Apply ZIP update: 235-didactopus-productionization-scaffold.zip [2026-03-14T13:20:53]

pyproject.toml

@@ -6,10 +6,20 @@ 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",
+  "psycopg[binary]>=3.1",
+  "passlib[bcrypt]>=1.7",
+  "python-jose[cryptography]>=3.3"
+]
 
 [project.scripts]
-didactopus-pack-to-frontend = "didactopus.pack_to_frontend:main"
+didactopus-api = "didactopus.api:main"
+didactopus-worker = "didactopus.worker:main"
 
 [tool.setuptools.packages.find]
 where = ["src"]

src/didactopus/api.py

@@ -1,19 +1,30 @@
 from __future__ import annotations
-from fastapi import FastAPI, HTTPException, Header, Depends
+from fastapi import FastAPI, HTTPException, Header, Depends, BackgroundTasks
 from fastapi.middleware.cors import CORSMiddleware
-import uvicorn, json, tempfile
+import uvicorn
-from pathlib import Path
+from .config import load_settings
 from .db import Base, engine
-from .models import LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState, MediaRenderRequest
+from .models import LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState, EvidenceEvent, EvaluatorSubmission, EvaluatorJobStatus, CreatePackRequest
-from .repository import authenticate_user, get_user_by_id, store_refresh_token, refresh_token_active, revoke_refresh_token, list_packs_for_user, get_pack, get_pack_row, create_learner, learner_owned_by_user, load_learner_state, save_learner_state
+from .repository import (
+    authenticate_user, get_user_by_id, store_refresh_token, refresh_token_active, revoke_refresh_token,
+    list_packs, get_pack, upsert_pack, create_learner, learner_owned_by_user, load_learner_state,
+    save_learner_state, create_evaluator_job, get_evaluator_job, list_evaluator_jobs_for_learner
+)
+from .engine import apply_evidence, recommend_next
 from .auth import issue_access_token, issue_refresh_token, decode_token, new_token_id
-from .engine import build_graph_frames, stable_layout
+from .worker import process_job
-from .render_bundle import make_render_bundle
 
+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()
@@ -25,24 +36,17 @@ def current_user(authorization: str = Header(default="")):
         raise HTTPException(status_code=401, detail="Unauthorized")
     return user
 
+def require_admin(user = Depends(current_user)):
+    if user.role != "admin":
+        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")
 
-def ensure_pack_access(user, pack_id: str):
-    row = get_pack_row(pack_id)
-    if row is None:
-        raise HTTPException(status_code=404, detail="Pack not found")
-    if user.role == "admin":
-        return row
-    if row.policy_lane == "community":
-        return row
-    if row.owner_user_id == user.id:
-        return row
-    raise HTTPException(status_code=403, detail="Pack not accessible by this user")
-
 @app.post("/api/login", response_model=TokenPair)
 def login(payload: LoginRequest):
     user = authenticate_user(payload.username, payload.password)
@@ -50,7 +54,12 @@ def login(payload: LoginRequest):
         raise HTTPException(status_code=401, detail="Invalid credentials")
     token_id = new_token_id()
     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)
+    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):
@@ -66,11 +75,29 @@ def refresh(payload: RefreshRequest):
     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)
+    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"))]
+    include_unpublished = user.role == "admin"
+    return [p.model_dump() for p in list_packs(include_unpublished=include_unpublished)]
+
+@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/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/learners")
 def api_create_learner(payload: CreateLearnerRequest, user = Depends(current_user)):
@@ -89,52 +116,45 @@ 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-bundle/{pack_id}")
+@app.get("/api/learners/{learner_id}/recommendations/{pack_id}")
-def api_render_bundle(learner_id: str, pack_id: str, payload: MediaRenderRequest, 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),
+
-    }
+@app.post("/api/learners/{learner_id}/evaluator-jobs", response_model=EvaluatorJobStatus)
-    base = Path(tempfile.mkdtemp(prefix="didactopus_render_"))
+def api_submit_evaluator_job(learner_id: str, payload: EvaluatorSubmission, background_tasks: BackgroundTasks, user = Depends(current_user)):
-    payload_json = base / "animation_payload.json"
+    ensure_learner_access(user, learner_id)
-    payload_json.write_text(json.dumps(animation, indent=2), encoding="utf-8")
+    job_id = create_evaluator_job(learner_id, payload.pack_id, payload.concept_id, payload.submitted_text)
-    out_dir = base / "bundle"
+    background_tasks.add_task(process_job, job_id)
-    make_render_bundle(str(payload_json), str(out_dir), fps=payload.fps, fmt=payload.format)
+    return EvaluatorJobStatus(job_id=job_id, status="queued")
-    return {
+
-        "bundle_dir": str(out_dir),
+@app.get("/api/evaluator-jobs/{job_id}", response_model=EvaluatorJobStatus)
-        "payload_json": str(payload_json),
+def api_get_evaluator_job(job_id: int, user = Depends(current_user)):
-        "manifest": str(out_dir / "render_manifest.json"),
+    job = get_evaluator_job(job_id)
-        "script": str(out_dir / "render.sh"),
+    if job is None:
-        "format": payload.format,
+        raise HTTPException(status_code=404, detail="Job not found")
-        "fps": payload.fps,
+    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/learners/{learner_id}/evaluator-history")
+def api_get_evaluator_history(learner_id: str, user = Depends(current_user)):
+    ensure_learner_access(user, learner_id)
+    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]
 
