Apply ZIP update: 210-didactopus-learning-animation-layer.zip [2026-03-14T13:20:36]
This commit is contained in:
parent
ed60c1d8f2
commit
82f827b8bd
|
|
@ -6,7 +6,17 @@ 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",
|
||||
"fastapi>=0.115",
|
||||
"uvicorn>=0.30",
|
||||
"sqlalchemy>=2.0",
|
||||
"passlib[bcrypt]>=1.7",
|
||||
"python-jose[cryptography]>=3.3"
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
didactopus-api = "didactopus.api:main"
|
||||
|
||||
[tool.setuptools.packages.find]
|
||||
where = ["src"]
|
||||
|
|
|
|||
|
|
@ -1,45 +1,103 @@
|
|||
from __future__ import annotations
|
||||
from fastapi import FastAPI, HTTPException, Header, Depends
|
||||
import json
|
||||
from fastapi import FastAPI, HTTPException, Header, Depends, BackgroundTasks
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
import uvicorn
|
||||
from .config import load_settings
|
||||
from .db import Base, engine
|
||||
from .models import LoginRequest, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState
|
||||
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 .auth import issue_access_token, issue_refresh_token, decode_token, new_token_id
|
||||
from .engine import build_graph_frames, stable_layout
|
||||
from .models import (
|
||||
LoginRequest, ServiceAccountLoginRequest, ServiceAccountCreateRequest, ServiceAccountRotateRequest,
|
||||
ServiceAccountStateRequest, ServiceToken, RefreshRequest, TokenPair, CreateLearnerRequest, LearnerState,
|
||||
EvidenceEvent, EvaluatorSubmission, EvaluatorJobStatus, CreatePackRequest, AgentCapabilityManifest,
|
||||
AgentLearnerPlanRequest, AgentLearnerPlanResponse, LearnerRunCreateRequest, WorkflowEventCreateRequest
|
||||
)
|
||||
from .repository import (
|
||||
authenticate_user, get_user_by_id, create_service_account, list_service_accounts, authenticate_service_account,
|
||||
rotate_service_account_secret, set_service_account_active, add_agent_audit_log, list_agent_audit_logs,
|
||||
create_learner_run, end_learner_run, list_learner_runs, add_workflow_event, list_workflow_events,
|
||||
store_refresh_token, refresh_token_active, revoke_refresh_token, deployment_policy_profile, list_packs_for_user,
|
||||
get_pack, get_pack_row, 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, build_animation_frames
|
||||
from .auth import issue_access_token, issue_refresh_token, issue_service_access_token, decode_token, new_token_id, new_secret
|
||||
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=["*"])
|
||||
|
||||
def current_user(authorization: str = Header(default="")):
|
||||
def current_actor(authorization: str = Header(default="")):
|
||||
token = authorization.removeprefix("Bearer ").strip()
|
||||
payload = decode_token(token) if token else None
|
||||
if not payload or payload.get("kind") != "access":
|
||||
if not payload:
|
||||
raise HTTPException(status_code=401, detail="Unauthorized")
|
||||
user = get_user_by_id(int(payload["sub"]))
|
||||
if user is None or not user.is_active:
|
||||
raise HTTPException(status_code=401, detail="Unauthorized")
|
||||
return user
|
||||
if payload.get("kind") == "access":
|
||||
user = get_user_by_id(int(payload["sub"]))
|
||||
if user is None or not user.is_active:
|
||||
raise HTTPException(status_code=401, detail="Unauthorized")
|
||||
return {"actor_type": "user", "user": user, "scopes": None}
|
||||
if payload.get("kind") == "service":
|
||||
return {
|
||||
"actor_type": "service",
|
||||
"service_account_id": int(payload["sub"]),
|
||||
"service_account_name": payload.get("service_account_name"),
|
||||
"scopes": payload.get("scopes", []),
|
||||
}
|
||||
raise HTTPException(status_code=401, detail="Unauthorized")
|
||||
|
||||
def ensure_learner_access(user, learner_id: str):
|
||||
def require_admin(actor = Depends(current_actor)):
|
||||
if actor["actor_type"] != "user" or actor["user"].role != "admin":
|
||||
raise HTTPException(status_code=403, detail="Admin role required")
|
||||
return actor["user"]
|
||||
|
||||
