
-        db.commit()
+        return [PackData.model_validate(json.loads(r.data_json)) for r in rows]
 
-def refresh_token_active(token_id: str) -> bool:
+def get_pack(pack_id: str) -> PackData | None:
-    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_for_user(user_id: int | None = None, 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()
-        out = []
-        for r in rows:
-            if r.policy_lane == "community":
-                out.append(PackData.model_validate(json.loads(r.data_json)))
-            elif user_id is not None and r.owner_user_id == user_id:
-                out.append(PackData.model_validate(json.loads(r.data_json)))
-        return out
-
-def get_pack(pack_id: str):
     with SessionLocal() as db:
         row = db.get(PackORM, pack_id)
-        return None if row is None else PackData.model_validate(json.loads(row.data_json))
-
-def get_pack_row(pack_id: str):
-    with SessionLocal() as db:
-        return db.get(PackORM, pack_id)
-
-def upsert_pack(pack: PackData, submitted_by_user_id: int, policy_lane: str = "personal", is_published: bool = False):
-    with SessionLocal() as db:
-        row = db.get(PackORM, pack.id)
-        payload = json.dumps(pack.model_dump())
         if row is None:
-            row = PackORM(
+            return None
-                id=pack.id,
+        return PackData.model_validate(json.loads(row.data_json))
-                owner_user_id=submitted_by_user_id if policy_lane == "personal" else None,
-                policy_lane=policy_lane,
-                title=pack.title,
-                subtitle=pack.subtitle,
-                level=pack.level,
-                data_json=payload,
-                is_published=is_published if policy_lane == "personal" else False,
-            )
-            db.add(row)
-        else:
-            row.owner_user_id = submitted_by_user_id if policy_lane == "personal" else row.owner_user_id
-            row.policy_lane = policy_lane
-            row.title = pack.title
-            row.subtitle = pack.subtitle
-            row.level = pack.level
-            row.data_json = payload
-            if policy_lane == "personal":
-                row.is_published = is_published
-        db.commit()
 
-def create_learner(owner_user_id: int, learner_id: str, display_name: str = ""):
+def create_learner(owner_user_id: int, learner_id: str, display_name: str = "") -> None:
     with SessionLocal() as db:
         if db.get(LearnerORM, learner_id) is None:
             db.add(LearnerORM(id=learner_id, owner_user_id=owner_user_id, display_name=display_name))
@@ -98,23 +42,89 @@ def learner_owned_by_user(user_id: int, learner_id: str) -> bool:
         learner = db.get(LearnerORM, learner_id)
         return learner is not None and learner.owner_user_id == user_id
 
-def load_learner_state(learner_id: str):
+def load_learner_state(learner_id: str) -> LearnerState:
     with SessionLocal() as db:
         records = db.execute(select(MasteryRecordORM).where(MasteryRecordORM.learner_id == learner_id)).scalars().all()
         history = db.execute(select(EvidenceEventORM).where(EvidenceEventORM.learner_id == learner_id)).scalars().all()
         return LearnerState(
             learner_id=learner_id,
-            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],
+            records=[
-            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],
+                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
+            ],
+            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
+            ]
         )
 
-def save_learner_state(state: LearnerState):
+def save_learner_state(state: LearnerState) -> LearnerState:
     with SessionLocal() as db:
+        db.execute(select(LearnerORM).where(LearnerORM.id == state.learner_id))
         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))
+            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.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()
     return state
+
+def create_evaluator_job(learner_id: str, pack_id: str, concept_id: str, submitted_text: str) -> int:
+    with SessionLocal() as db:
+        job = EvaluatorJobORM(
+            learner_id=learner_id,
+            pack_id=pack_id,
+            concept_id=concept_id,
+            submitted_text=submitted_text,
+            status="queued",
+        )
+        db.add(job)
+        db.commit()
+        db.refresh(job)
+        return job.id
+
+def get_evaluator_job(job_id: int) -> EvaluatorJobORM | None:
+    with SessionLocal() as db:
+        return db.get(EvaluatorJobORM, job_id)
+
+def update_evaluator_job(job_id: int, status: str, score: float | None = None, confidence_hint: float | None = None, notes: str = "") -> None:
+    with SessionLocal() as db:
+        job = db.get(EvaluatorJobORM, job_id)
+        if job is None:
+            return
+        job.status = status
+        job.result_score = score
+        job.result_confidence_hint = confidence_hint
+        job.result_notes = notes
+        db.commit()

