Apply ZIP update: 235-didactopus-productionization-scaffold.zip [2026-03-14T13:20:53]
This commit is contained in:
parent
b722c379dd
commit
664f959f34
|
|
@ -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"]
|
||||
|
|
|
|||
|
|
@ -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()
|
||||
|
|
|
|||
|
|
@ -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:
|
||||
|
|
|
|||
|
|
@ -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()
|
||||
|
|
|
|||
|
|
@ -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]
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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="")
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
||||
|
|
@ -37,53 +37,30 @@ 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
|
||||
db.commit()
|
||||
|
||||
|
|
@ -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()
|
||||
|
|
|
|||
|
|
@ -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()
|
||||
|
|
|
|||
|
|
@ -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()
|
||||
|
|
|
|||
|
|
@ -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>
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"name": "didactopus-live-pack-ui",
|
||||
"name": "didactopus-production-ui",
|
||||
"private": true,
|
||||
"version": "0.1.0",
|
||||
"type": "module",
|
||||
|
|
|
|||
|
|
@ -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 (
|
||||
<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>
|
||||
);
|
||||
}
|
||||
|
||||
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 <div className="page"><div className="card">Loading packs...</div></div>;
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="page">
|
||||
<header className="hero">
|
||||
<div>
|
||||
<h1>Didactopus learner prototype</h1>
|
||||
<p>Real pack files, persistent learner state, and live recommendation updates.</p>
|
||||
<div className="card">
|
||||
<h1>Didactopus productionization scaffold</h1>
|
||||
<p>This UI scaffold is intended for later connection to evaluator history, learner management, and admin pack management endpoints.</p>
|
||||
</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>
|
||||
);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -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 />);
|
||||
|
|
|
|||
|
|
@ -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; }
|
||||
|
|
|
|||
Loading…
Reference in New Issue