 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

@@ -20,10 +20,10 @@ def _encode_token(payload: dict, expires_delta: timedelta) -> str:
     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))
+    return _encode_token({"sub": str(user_id), "username": username, "role": role, "kind": "access"}, timedelta(minutes=settings.access_token_minutes))
 
 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))
+    return _encode_token({"sub": str(user_id), "username": username, "role": role, "kind": "refresh", "jti": token_id}, timedelta(days=settings.refresh_token_days))
 
 def decode_token(token: str) -> dict | None:
     try:

src/didactopus/config.py

@@ -3,11 +3,13 @@ import os
 from pydantic import BaseModel
 
 class Settings(BaseModel):
-    database_url: str = os.getenv("DIDACTOPUS_DATABASE_URL", "sqlite+pysqlite:///:memory:")
+    database_url: str = os.getenv("DIDACTOPUS_DATABASE_URL", "postgresql+psycopg://didactopus:didactopus-dev-password@localhost:5432/didactopus")
     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"
+    access_token_minutes: int = 30
+    refresh_token_days: int = 14
 
 def load_settings() -> Settings:
     return Settings()

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

@@ -1,5 +1,8 @@
 from __future__ import annotations
 from pydantic import BaseModel, Field
+from typing import Literal
+
+EvidenceKind = Literal["checkpoint", "project", "exercise", "review"]
 
 class TokenPair(BaseModel):
     access_token: str
@@ -15,24 +18,19 @@ class LoginRequest(BaseModel):
 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
     title: str
     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 +39,7 @@ 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 +55,7 @@ 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 +63,23 @@ class LearnerState(BaseModel):
     records: list[MasteryRecord] = Field(default_factory=list)
     history: list[EvidenceEvent] = Field(default_factory=list)
 
-class MediaRenderRequest(BaseModel):
+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 = ""
+
+class CreatePackRequest(BaseModel):
+    pack: PackData
+    is_published: bool = True

src/didactopus/orm.py

@@ -1,5 +1,5 @@
 from sqlalchemy import String, Integer, Float, ForeignKey, Text, Boolean
-from sqlalchemy.orm import Mapped, mapped_column
+from sqlalchemy.orm import Mapped, mapped_column, relationship
 from .db import Base
 
 class UserORM(Base):
@@ -20,13 +20,11 @@ class RefreshTokenORM(Base):
 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)
+    is_published: Mapped[bool] = mapped_column(Boolean, default=True)
 
 class LearnerORM(Base):
     __tablename__ = "learners"
@@ -56,3 +54,15 @@ 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="")
+
+class EvaluatorJobORM(Base):
+    __tablename__ = "evaluator_jobs"
+    id: Mapped[int] = mapped_column(Integer, primary_key=True)
+    learner_id: Mapped[str] = mapped_column(ForeignKey("learners.id"), index=True)
+    pack_id: Mapped[str] = mapped_column(ForeignKey("packs.id"), index=True)
+    concept_id: Mapped[str] = mapped_column(String(100), index=True)
+    submitted_text: Mapped[str] = mapped_column(Text, default="")
+    status: Mapped[str] = mapped_column(String(50), default="queued")
+    result_score: Mapped[float | None] = mapped_column(Float, nullable=True)
+    result_confidence_hint: Mapped[float | None] = mapped_column(Float, nullable=True)
+    result_notes: Mapped[str] = mapped_column(Text, default="")

src/didactopus/repository.py

@@ -2,7 +2,7 @@ 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, RefreshTokenORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM, EvaluatorJobORM
 from .models import PackData, LearnerState, MasteryRecord, EvidenceEvent
 from .auth import verify_password
 