src/didactopus/seed.py

@@ -1,34 +1,79 @@
 from __future__ import annotations
-from sqlalchemy import select
+import json
 from .db import Base, engine, SessionLocal
-from .orm import UserORM
+from .orm import UserORM, PackORM
-from .auth import hash_password
+from .auth import hash_password, issue_token
-from .repository import upsert_pack, create_learner
+from sqlalchemy import select
-from .models import PackData, PackConcept, GraphPosition, CrossPackLink
+
+PACKS = [
+    {
+        "id": "bayes-pack",
+        "title": "Bayesian Reasoning",
+        "subtitle": "Probability, evidence, updating, and model criticism.",
+        "level": "novice-friendly",
+        "concepts": [
+            {"id": "prior", "title": "Prior", "prerequisites": [], "masteryDimension": "mastery", "exerciseReward": "Prior badge earned"},
+            {"id": "posterior", "title": "Posterior", "prerequisites": ["prior"], "masteryDimension": "mastery", "exerciseReward": "Posterior path opened"},
+            {"id": "model-checking", "title": "Model Checking", "prerequisites": ["posterior"], "masteryDimension": "mastery", "exerciseReward": "Model-checking unlocked"}
+        ],
+        "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": {
+            "sources": 2,
+            "attributionRequired": True,
+            "shareAlikeRequired": True,
+            "noncommercialOnly": True,
+            "flags": ["share-alike", "noncommercial", "excluded-third-party-content"]
+        }
+    },
+    {
+        "id": "stats-pack",
+        "title": "Introductory Statistics",
+        "subtitle": "Descriptive statistics, sampling, and inference.",
+        "level": "novice-friendly",
+        "concepts": [
+            {"id": "descriptive", "title": "Descriptive Statistics", "prerequisites": [], "masteryDimension": "mastery", "exerciseReward": "Descriptive tools unlocked"},
+            {"id": "sampling", "title": "Sampling", "prerequisites": ["descriptive"], "masteryDimension": "mastery", "exerciseReward": "Sampling pathway opened"},
+            {"id": "inference", "title": "Inference", "prerequisites": ["sampling"], "masteryDimension": "mastery", "exerciseReward": "Inference challenge unlocked"}
+        ],
+        "onboarding": {
+            "headline": "Build your first useful data skill",
+            "body": "You will learn one concept that immediately helps you summarize real data.",
+            "checklist": [
+                "See one worked example",
+                "Compute one short example yourself",
+                "Explain what the result means"
+            ]
+        },
+        "compliance": {
+            "sources": 1,
+            "attributionRequired": True,
+            "shareAlikeRequired": False,
+            "noncommercialOnly": False,
+            "flags": []
+        }
+    }
+]
 
 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:
+        existing = db.execute(select(UserORM).where(UserORM.username == "wesley")).scalar_one_or_none()
-            db.add(UserORM(username="wesley", password_hash=hash_password("demo-pass"), role="admin", is_active=True))
+        if existing is None:
+            db.add(UserORM(username="wesley", password_hash=hash_password("demo-pass"), token=issue_token()))
+        for pack in PACKS:
+            row = db.get(PackORM, pack["id"])
+            if row is None:
+                db.add(PackORM(id=pack["id"], title=pack["title"], subtitle=pack["subtitle"], level=pack["level"], data_json=json.dumps(pack)))
         db.commit()
-    create_learner(1, "wesley-learner", "Wesley learner")
+    print("Seeded database. Demo user: wesley / demo-pass")
-    upsert_pack(
+
-        PackData(
+if __name__ == "__main__":
-            id="wesley-private-pack",
+    main()
-            title="Wesley Private Pack",
-            subtitle="Personal pack example.",
-            level="novice-friendly",
-            concepts=[
-                PackConcept(id="intro", title="Intro", prerequisites=[], position=GraphPosition(x=150, y=120)),
-                PackConcept(id="second", title="Second concept", prerequisites=["intro"], position=GraphPosition(x=420, y=120)),
-                PackConcept(id="third", title="Third concept", prerequisites=["second"], position=GraphPosition(x=700, y=120), cross_pack_links=[CrossPackLink(source_concept_id="third", target_pack_id="advanced-pack", target_concept_id="adv-1", relationship="next_pack")]),
-                PackConcept(id="branch", title="Branch concept", prerequisites=["intro"], position=GraphPosition(x=420, y=320)),
-            ],
-            onboarding={"headline":"Start privately"},
-            compliance={}
-        ),
-        submitted_by_user_id=1,
-        policy_lane="personal",
-        is_published=True,
-    )

