diff --git a/pyproject.toml b/pyproject.toml index b6064b1..35368af 100644 --- a/pyproject.toml +++ b/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"] diff --git a/src/didactopus/api.py b/src/didactopus/api.py index 8f42cf9..e494573 100644 --- a/src/didactopus/api.py +++ b/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 -from pathlib import Path +import uvicorn +from .config import load_settings from .db import Base, engine -from .models import LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState, MediaRenderRequest -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 .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, 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 .render_bundle import make_render_bundle +from .worker import process_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() @@ -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") -def api_pack_layout(pack_id: str, 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)): +@app.post("/api/learners/{learner_id}/evidence") +def api_post_evidence(learner_id: str, event: EvidenceEvent, 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) - return { - "learner_id": learner_id, - "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 [], - } + state = apply_evidence(state, event) + save_learner_state(state) + return state.model_dump() -@app.post("/api/learners/{learner_id}/render-bundle/{pack_id}") -def api_render_bundle(learner_id: str, pack_id: str, payload: MediaRenderRequest, user = Depends(current_user)): +@app.get("/api/learners/{learner_id}/recommendations/{pack_id}") +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 = { - "learner_id": learner_id, - "pack_id": pack_id, - "pack_title": pack.title if pack else "", - "frames": build_graph_frames(state, pack), - } - base = Path(tempfile.mkdtemp(prefix="didactopus_render_")) - payload_json = base / "animation_payload.json" - payload_json.write_text(json.dumps(animation, indent=2), encoding="utf-8") - out_dir = base / "bundle" - make_render_bundle(str(payload_json), str(out_dir), fps=payload.fps, fmt=payload.format) - return { - "bundle_dir": str(out_dir), - "payload_json": str(payload_json), - "manifest": str(out_dir / "render_manifest.json"), - "script": str(out_dir / "render.sh"), - "format": payload.format, - "fps": payload.fps, - } + pack = get_pack(pack_id) + if pack is None: + raise HTTPException(status_code=404, detail="Pack not found") + return {"cards": recommend_next(state, pack)} + +@app.post("/api/learners/{learner_id}/evaluator-jobs", response_model=EvaluatorJobStatus) +def api_submit_evaluator_job(learner_id: str, payload: EvaluatorSubmission, background_tasks: BackgroundTasks, user = Depends(current_user)): + ensure_learner_access(user, learner_id) + job_id = create_evaluator_job(learner_id, payload.pack_id, payload.concept_id, payload.submitted_text) + background_tasks.add_task(process_job, job_id) + return EvaluatorJobStatus(job_id=job_id, status="queued") + +@app.get("/api/evaluator-jobs/{job_id}", response_model=EvaluatorJobStatus) +def api_get_evaluator_job(job_id: int, user = Depends(current_user)): + job = get_evaluator_job(job_id) + if job is None: + 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) + +@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() diff --git a/src/didactopus/auth.py b/src/didactopus/auth.py index 54745ac..a2d088d 100644 --- a/src/didactopus/auth.py +++ b/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: diff --git a/src/didactopus/config.py b/src/didactopus/config.py index 1f71733..9890f28 100644 --- a/src/didactopus/config.py +++ b/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() diff --git a/src/didactopus/engine.py b/src/didactopus/engine.py index 6b7c236..c1e52bf 100644 --- a/src/didactopus/engine.py +++ b/src/didactopus/engine.py @@ -1,110 +1,59 @@ from __future__ import annotations -from collections import defaultdict -from .models import LearnerState, PackData +from .models import LearnerState, EvidenceEvent, MasteryRecord, PackData -def concept_depths(pack: PackData) -> dict[str, int]: - concept_map = {c.id: c for c in pack.concepts} - memo = {} - def depth(cid: str) -> int: - if cid in memo: - 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 get_record(state: LearnerState, concept_id: str, dimension: str = "mastery") -> MasteryRecord | None: + for rec in state.records: + if rec.concept_id == concept_id and rec.dimension == dimension: + return rec + return None -def stable_layout(pack: PackData, width: int = 900, height: int = 520): - depths = concept_depths(pack) - layers = defaultdict(list) - for c in pack.concepts: - layers[depths.get(c.id, 0)].append(c) - positions = {} - max_depth = max(layers.keys()) if layers else 0 - for d in sorted(layers): - nodes = sorted(layers[d], key=lambda c: c.id) - y = 90 + d * ((height - 160) / max(1, max_depth)) - for idx, node in enumerate(nodes): - if node.position is not None: - 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 apply_evidence(state: LearnerState, event: EvidenceEvent, decay: float = 0.05, reinforcement: float = 0.25) -> LearnerState: + rec = get_record(state, event.concept_id, event.dimension) + if rec is None: + rec = MasteryRecord(concept_id=event.concept_id, dimension=event.dimension, score=0.0, confidence=0.0, evidence_count=0, last_updated=event.timestamp) + state.records.append(rec) + 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(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: - score = scores.get(concept.id, 0.0) - if score >= min_score: +def concept_status(state: LearnerState, concept, min_score: float = 0.65, min_confidence: float = 0.45) -> str: + rec = get_record(state, concept.id, concept.masteryDimension) + if rec and rec.score >= min_score and rec.confidence >= min_confidence: return "mastered" - if prereqs_satisfied(scores, concept, min_score): - return "active" if score > 0 else "available" + if prereqs_satisfied(state, concept, min_score, min_confidence): + return "active" if rec else "available" return "locked" -def build_graph_frames(state: LearnerState, pack: PackData): - concepts = {c.id: c for c in pack.concepts} - layout = stable_layout(pack) - scores = {c.id: 0.0 for c in pack.concepts} - frames = [] - history = sorted(state.history, key=lambda x: x.timestamp) - static_edges = [{"source": pre, "target": c.id, "kind": "prerequisite"} for c in pack.concepts for pre in c.prerequisites] - static_cross = [{ - "source": c.id, - "target_pack_id": link.target_pack_id, - "target_concept_id": link.target_concept_id, - "relationship": link.relationship, - "kind": "cross_pack" - } for c in pack.concepts for link in c.cross_pack_links] - for idx, ev in enumerate(history): - if ev.concept_id in scores: - scores[ev.concept_id] = ev.score - nodes = [] - for cid, concept in concepts.items(): - score = scores.get(cid, 0.0) - 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"], +def recommend_next(state: LearnerState, pack: PackData) -> list[dict]: + cards = [] + for concept in pack.concepts: + status = concept_status(state, concept) + rec = get_record(state, concept.id, concept.masteryDimension) + if status in {"available", "active"}: + cards.append({ + "id": concept.id, + "title": f"Work on {concept.title}", + "minutes": 15 if status == "available" else 10, + "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.", + "why": [ + "Prerequisite check passed", + f"Current score: {rec.score:.2f}" if rec else "No evidence recorded yet", + f"Current confidence: {rec.confidence:.2f}" if rec else "Confidence starts after your first exercise", + ], + "reward": concept.exerciseReward or f"{concept.title} progress recorded", + "conceptId": concept.id, + "scoreHint": 0.82 if status == "available" else 0.76, + "confidenceHint": 0.72 if status == "available" else 0.55, }) - frames.append({ - "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 + return cards[:4] diff --git a/src/didactopus/models.py b/src/didactopus/models.py index fb9adf3..e2a0b8b 100644 --- a/src/didactopus/models.py +++ b/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) - -class CreateLearnerRequest(BaseModel): - learner_id: str - display_name: str = "" + compliance: PackCompliance = Field(default_factory=PackCompliance) 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" - fps: int = 2 - theme: str = "default" + concept_id: str + submitted_text: str + kind: str = "checkpoint" + +class EvaluatorJobStatus(BaseModel): + job_id: int + status: str + result_score: float | None = None + result_confidence_hint: float | None = None + result_notes: str = "" + +class CreatePackRequest(BaseModel): + pack: PackData + is_published: bool = True diff --git a/src/didactopus/orm.py b/src/didactopus/orm.py index 49c1d57..fb79b36 100644 --- a/src/didactopus/orm.py +++ b/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="") diff --git a/src/didactopus/repository.py b/src/didactopus/repository.py index bc8e397..90ad6a9 100644 --- a/src/didactopus/repository.py +++ b/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 = [] - 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 + return [PackData.model_validate(json.loads(r.data_json)) for r in rows] 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): +def upsert_pack(pack: PackData, is_published: bool = True): with SessionLocal() as db: row = db.get(PackORM, pack.id) payload = json.dumps(pack.model_dump()) if row is None: - row = PackORM( - 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) + db.add(PackORM(id=pack.id, title=pack.title, subtitle=pack.subtitle, level=pack.level, data_json=payload, is_published=is_published)) 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() diff --git a/src/didactopus/seed.py b/src/didactopus/seed.py index bdc7b86..f77244d 100644 --- a/src/didactopus/seed.py +++ b/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") - upsert_pack( - PackData( - id="wesley-private-pack", - 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, - ) + print("Seeded database. Demo user: wesley / demo-pass") + +if __name__ == "__main__": + main() diff --git a/src/didactopus/worker.py b/src/didactopus/worker.py index ad99705..aa3f154 100644 --- a/src/didactopus/worker.py +++ b/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() diff --git a/webui/index.html b/webui/index.html index 45716ea..be6856a 100644 --- a/webui/index.html +++ b/webui/index.html @@ -3,7 +3,7 @@ - Didactopus Pack UI + Didactopus Production UI Scaffold diff --git a/webui/package.json b/webui/package.json index 5d364c7..369022a 100644 --- a/webui/package.json +++ b/webui/package.json @@ -1,5 +1,5 @@ { - "name": "didactopus-live-pack-ui", + "name": "didactopus-production-ui", "private": true, "version": "0.1.0", "type": "module", diff --git a/webui/src/App.jsx b/webui/src/App.jsx index 6c3533b..5256ec2 100644 --- a/webui/src/App.jsx +++ b/webui/src/App.jsx @@ -1,207 +1,11 @@ -import React, { useEffect, useMemo, useState } 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 ( - - ); -} - -function NextStepCard({ step, onSimulate }) { - return ( -
-
-
-