@@ -37,54 +37,31 @@ def revoke_refresh_token(token_id: str):
             row.is_revoked = True
             db.commit()
 
-def list_packs_for_user(user_id: int | None = None, include_unpublished: bool = False):
+def list_packs(include_unpublished: bool = False) -> list[PackData]:
     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 = []
+        return [PackData.model_validate(json.loads(r.data_json)) for r in rows]
-        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):
+def upsert_pack(pack: PackData, is_published: bool = True):
-    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(
+            db.add(PackORM(id=pack.id, title=pack.title, subtitle=pack.subtitle, level=pack.level, data_json=payload, is_published=is_published))
-                id=pack.id,
-                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
-                row.is_published = is_published
         db.commit()
 
 def create_learner(owner_user_id: int, learner_id: str, display_name: str = ""):
@@ -98,7 +75,7 @@ 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()
@@ -118,3 +95,30 @@ def save_learner_state(state: LearnerState):
             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 list_evaluator_jobs_for_learner(learner_id: str) -> list[EvaluatorJobORM]:
+    with SessionLocal() as db:
+        return db.execute(select(EvaluatorJobORM).where(EvaluatorJobORM.learner_id == learner_id).order_by(EvaluatorJobORM.id.desc())).scalars().all()
+
+def get_evaluator_job(job_id: int):
+    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 = ""):
+    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 +1,36 @@
 from __future__ import annotations
+import json
 from sqlalchemy import select
 from .db import Base, engine, SessionLocal
-from .orm import UserORM
+from .orm import UserORM, PackORM
 from .auth import hash_password
-from .repository import upsert_pack, create_learner
+
-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"]}
+    }
+]
 
 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))
+        for pack in PACKS:
+            if db.get(PackORM, pack["id"]) is None:
+                db.add(PackORM(id=pack["id"], title=pack["title"], subtitle=pack["subtitle"], level=pack["level"], data_json=json.dumps(pack), is_published=True))
         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,
-    )

src/didactopus/worker.py

@@ -8,14 +8,27 @@ def process_job(job_id: int):
     job = get_evaluator_job(job_id)
     if job is None:
         return
+    update_evaluator_job(job_id, "running")
     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."
-    update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes, trace={"notes": ["completed"]})
+    update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes)
     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}"))
+    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 main():
+    print("Didactopus worker scaffold running. In a real deployment this would poll a queue.")
     while True:
         time.sleep(60)
+
+if __name__ == "__main__":
+    main()

webui/index.html

@@ -3,7 +3,7 @@
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Didactopus Pack UI</title>
+    <title>Didactopus Production UI Scaffold</title>
     <script type="module" src="/src/main.jsx"></script>
   </head>
   <body>

webui/package.json

@@ -1,5 +1,5 @@
 {
-  "name": "didactopus-live-pack-ui",
+  "name": "didactopus-production-ui",
   "private": true,
   "version": "0.1.0",
   "type": "module",