webui/index.html

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

webui/package.json

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

webui/src/App.jsx

@@ -1,150 +1,235 @@
-import React, { useEffect, useState } from "react";
+import React, { useEffect, useMemo, useState } from "react";
-import { login, refresh, fetchPacks, fetchLearnerState, putLearnerState, createRenderJob, listRenderJobs, listArtifacts } from "./api";
+import { login, fetchPacks, createLearner, fetchLearnerState, fetchRecommendations, postEvidence, submitEvaluatorJob, fetchEvaluatorJob } from "./api";
-import { loadAuth, saveAuth, clearAuth } from "./authStore";
+import { buildMasteryMap, progressPercent } from "./localEngine";
 
-function LoginView({ onAuth }) {
+function LoginPanel({ onLogin }) {
   const [username, setUsername] = useState("wesley");
   const [password, setPassword] = useState("demo-pass");
   const [error, setError] = useState("");
-  async function doLogin() {
+
+  async function handleLogin() {
     try {
-      const result = await login(username, password);
+      setError("");
-      saveAuth(result);
+      const result = await onLogin(username, password);
-      onAuth(result);
+      return result;
-    } catch { setError("Login failed"); }
+    } catch (e) {
+      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>
+      <button className="primary" onClick={handleLogin}>Login</button>
       {error ? <div className="error">{error}</div> : null}
     </section>
+  );
+}
+
+function DomainCard({ domain, selected, onSelect }) {
+  return (
+    <button className={`domain-card ${selected ? "selected" : ""}`} onClick={() => onSelect(domain.id)}>
+      <div className="domain-title">{domain.title}</div>
+      <div className="domain-subtitle">{domain.subtitle}</div>
+    </button>
+  );
+}
+
+function NextStepCard({ step, onSimulate }) {
+  return (
+    <div className="step-card">
+      <div className="step-header">
+        <div>
+          <h3>{step.title}</h3>
+          <div className="muted">{step.minutes} minutes</div>
+        </div>
+        <div className="reward-pill">{step.reward}</div>
+      </div>
+      <p>{step.reason}</p>
+      <details>
+        <summary>Why this is recommended</summary>
+        <ul>{step.why.map((item, idx) => <li key={idx}>{item}</li>)}</ul>
+      </details>
+      <div className="button-row">
+        <button className="primary" onClick={() => onSimulate(step)}>Simulate step</button>
+      </div>
     </div>
   );
 }
 
 export default function App() {
-  const [auth, setAuth] = useState(loadAuth());
+  const [token, setToken] = useState("");
+  const [username, setUsername] = useState("");
   const [packs, setPacks] = useState([]);
-  const [learnerId] = useState("wesley-learner");
+  const [selectedDomainId, setSelectedDomainId] = useState("");
-  const [packId, setPackId] = useState("");
+  const [learnerId, setLearnerId] = useState("wesley-learner");
-  const [jobs, setJobs] = useState([]);
+  const [learnerState, setLearnerState] = useState(null);
-  const [artifacts, setArtifacts] = useState([]);
+  const [cards, setCards] = useState([]);
-  const [format, setFormat] = useState("gif");
+  const [jobStatus, setJobStatus] = useState(null);
-  const [fps, setFps] = useState(2);
-  const [message, setMessage] = useState("");
 