def audit_service_action(actor, action: str, target: str, outcome: str = "ok", detail: dict | None = None):
|
||||
if actor["actor_type"] == "service":
|
||||
add_agent_audit_log(
|
||||
actor["service_account_id"],
|
||||
actor["service_account_name"],
|
||||
action,
|
||||
target,
|
||||
outcome,
|
||||
detail or {},
|
||||
)
|
||||
|
||||
def require_scope(scope: str):
|
||||
def inner(actor = Depends(current_actor)):
|
||||
if actor["actor_type"] == "user":
|
||||
return actor
|
||||
scopes = set(actor.get("scopes") or [])
|
||||
if scope not in scopes:
|
||||
audit_service_action(actor, f"scope_denied:{scope}", "", "denied", {"scope": scope})
|
||||
raise HTTPException(status_code=403, detail=f"Missing scope: {scope}")
|
||||
return actor
|
||||
return inner
|
||||
|
||||
def ensure_learner_access(actor, learner_id: str):
|
||||
if actor["actor_type"] == "service":
|
||||
return
|
||||
user = actor["user"]
|
||||
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")
|
||||
raise HTTPException(status_code=403, detail="Learner not accessible by this actor")
|
||||
|
||||
def ensure_pack_access(user, pack_id: str):
|
||||
def ensure_pack_access(actor, pack_id: str):
|
||||
row = get_pack_row(pack_id)
|
||||
if row is None:
|
||||
raise HTTPException(status_code=404, detail="Pack not found")
|
||||
if actor["actor_type"] == "service":
|
||||
return row
|
||||
user = actor["user"]
|
||||
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")
|
||||
raise HTTPException(status_code=403, detail="Pack not accessible by this actor")
|
||||
|
||||
@app.post("/api/login", response_model=TokenPair)
|
||||
def login(payload: LoginRequest):
|
||||
|
|
@ -50,6 +108,14 @@ def login(payload: LoginRequest):
|
|||
store_refresh_token(user.id, token_id)
|
||||
return TokenPair(access_token=issue_access_token(user.id, user.username, user.role), refresh_token=issue_refresh_token(user.id, user.username, user.role, token_id), username=user.username, role=user.role)
|
||||
|
||||
@app.post("/api/service-accounts/login", response_model=ServiceToken)
|
||||
def service_login(payload: ServiceAccountLoginRequest):
|
||||
sa = authenticate_service_account(payload.name, payload.secret)
|
||||
if sa is None:
|
||||
raise HTTPException(status_code=401, detail="Invalid service account credentials")
|
||||
scopes = json.loads(sa.scopes_json or "[]")
|
||||
return ServiceToken(access_token=issue_service_access_token(sa.id, sa.name, scopes), service_account_name=sa.name, scopes=scopes)
|
||||
|
||||
@app.post("/api/refresh", response_model=TokenPair)
|
||||
def refresh(payload: RefreshRequest):
|
||||
data = decode_token(payload.refresh_token)
|
||||
|
|
@ -66,47 +132,189 @@ def refresh(payload: RefreshRequest):
|
|||
store_refresh_token(user.id, new_jti)
|
||||
return TokenPair(access_token=issue_access_token(user.id, user.username, user.role), refresh_token=issue_refresh_token(user.id, user.username, user.role, new_jti), username=user.username, role=user.role)
|
||||
|
||||
@app.get("/api/deployment-policy")
|
||||
def api_deployment_policy(actor = Depends(current_actor)):
|
||||
return deployment_policy_profile().model_dump()
|
||||
|
||||
@app.get("/api/agent/capabilities", response_model=AgentCapabilityManifest)
|
||||
def api_agent_capabilities(actor = Depends(current_actor)):
|
||||
return AgentCapabilityManifest()
|
||||
|
||||
@app.post("/api/agent/learner-plan", response_model=AgentLearnerPlanResponse)
|
||||
def api_agent_learner_plan(payload: AgentLearnerPlanRequest, actor = Depends(require_scope("recommendations:read"))):
|
||||
ensure_learner_access(actor, payload.learner_id)
|
||||
ensure_pack_access(actor, payload.pack_id)
|
||||
state = load_learner_state(payload.learner_id)
|
||||
pack = get_pack(payload.pack_id)
|
||||
if pack is None:
|
||||
raise HTTPException(status_code=404, detail="Pack not found")
|
||||
cards = recommend_next(state, pack)
|
||||
audit_service_action(actor, "agent_learner_plan", f"{payload.learner_id}:{payload.pack_id}", "ok", {"cards": len(cards)})
|
||||