webui/src/App.jsx

@@ -1,207 +1,11 @@
-import React, { useEffect, useMemo, useState } from "react";
+import React from "react";
-import { applyEvidence, buildMasteryMap, claimReadiness, milestoneMessages, progressPercent, recommendNext } from "./engine";
-import { loadLearnerState, saveLearnerState, resetLearnerState } from "./storage";
-
-const PACKS = ["/packs/bayes-pack.json", "/packs/stats-pack.json"];
-
-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>
-      <div className="domain-meta">
-        <span>{domain.level}</span>
-        <span>{domain.concepts.length} concepts</span>
-      </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>
-      <button className="primary" onClick={() => onSimulate(step)}>Simulate completing this step</button>
-    </div>
-  );
-}
-
 export default function App() {
-  const [packs, setPacks] = useState([]);
-  const [selectedDomainId, setSelectedDomainId] = useState("");
-  const [learnerName, setLearnerName] = useState("Wesley");
-  const [domainStates, setDomainStates] = useState({});
-  const [lastReward, setLastReward] = useState("");
-
-  useEffect(() => {
-    Promise.all(PACKS.map((u) => fetch(u).then((r) => r.json()))).then((loaded) => {
-      setPacks(loaded);
-      setSelectedDomainId(loaded[0]?.id || "");
-      const states = {};
-      for (const pack of loaded) {
-        states[pack.id] = loadLearnerState(pack.id);
-      }
-      setDomainStates(states);
-    });
-  }, []);
-
-  const domain = useMemo(() => packs.find((d) => d.id === selectedDomainId) || null, [packs, selectedDomainId]);
-  const learnerState = domain ? (domainStates[domain.id] || loadLearnerState(domain.id)) : null;
-
-  const masteryMap = useMemo(() => domain && learnerState ? buildMasteryMap(learnerState, domain) : [], [learnerState, domain]);
-  const progress = useMemo(() => domain && learnerState ? progressPercent(learnerState, domain) : 0, [learnerState, domain]);
-  const recs = useMemo(() => domain && learnerState ? recommendNext(learnerState, domain) : [], [learnerState, domain]);
-  const milestones = useMemo(() => domain && learnerState ? milestoneMessages(learnerState, domain) : [], [learnerState, domain]);
-  const readiness = useMemo(() => domain && learnerState ? claimReadiness(learnerState, domain) : {ready:false, mastered:0, avgScore:0, avgConfidence:0}, [learnerState, domain]);
-
-  function updateState(domainId, nextState) {
-    saveLearnerState(domainId, nextState);
-    setDomainStates((prev) => ({ ...prev, [domainId]: nextState }));
-  }
-
-  function simulateStep(step) {
-    if (!domain || !learnerState) return;
-    const timestamp = new Date().toISOString();
-    const updated = applyEvidence(learnerState, {
-      concept_id: step.conceptId,
-      dimension: "mastery",
-      score: step.scoreHint,
-      confidence_hint: step.confidenceHint,
-      timestamp,
-      kind: "checkpoint",
-      source_id: `ui-${step.id}`
-    });
-    updateState(domain.id, updated);
-    setLastReward(step.reward);
-  }
-
-  function resetSelectedDomain() {
-    if (!domain) return;
-    resetLearnerState(domain.id);
-    updateState(domain.id, loadLearnerState(domain.id));
-    setLastReward("");
-  }
-
-  if (!domain || !learnerState) {
-    return <div className="page"><div className="card">Loading packs...</div></div>;
-  }
-
   return (
     <div className="page">
-      <header className="hero">
+      <div className="card">
-        <div>
+        <h1>Didactopus productionization scaffold</h1>
-          <h1>Didactopus learner prototype</h1>
+        <p>This UI scaffold is intended for later connection to evaluator history, learner management, and admin pack management endpoints.</p>
-          <p>Real pack files, persistent learner state, and live recommendation updates.</p>
+      </div>
-        </div>
-        <div className="hero-controls">
-          <label>
-            Learner name
-            <input value={learnerName} onChange={(e) => setLearnerName(e.target.value)} />
-          </label>
-          <button onClick={resetSelectedDomain}>Reset selected domain</button>
-        </div>
-      </header>
-
-      <section className="domain-grid">
-        {packs.map((d) => <DomainCard key={d.id} domain={d} selected={d.id === domain.id} onSelect={setSelectedDomainId} />)}
-      </section>
-
-      <main className="layout">
-        <div className="left-col">
-          <section className="card">
-            <h2>First-session onboarding</h2>
-            <h3>{domain.onboarding.headline}</h3>
-            <p>{domain.onboarding.body}</p>
-            <p className="muted">Learner: {learnerName || "Unnamed learner"}</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 ${node.status}`}>
-                  <div className="node-label">{node.label}</div>
-                  <div className="node-status">{node.status}</div>
-                </div>
-              ))}
-            </div>
-          </section>
-
-          <section className="card">
-            <h2>Evidence log</h2>
-            {learnerState.history.length === 0 ? <div className="muted">No evidence recorded yet.</div> : (
-              <ul>
-                {learnerState.history.slice().reverse().map((item, idx) => (
-                  <li key={idx}>{item.concept_id} · score {item.score.toFixed(2)} · confidence hint {item.confidence_hint.toFixed(2)}</li>
-                ))}
-              </ul>
-            )}
-          </section>
-        </div>
-
-        <div className="center-col">
-          <section className="card">
-            <h2>What should I do next?</h2>
-            {recs.length === 0 ? (
-              <div className="muted">No immediate recommendation available.</div>
-            ) : (
-              <div className="steps-stack">
-                {recs.map((step) => <NextStepCard key={step.id} step={step} onSimulate={simulateStep} />)}
-              </div>
-            )}
-          </section>
-        </div>
-
-        <div className="right-col">
-          <section className="card">
-            <h2>Progress</h2>
-            <div className="progress-wrap">
-              <div className="progress-label">Mastery progress</div>
-              <div className="progress-bar"><div className="progress-fill" style={{ width: `${progress}%` }} /></div>
-              <div className="muted">{progress}%</div>
-            </div>
-            <div className={`readiness-box ${readiness.ready ? "ready" : ""}`}>
-              <strong>{readiness.ready ? "Usable expertise threshold met" : "Still building toward usable expertise"}</strong>
-              <div className="muted">Mastered concepts: {readiness.mastered}</div>
-              <div className="muted">Average score: {readiness.avgScore.toFixed(2)}</div>
-              <div className="muted">Average confidence: {readiness.avgConfidence.toFixed(2)}</div>
-            </div>
-          </section>
-
-          <section className="card">
-            <h2>Milestones and rewards</h2>
-            {lastReward ? <div className="reward-banner">{lastReward}</div> : null}
-            <ul>{milestones.map((m, idx) => <li key={idx}>{m}</li>)}</ul>
-          </section>
-
-          <section className="card">
-            <h2>Source attribution and 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>
-            <div className="flag-row">
-              {domain.compliance.flags.length ? domain.compliance.flags.map((f) => <span className="flag" key={f}>{f}</span>) : <span className="muted">No extra flags</span>}
-            </div>
-          </section>
-        </div>
-      </main>
     </div>
   );
 }