-  async function refreshAuthToken() {
+  async function handleLogin(user, pass) {
-    if (!auth?.refresh_token) return null;
+    const auth = await login(user, pass);
-    try {
+    setToken(auth.token);
-      const result = await refresh(auth.refresh_token);
+    setUsername(auth.username);
-      saveAuth(result);
+    await createLearner(auth.token, learnerId, learnerId);
-      setAuth(result);
+    const loadedPacks = await fetchPacks(auth.token);
-      return result;
+    setPacks(loadedPacks);
-    } catch {
+    setSelectedDomainId(loadedPacks[0]?.id || "");
-      clearAuth();
+    const state = await fetchLearnerState(auth.token, learnerId);
-      setAuth(null);
+    setLearnerState(state);
-      return null;
+    return auth;
-    }
-  }
-
-  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);
-    }
-  }
-
-  async function reloadLists() {
-    setJobs(await guarded((token) => listRenderJobs(token, learnerId)));
-    setArtifacts(await guarded((token) => listArtifacts(token, learnerId)));
   }
 
   useEffect(() => {
-    if (!auth) return;
+    async function loadCards() {
-    async function load() {
+      if (!token || !selectedDomainId) return;
-      const p = await guarded((token) => fetchPacks(token));
+      const data = await fetchRecommendations(token, learnerId, selectedDomainId);
-      setPacks(p);
+      setCards(data.cards || []);
-      setPackId(p[0]?.id || "");
-      await reloadLists();
     }
-    load();
+    loadCards();
-  }, [auth]);
+  }, [token, learnerId, selectedDomainId, learnerState]);
 
-  async function generateDemo() {
+  const domain = useMemo(() => packs.find((d) => d.id === selectedDomainId) || null, [packs, selectedDomainId]);
-    let state = await guarded((token) => fetchLearnerState(token, learnerId));
+  const masteryMap = useMemo(() => domain && learnerState ? buildMasteryMap(learnerState, domain) : [], [learnerState, domain]);
-    const base = Date.now()
+  const progress = useMemo(() => domain && learnerState ? progressPercent(learnerState, domain) : 0, [learnerState, domain]);
-    const events = [
+
-      ["intro", 0.30, "exercise", 0],
+  async function simulateStep(step) {
-      ["intro", 0.78, "review", 1000],
+    const nextState = await postEvidence(token, learnerId, {
-      ["second", 0.42, "exercise", 2000],
+      concept_id: step.conceptId,
-      ["second", 0.72, "review", 3000],
+      dimension: "mastery",
-      ["third", 0.25, "exercise", 4000],
+      score: step.scoreHint,
-      ["branch", 0.60, "exercise", 5000],
+      confidence_hint: step.confidenceHint,
-    ];
+      timestamp: new Date().toISOString(),
-    const latest = {}
+      kind: "checkpoint",
-    for (const [cid, score, kind, offset] of events) {
+      source_id: `ui-${step.id}`
-      const ts = new Date(base + offset).toISOString();
+    });
-      state.history.push({ concept_id: cid, dimension: "mastery", score, confidence_hint: 0.6, timestamp: ts, kind, source_id: `demo-${cid}-${offset}` });
+    setLearnerState(nextState);
-      latest[cid] = { concept_id: cid, dimension: "mastery", score, confidence: Math.min(0.9, score), evidence_count: (latest[cid]?.evidence_count || 0) + 1, last_updated: ts };
-    }
-    state.records = Object.values(latest);
-    await guarded((token) => putLearnerState(token, learnerId, state));
-    setMessage("Demo state generated.");
   }
 
-  async function createJob() {
+  async function submitDemoEvaluator() {
-    const result = await guarded((token) => createRenderJob(token, learnerId, packId, { learner_id: learnerId, pack_id: packId, format, fps, theme: "default" }));
+    if (!domain) return;
-    setMessage(`Render job ${result.job_id} queued.`);
+    const firstConcept = domain.concepts[0]?.id;
-    setTimeout(() => reloadLists(), 500);
+    const job = await submitEvaluatorJob(token, learnerId, {
+      pack_id: domain.id,
+      concept_id: firstConcept,
+      submitted_text: "This is a moderately detailed learner response intended to trigger a somewhat better prototype evaluator score.",
+      kind: "checkpoint"
+    });
+    setJobStatus(job);
+    setTimeout(async () => {
+      const refreshed = await fetchEvaluatorJob(token, job.job_id);
+      setJobStatus(refreshed);
+      const state = await fetchLearnerState(token, learnerId);
+      setLearnerState(state);
+    }, 1200);
   }
 