{step.title}

-
{step.minutes} minutes
-
-
{step.reward}
-
-

{step.reason}

-
- Why this is recommended - -
- -
- ); -} - +import React from "react"; 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
Loading packs...
; - } - return (
-
-
-

Didactopus learner prototype

-

Real pack files, persistent learner state, and live recommendation updates.

-
-
- - -
-
- -
- {packs.map((d) => )} -
- -
-
-
-

First-session onboarding

-

{domain.onboarding.headline}

-

{domain.onboarding.body}

-

Learner: {learnerName || "Unnamed learner"}

-
    {domain.onboarding.checklist.map((item, idx) =>
  • {item}
  • )}
-
- -
-

Visible mastery map

-
- {masteryMap.map((node) => ( -
-
{node.label}
-
{node.status}
-
- ))} -
-
- -
-

Evidence log

- {learnerState.history.length === 0 ?
No evidence recorded yet.
: ( -
    - {learnerState.history.slice().reverse().map((item, idx) => ( -
  • {item.concept_id} · score {item.score.toFixed(2)} · confidence hint {item.confidence_hint.toFixed(2)}
  • - ))} -
- )} -
-
- -
-
-

What should I do next?

- {recs.length === 0 ? ( -
No immediate recommendation available.
- ) : ( -
- {recs.map((step) => )} -
- )} -
-
- -
-
-

Progress

-
-
Mastery progress
-
-
{progress}%
-
-
- {readiness.ready ? "Usable expertise threshold met" : "Still building toward usable expertise"} -
Mastered concepts: {readiness.mastered}
-
Average score: {readiness.avgScore.toFixed(2)}
-
Average confidence: {readiness.avgConfidence.toFixed(2)}
-
-
- -
-

Milestones and rewards

- {lastReward ?
{lastReward}
: null} -
    {milestones.map((m, idx) =>
  • {m}
  • )}
-
- -
-

Source attribution and compliance

-
-
Sources
{domain.compliance.sources}
-
Attribution
{domain.compliance.attributionRequired ? "required" : "not required"}
-
Share-alike
{domain.compliance.shareAlikeRequired ? "yes" : "no"}
-
Noncommercial
{domain.compliance.noncommercialOnly ? "yes" : "no"}
-
-
- {domain.compliance.flags.length ? domain.compliance.flags.map((f) => {f}) : No extra flags} -
-
-
-
+
+

Didactopus productionization scaffold

+

This UI scaffold is intended for later connection to evaluator history, learner management, and admin pack management endpoints.

+
); } diff --git a/webui/src/main.jsx b/webui/src/main.jsx index 8ad26cf..7352818 100644 --- a/webui/src/main.jsx +++ b/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(); diff --git a/webui/src/styles.css b/webui/src/styles.css index 0de0492..3c9f1b9 100644 --- a/webui/src/styles.css +++ b/webui/src/styles.css @@ -1,53 +1,3 @@ -:root { - --bg: #f6f8fb; - --card: #ffffff; - --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; } -} +body { margin:0; font-family:Arial, Helvetica, sans-serif; background:#f6f8fb; color:#1f2430; } +.page { max-width: 1100px; margin: 0 auto; padding: 24px; } +.card { background:white; border:1px solid #dbe1ea; border-radius:18px; padding:20px; }