return AgentLearnerPlanResponse(learner_id=payload.learner_id, pack_id=payload.pack_id, next_cards=cards, suggested_actions=["Read learner state", "Choose next card", "Submit evidence", "Refresh recommendations"])
|
||||
|
||||
@app.post("/api/admin/service-accounts")
|
||||
def api_create_service_account(payload: ServiceAccountCreateRequest, user = Depends(require_admin)):
|
||||
secret = new_secret()
|
||||
sa = create_service_account(payload.name, user.id, payload.description, payload.scopes, secret)
|
||||
return {"id": sa.id, "name": sa.name, "scopes": payload.scopes, "secret": secret}
|
||||
|
||||
@app.get("/api/admin/service-accounts")
|
||||
def api_list_service_accounts(user = Depends(require_admin)):
|
||||
return list_service_accounts()
|
||||
|
||||
@app.post("/api/admin/service-accounts/rotate")
|
||||
def api_rotate_service_account(payload: ServiceAccountRotateRequest, user = Depends(require_admin)):
|
||||
secret = new_secret()
|
||||
sa = rotate_service_account_secret(payload.name, secret)
|
||||
if sa is None:
|
||||
raise HTTPException(status_code=404, detail="Service account not found")
|
||||
return {"name": sa.name, "secret": secret}
|
||||
|
||||
@app.post("/api/admin/service-accounts/state")
|
||||
def api_service_account_state(payload: ServiceAccountStateRequest, name: str, user = Depends(require_admin)):
|
||||
sa = set_service_account_active(name, payload.is_active)
|
||||
if sa is None:
|
||||
raise HTTPException(status_code=404, detail="Service account not found")
|
||||
return {"name": sa.name, "is_active": sa.is_active}
|
||||
|
||||
@app.get("/api/admin/agent-audit-logs")
|
||||
def api_agent_audit_logs(user = Depends(require_admin)):
|
||||
return list_agent_audit_logs()
|
||||
|
||||
@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"))]
|
||||
def api_list_packs(actor = Depends(require_scope("packs:read"))):
|
||||
user_id = actor["user"].id if actor["actor_type"] == "user" else None
|
||||
packs = [p.model_dump() for p in list_packs_for_user(user_id, include_unpublished=(actor["actor_type"] == "user" and actor["user"].role == "admin"))]
|
||||
audit_service_action(actor, "packs_list", "packs", "ok", {"count": len(packs)})
|
||||
return packs
|
||||
|
||||
@app.post("/api/packs")
|
||||
def api_upsert_personal_pack(payload: CreatePackRequest, actor = Depends(require_scope("packs:write_personal"))):
|
||||
if payload.policy_lane != "personal":
|
||||
raise HTTPException(status_code=403, detail="This endpoint is for personal-lane write access")
|
||||
if actor["actor_type"] != "user":
|
||||
raise HTTPException(status_code=403, detail="Service accounts may not own personal packs in this scaffold")
|
||||
upsert_pack(payload.pack, submitted_by_user_id=actor["user"].id, policy_lane="personal", is_published=payload.is_published, change_summary=payload.change_summary)
|
||||
return {"ok": True, "pack_id": payload.pack.id, "policy_lane": "personal"}
|
||||
|
||||
@app.post("/api/learners")
|
||||
def api_create_learner(payload: CreateLearnerRequest, user = Depends(current_user)):
|
||||
create_learner(user.id, payload.learner_id, payload.display_name)
|
||||
def api_create_learner(payload: CreateLearnerRequest, actor = Depends(require_scope("learners:write"))):
|
||||
if actor["actor_type"] != "user":
|
||||
raise HTTPException(status_code=403, detail="Service accounts do not create learners in this scaffold")
|
||||
create_learner(actor["user"].id, payload.learner_id, payload.display_name)
|
||||
return {"ok": True, "learner_id": payload.learner_id}
|
||||
|
||||
@app.get("/api/learners/{learner_id}/state")
|
||||
def api_get_learner_state(learner_id: str, user = Depends(current_user)):
|
||||
ensure_learner_access(user, learner_id)
|
||||
return load_learner_state(learner_id).model_dump()
|
||||
def api_get_learner_state(learner_id: str, actor = Depends(require_scope("learners:read"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
state = load_learner_state(learner_id).model_dump()
|
||||
audit_service_action(actor, "learner_state_read", learner_id, "ok", {"records": len(state.get("records", []))})
|
||||