-  if (!auth) return <LoginView onAuth={setAuth} />;
+  if (!token) {
+    return <div className="page"><LoginPanel onLogin={handleLogin} /></div>;
+  }
+
+  if (!domain || !learnerState) {
+    return <div className="page"><div className="card">Loading authenticated learner view...</div></div>;
+  }
 
   return (
     <div className="page">
       <header className="hero">
         <div>
-          <h1>Didactopus artifact registry</h1>
+          <h1>Didactopus learner prototype</h1>
-          <p>Track render jobs and produced media artifacts as first-class Didactopus objects.</p>
+          <p>Authenticated multi-user scaffold with DB-backed state and async evaluator jobs.</p>
-          <div className="muted">{message}</div>
+          <div className="muted">Signed in as {username}</div>
         </div>
-        <div className="controls">
+        <div className="hero-controls">
-          <label>Pack
+          <label>Learner ID<input value={learnerId} onChange={(e) => setLearnerId(e.target.value)} /></label>
-            <select value={packId} onChange={(e) => setPackId(e.target.value)}>
+          <button onClick={submitDemoEvaluator}>Submit demo evaluator job</button>
-              {packs.map((p) => <option key={p.id} value={p.id}>{p.title}</option>)}
-            </select>
-          </label>
-          <label>Format
-            <select value={format} onChange={(e) => setFormat(e.target.value)}>
-              <option value="gif">GIF</option>
-              <option value="mp4">MP4</option>
-            </select>
-          </label>
-          <label>FPS
-            <input type="number" value={fps} onChange={(e) => setFps(Number(e.target.value || 2))} />
-          </label>
-          <button onClick={generateDemo}>Generate demo state</button>
-          <button onClick={createJob}>Create render job</button>
-          <button onClick={reloadLists}>Refresh lists</button>
-          <button onClick={() => { clearAuth(); setAuth(null); }}>Logout</button>
         </div>
       </header>
 