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

@@ -1,53 +1,3 @@
-:root {
+body { margin:0; font-family:Arial, Helvetica, sans-serif; background:#f6f8fb; color:#1f2430; }
-  --bg: #f6f8fb;
+.page { max-width: 1100px; margin: 0 auto; padding: 24px; }
-  --card: #ffffff;
+.card { background:white; border:1px solid #dbe1ea; border-radius:18px; padding:20px; }
-  --text: #1f2430;
-  --muted: #60697a;
-  --border: #dbe1ea;
-  --accent: #2d6cdf;
-  --soft: #eef4ff;
-}
-* { 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; }
-.hero { background: var(--card); border: 1px solid var(--border); border-radius: 22px; padding: 24px; display: flex; justify-content: space-between; gap: 16px; }
-.hero-controls { min-width: 260px; }
-.hero-controls input { width: 100%; margin-top: 6px; border: 1px solid var(--border); border-radius: 10px; padding: 10px; font: inherit; }
-.hero-controls button { margin-top: 12px; }
-.domain-grid { display: grid; grid-template-columns: repeat(2, 1fr); gap: 16px; margin-top: 16px; }
-.domain-card { border: 1px solid var(--border); background: var(--card); border-radius: 18px; padding: 16px; text-align: left; cursor: pointer; }
-.domain-card.selected { border-color: var(--accent); box-shadow: 0 0 0 2px rgba(45,108,223,0.12); }
-.domain-title { font-size: 20px; font-weight: 700; }
-.domain-subtitle { margin-top: 6px; color: var(--muted); }
-.domain-meta { margin-top: 10px; display: flex; gap: 12px; color: var(--muted); font-size: 14px; }
-.layout { display: grid; grid-template-columns: 1fr 1.25fr 0.95fr; gap: 16px; margin-top: 16px; }
-.card { background: var(--card); border: 1px solid var(--border); border-radius: 20px; padding: 18px; }
-.muted { color: var(--muted); }
-.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 { margin-top: 10px; background: var(--accent); color: white; border: none; }
-.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); }
-.reward-banner { background: #fff7dd; border: 1px solid #ecdca2; border-radius: 14px; padding: 12px; margin-bottom: 12px; font-weight: 700; }
-.readiness-box { border: 1px solid var(--border); background: #fbfcfe; border-radius: 14px; padding: 12px; }
-.readiness-box.ready { background: #eef9f0; }
-.compliance-grid { display: grid; grid-template-columns: repeat(2, 1fr); gap: 10px; }
-.flag-row { margin-top: 12px; display: flex; flex-wrap: wrap; gap: 8px; }
-.flag { border: 1px solid var(--border); background: #f4f7fc; border-radius: 999px; padding: 6px 10px; font-size: 12px; }
-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; }
-}