return state
|
||||
|
||||
@app.put("/api/learners/{learner_id}/state")
|
||||
def api_put_learner_state(learner_id: str, state: LearnerState, user = Depends(current_user)):
|
||||
ensure_learner_access(user, learner_id)
|
||||
def api_put_learner_state(learner_id: str, state: LearnerState, actor = Depends(require_scope("learners:write"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
if learner_id != state.learner_id:
|
||||
raise HTTPException(status_code=400, detail="Learner ID mismatch")
|
||||
return save_learner_state(state).model_dump()
|
||||
result = save_learner_state(state).model_dump()
|
||||
audit_service_action(actor, "learner_state_write", learner_id, "ok", {"records": len(result.get("records", []))})
|
||||
return result
|
||||
|
||||
@app.get("/api/packs/{pack_id}/layout")
|
||||
def api_pack_layout(pack_id: str, user = Depends(current_user)):
|
||||
ensure_pack_access(user, pack_id)
|
||||
@app.post("/api/learners/{learner_id}/evidence")
|
||||
def api_post_evidence(learner_id: str, event: EvidenceEvent, actor = Depends(require_scope("learners:write"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
state = load_learner_state(learner_id)
|
||||
state = apply_evidence(state, event)
|
||||
result = save_learner_state(state).model_dump()
|
||||
audit_service_action(actor, "learner_evidence_post", learner_id, "ok", {"concept_id": event.concept_id})
|
||||
return result
|
||||
|
||||
@app.get("/api/learners/{learner_id}/recommendations/{pack_id}")
|
||||
def api_get_recommendations(learner_id: str, pack_id: str, actor = Depends(require_scope("recommendations:read"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
ensure_pack_access(actor, pack_id)
|
||||
state = load_learner_state(learner_id)
|
||||
pack = get_pack(pack_id)
|
||||
return {"pack_id": pack_id, "layout": stable_layout(pack)} if pack else {"pack_id": pack_id, "layout": {}}
|
||||
if pack is None:
|
||||
raise HTTPException(status_code=404, detail="Pack not found")
|
||||
cards = recommend_next(state, pack)
|
||||
audit_service_action(actor, "recommendations_read", f"{learner_id}:{pack_id}", "ok", {"cards": len(cards)})
|
||||
return {"cards": cards}
|
||||
|
||||
@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)
|
||||
@app.post("/api/learners/{learner_id}/evaluator-jobs", response_model=EvaluatorJobStatus)
|
||||
def api_submit_evaluator_job(learner_id: str, payload: EvaluatorSubmission, background_tasks: BackgroundTasks, actor = Depends(require_scope("evaluators:submit"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
ensure_pack_access(actor, payload.pack_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)
|
||||
audit_service_action(actor, "evaluator_job_submit", str(job_id), "ok", {"learner_id": learner_id, "pack_id": payload.pack_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, actor = Depends(require_scope("evaluators:read"))):
|
||||
job = get_evaluator_job(job_id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="Job not found")
|
||||
audit_service_action(actor, "evaluator_job_read", str(job_id), "ok", {})
|
||||
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, actor = Depends(require_scope("evaluators:read"))):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
jobs = list_evaluator_jobs_for_learner(learner_id)
|
||||
audit_service_action(actor, "evaluator_history_read", learner_id, "ok", {"jobs": len(jobs)})
|
||||
return [{"job_id": j.id, "status": j.status, "concept_id": j.concept_id, "result_score": j.result_score, "result_confidence_hint": j.result_confidence_hint, "result_notes": j.result_notes} for j in jobs]
|
||||
|
||||
@app.post("/api/learner-runs")
|
||||
def api_create_learner_run(payload: LearnerRunCreateRequest, actor = Depends(current_actor)):
|
||||
ensure_learner_access(actor, payload.learner_id)
|
||||
ensure_pack_access(actor, payload.pack_id)
|
||||
actor_name = actor["service_account_name"] if actor["actor_type"] == "service" else actor["user"].username
|
||||
run_id = create_learner_run(payload.learner_id, payload.pack_id, payload.actor_kind, actor_name, payload.title)