-      <main className="layout twocol">
+      <section className="domain-grid">
-        <section className="card">
+        {packs.map((d) => <DomainCard key={d.id} domain={d} selected={d.id === domain.id} onSelect={setSelectedDomainId} />)}
-          <h2>Render jobs</h2>
-          <pre className="prebox">{JSON.stringify(jobs, null, 2)}</pre>
       </section>
+
+      <main className="layout">
+        <div className="left-col">
           <section className="card">
-          <h2>Artifacts</h2>
+            <h2>Onboarding</h2>
-          <pre className="prebox">{JSON.stringify(artifacts, null, 2)}</pre>
+            <h3>{domain.onboarding.headline}</h3>
+            <p>{domain.onboarding.body}</p>
+            <ul>{(domain.onboarding.checklist || []).map((item, idx) => <li key={idx}>{item}</li>)}</ul>
           </section>
+
+          <section className="card">
+            <h2>Visible mastery map</h2>
+            <div className="map-grid">
+              {masteryMap.map((node) => (
+                <div key={node.id} className={`map-node ${node.status}`}>
+                  <div className="node-label">{node.label}</div>
+                  <div className="node-status">{node.status}</div>
+                </div>
+              ))}
+            </div>
+          </section>
+
+          <section className="card">
+            <h2>Async evaluator job</h2>
+            {jobStatus ? (
+              <div>
+                <div><strong>Status:</strong> {jobStatus.status}</div>
+                <div><strong>Score:</strong> {jobStatus.result_score ?? "-"}</div>
+                <div><strong>Confidence hint:</strong> {jobStatus.result_confidence_hint ?? "-"}</div>
+                <div className="muted">{jobStatus.result_notes || ""}</div>
+              </div>
+            ) : (
+              <div className="muted">No evaluator job submitted yet.</div>
+            )}
+          </section>
+        </div>
+
+        <div className="center-col">
+          <section className="card">
+            <h2>What should I do next?</h2>
+            {cards.length === 0 ? <div className="muted">No immediate recommendation available.</div> : (
+              <div className="steps-stack">
+                {cards.map((step) => <NextStepCard key={step.id} step={step} onSimulate={simulateStep} />)}
+              </div>
+            )}
+          </section>
+        </div>
+
+        <div className="right-col">
+          <section className="card">
+            <h2>Progress</h2>
+            <div className="progress-wrap">
+              <div className="progress-label">Mastery progress</div>
+              <div className="progress-bar"><div className="progress-fill" style={{ width: `${progress}%` }} /></div>
+              <div className="muted">{progress}%</div>
+            </div>
+          </section>
+
+          <section className="card">
+            <h2>Evidence log</h2>
+            {learnerState.history.length === 0 ? <div className="muted">No evidence recorded yet.</div> : (
+              <ul>
+                {learnerState.history.slice().reverse().map((item, idx) => (
+                  <li key={idx}>{item.concept_id} · score {item.score.toFixed(2)} · hint {item.confidence_hint.toFixed(2)} · {item.kind}</li>
+                ))}
+              </ul>
+            )}
+          </section>
+
+          <section className="card">
+            <h2>Compliance</h2>
+            <div className="compliance-grid">
+              <div><strong>Sources</strong><br />{domain.compliance.sources}</div>
+              <div><strong>Attribution</strong><br />{domain.compliance.attributionRequired ? "required" : "not required"}</div>
+              <div><strong>Share-alike</strong><br />{domain.compliance.shareAlikeRequired ? "yes" : "no"}</div>
+              <div><strong>Noncommercial</strong><br />{domain.compliance.noncommercialOnly ? "yes" : "no"}</div>
+            </div>
+          </section>
+        </div>
       </main>
     </div>
   );

webui/src/api.js

@@ -1,24 +1,62 @@
 const API = "http://127.0.0.1:8011/api";
 
-function authHeaders(token, json=true) {
+export async function login(username, password) {
-  const h = { Authorization: `Bearer ${token}` };
+  const res = await fetch(`${API}/login`, {
-  if (json) h["Content-Type"] = "application/json";
+    method: "POST",
-  return h;
+    headers: {"Content-Type": "application/json"},
+    body: JSON.stringify({ username, password })
+  });
+  if (!res.ok) throw new Error("Login failed");
+  return await res.json();
 }
 
-export async function login(username, password) {
+function authHeaders(token) {
-  const res = await fetch(`${API}/login`, { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ username, password }) });
+  return { "Content-Type": "application/json", "Authorization": `Bearer ${token}` };
-  if (!res.ok) throw new Error("login failed");
+}
+
+export async function fetchPacks(token) {
+  const res = await fetch(`${API}/packs`, { headers: authHeaders(token) });
   return await res.json();
 }
-export async function refresh(refreshToken) {
+
-  const res = await fetch(`${API}/refresh`, { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ refresh_token: refreshToken }) });
+export async function createLearner(token, learnerId, displayName) {
-  if (!res.ok) throw new Error("refresh failed");
+  const res = await fetch(`${API}/learners`, {
+    method: "POST",
+    headers: authHeaders(token),
+    body: JSON.stringify({ learner_id: learnerId, display_name: displayName })
+  });
+  return await res.json();
+}
+
+export async function fetchLearnerState(token, learnerId) {
+  const res = await fetch(`${API}/learners/${learnerId}/state`, { headers: authHeaders(token) });
+  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)
+  });
+  return await res.json();
+}
+
+export async function fetchRecommendations(token, learnerId, packId) {
+  const res = await fetch(`${API}/learners/${learnerId}/recommendations/${packId}`, { headers: authHeaders(token) });
+  return await res.json();
+}
+
+export async function submitEvaluatorJob(token, learnerId, payload) {
+  const res = await fetch(`${API}/learners/${learnerId}/evaluator-jobs`, {
+    method: "POST",
+    headers: authHeaders(token),
+    body: JSON.stringify(payload)
+  });
+  return await res.json();
+}
+
+export async function fetchEvaluatorJob(token, jobId) {
+  const res = await fetch(`${API}/evaluator-jobs/${jobId}`, { headers: authHeaders(token) });
   return await res.json();
 }
-export async function fetchPacks(token) { const res = await fetch(`${API}/packs`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchPacks failed"); return await res.json(); }
-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(); }
-export async function putLearnerState(token, learnerId, state) { const res = await fetch(`${API}/learners/${learnerId}/state`, { method: "PUT", headers: authHeaders(token), body: JSON.stringify(state) }); if (!res.ok) throw new Error("putLearnerState failed"); return await res.json(); }
-export async function createRenderJob(token, learnerId, packId, payload) { const res = await fetch(`${API}/learners/${learnerId}/render-jobs/${packId}`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) }); if (!res.ok) throw new Error("createRenderJob failed"); return await res.json(); }
-export async function listRenderJobs(token, learnerId) { const res = await fetch(`${API}/render-jobs?learner_id=${encodeURIComponent(learnerId)}`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("listRenderJobs failed"); return await res.json(); }
-export async function listArtifacts(token, learnerId) { const res = await fetch(`${API}/artifacts?learner_id=${encodeURIComponent(learnerId)}`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("listArtifacts failed"); return await res.json(); }

webui/src/localEngine.js

@@ -22,27 +22,3 @@ export function progressPercent(state, domain) {
   const mastered = domain.concepts.filter((c) => conceptStatus(state, c) === "mastered").length;
   return Math.round((mastered / total) * 100);
 }
-
-export function milestoneMessages(state, domain) {
-  const msgs = [];
-  for (const concept of domain.concepts) {
-    if (conceptStatus(state, concept) === "mastered") msgs.push(`${concept.title} mastered`);
-  }
-  if (msgs.length === 0) msgs.push("Complete your first guided exercise to earn a visible mastery marker");
-  return msgs;
-}
-
-export function claimReadiness(state, domain, minScore = 0.75, minConfidence = 0.60) {
-  const records = domain.concepts
-    .map((c) => getRecord(state, c.id, c.masteryDimension || "mastery"))
-    .filter(Boolean);
-  const mastered = records.filter((r) => r.score >= minScore && r.confidence >= minConfidence).length;
-  const avgScore = records.length ? records.reduce((a, r) => a + r.score, 0) / records.length : 0;
-  const avgConfidence = records.length ? records.reduce((a, r) => a + r.confidence, 0) / records.length : 0;
-  return {
-    ready: mastered >= Math.max(1, domain.concepts.length - 1) && avgScore >= minScore && avgConfidence >= minConfidence,
-    mastered,
-    avgScore,
-    avgConfidence
-  };
-}

webui/src/main.jsx

@@ -2,4 +2,5 @@ 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

@@ -1,23 +1,52 @@
 :root {
-  --bg:#f6f8fb; --card:#ffffff; --text:#1f2430; --muted:#60697a; --border:#dbe1ea; --accent:#2d6cdf;
+  --bg: #f6f8fb;
+  --card: #ffffff;
+  --text: #1f2430;
+  --muted: #60697a;
+  --border: #dbe1ea;
+  --accent: #2d6cdf;
+  --soft: #eef4ff;
 }
-* { box-sizing:border-box; }
+* { box-sizing: border-box; }
-body { margin:0; font-family:Arial, Helvetica, sans-serif; background:var(--bg); color:var(--text); }
+body { margin: 0; font-family: Arial, Helvetica, sans-serif; background: var(--bg); color: var(--text); }
-.page { max-width:1500px; margin:0 auto; padding:24px; }
+.page { max-width: 1500px; margin: 0 auto; padding: 20px; }
-.narrow-page { max-width:520px; }
+.hero { background: var(--card); border: 1px solid var(--border); border-radius: 22px; padding: 24px; display: flex; justify-content: space-between; gap: 16px; }
-.hero { background:var(--card); border:1px solid var(--border); border-radius:22px; padding:24px; display:flex; justify-content:space-between; gap:16px; align-items:flex-start; }
+.hero-controls { min-width: 260px; }
-.controls { display:flex; gap:10px; align-items:flex-end; flex-wrap:wrap; }
+.hero-controls input { width: 100%; margin-top: 6px; border: 1px solid var(--border); border-radius: 10px; padding: 10px; font: inherit; }
-label { display:block; font-weight:600; }
+.domain-grid { display: grid; grid-template-columns: repeat(2, 1fr); gap: 16px; margin-top: 16px; }
-input, select { width:100%; margin-top:6px; border:1px solid var(--border); border-radius:10px; padding:10px; font:inherit; background:white; }
+.domain-card { border: 1px solid var(--border); background: var(--card); border-radius: 18px; padding: 16px; text-align: left; cursor: pointer; }
-button { border:1px solid var(--border); background:white; border-radius:12px; padding:10px 14px; cursor:pointer; }
+.domain-card.selected { border-color: var(--accent); box-shadow: 0 0 0 2px rgba(45,108,223,0.12); }
-.card { background:var(--card); border:1px solid var(--border); border-radius:18px; padding:18px; }
+.domain-title { font-size: 20px; font-weight: 700; }
-.narrow { margin-top:60px; }
+.domain-subtitle { margin-top: 6px; color: var(--muted); }
-.layout { display:grid; gap:16px; }
+.domain-meta { margin-top: 10px; display: flex; gap: 12px; color: var(--muted); font-size: 14px; }
-.twocol { grid-template-columns:1fr 1fr; }
+.layout { display: grid; grid-template-columns: 1fr 1.25fr 0.95fr; gap: 16px; margin-top: 16px; }
-.prebox { background:#f7f8fa; border:1px solid var(--border); border-radius:12px; padding:12px; overflow:auto; max-height:460px; }
+.card { background: var(--card); border: 1px solid var(--border); border-radius: 20px; padding: 18px; }
-.muted { color:var(--muted); }
+.narrow { max-width: 420px; margin: 60px auto; }
-.error { color:#b42318; margin-top:10px; }
+label { display: block; font-weight: 600; margin-bottom: 12px; }
-@media (max-width:1100px) {
+input { width: 100%; margin-top: 6px; border: 1px solid var(--border); border-radius: 10px; padding: 10px; font: inherit; }
-  .hero { flex-direction:column; }
+.muted { color: var(--muted); }
-  .twocol { grid-template-columns:1fr; }
+.error { color: #b42318; margin-top: 10px; }
+.steps-stack { display: grid; gap: 14px; }
+.step-card { border: 1px solid var(--border); border-radius: 16px; padding: 14px; background: #fcfdff; }
+.step-header { display: flex; justify-content: space-between; gap: 12px; align-items: start; }
+.reward-pill { background: var(--soft); border: 1px solid var(--border); border-radius: 999px; padding: 8px 10px; font-size: 12px; }
+button { border: 1px solid var(--border); background: white; border-radius: 12px; padding: 10px 14px; cursor: pointer; }
+.primary { background: var(--accent); color: white; border: none; }
+.button-row { display: flex; gap: 10px; }
+.map-grid { display: grid; grid-template-columns: repeat(2, 1fr); gap: 12px; }
+.map-node { border: 1px solid var(--border); border-radius: 16px; padding: 14px; }
+.map-node.mastered { background: #eef9f0; }
+.map-node.active, .map-node.available { background: #eef4ff; }
+.map-node.locked { background: #f6f7fa; }
+.node-label { font-weight: 700; }
+.node-status { margin-top: 6px; color: var(--muted); text-transform: capitalize; }
+.progress-wrap { margin-bottom: 14px; }
+.progress-bar { width: 100%; height: 12px; border-radius: 999px; background: #e9edf4; overflow: hidden; margin: 8px 0; }
+.progress-fill { height: 100%; background: var(--accent); }
+.compliance-grid { display: grid; grid-template-columns: repeat(2, 1fr); gap: 10px; }
+details summary { cursor: pointer; color: var(--accent); }
+@media (max-width: 1100px) {
+  .layout { grid-template-columns: 1fr; }
+  .domain-grid { grid-template-columns: 1fr; }
+  .hero { flex-direction: column; }
 }