|
||||
audit_service_action(actor, "learner_run_create", str(run_id), "ok", {"learner_id": payload.learner_id, "pack_id": payload.pack_id})
|
||||
return {"run_id": run_id}
|
||||
|
||||
@app.post("/api/learner-runs/{run_id}/complete")
|
||||
def api_complete_learner_run(run_id: int, actor = Depends(current_actor)):
|
||||
row = end_learner_run(run_id)
|
||||
if row is None:
|
||||
raise HTTPException(status_code=404, detail="Run not found")
|
||||
audit_service_action(actor, "learner_run_complete", str(run_id), "ok", {})
|
||||
return {"run_id": run_id, "status": row.status}
|
||||
|
||||
@app.get("/api/learners/{learner_id}/runs")
|
||||
def api_list_learner_runs(learner_id: str, actor = Depends(current_actor)):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
return list_learner_runs(learner_id)
|
||||
|
||||
@app.post("/api/workflow-events")
|
||||
def api_add_workflow_event(payload: WorkflowEventCreateRequest, actor = Depends(current_actor)):
|
||||
ensure_learner_access(actor, payload.learner_id)
|
||||
event_id = add_workflow_event(payload.run_id, payload.learner_id, payload.event_type, payload.concept_id, payload.timestamp, payload.detail)
|
||||
audit_service_action(actor, "workflow_event_add", str(event_id), "ok", {"run_id": payload.run_id, "event_type": payload.event_type})
|
||||
return {"event_id": event_id}
|
||||
|
||||
@app.get("/api/learner-runs/{run_id}/workflow-events")
|
||||
def api_list_workflow_events(run_id: int, actor = Depends(current_actor)):
|
||||
events = list_workflow_events(run_id)
|
||||
audit_service_action(actor, "workflow_events_read", str(run_id), "ok", {"count": len(events)})
|
||||
return events
|
||||
|
||||
@app.get("/api/learners/{learner_id}/animation/{pack_id}")
|
||||
def api_learning_animation(learner_id: str, pack_id: str, actor = Depends(current_actor)):
|
||||
ensure_learner_access(actor, learner_id)
|
||||
ensure_pack_access(actor, pack_id)
|
||||
pack = get_pack(pack_id)
|
||||
state = load_learner_state(learner_id)
|
||||
frames = build_graph_frames(state, pack)
|
||||
frames = build_animation_frames(state)
|
||||
audit_service_action(actor, "learning_animation_read", f"{learner_id}:{pack_id}", "ok", {"frames": len(frames)})
|
||||
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 [],
|
||||
"concepts": [c.id for c in pack.concepts] if pack else [],
|
||||
}
|
||||
|
||||
def main():
|
||||
uvicorn.run(app, host="127.0.0.1", port=8011)
|
||||
uvicorn.run(app, host=settings.host, port=settings.port)
|
||||
|
|
|
|||
|
|
@ -25,6 +25,9 @@ def issue_access_token(user_id: int, username: str, role: str) -> str:
|
|||
def issue_refresh_token(user_id: int, username: str, role: str, token_id: str) -> str:
|
||||
return _encode_token({"sub": str(user_id), "username": username, "role": role, "kind": "refresh", "jti": token_id}, timedelta(days=14))
|
||||
|
||||
def issue_service_access_token(service_account_id: int, name: str, scopes: list[str]) -> str:
|
||||
return _encode_token({"sub": str(service_account_id), "service_account_name": name, "kind": "service", "scopes": scopes}, timedelta(hours=8))
|
||||
|
||||
def decode_token(token: str) -> dict | None:
|
||||
try:
|
||||
return jwt.decode(token, settings.jwt_secret, algorithms=[settings.jwt_algorithm])
|
||||
|
|
@ -33,3 +36,6 @@ def decode_token(token: str) -> dict | None:
|
|||
|
||||
def new_token_id() -> str:
|
||||
return secrets.token_urlsafe(24)
|
||||
|
||||
def new_secret() -> str:
|
||||
return secrets.token_urlsafe(24)
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ class Settings(BaseModel):
|
|||
port: int = int(os.getenv("DIDACTOPUS_PORT", "8011"))
|
||||
jwt_secret: str = os.getenv("DIDACTOPUS_JWT_SECRET", "change-me")
|
||||
jwt_algorithm: str = "HS256"
|
||||
deployment_policy_profile: str = os.getenv("DIDACTOPUS_POLICY_PROFILE", "single_user")
|
||||
|
||||
def load_settings() -> Settings:
|
||||
return Settings()
|
||||
|
|
|
|||
|
|
@ -1,110 +1,76 @@
|
|||
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,
|
||||
})
|
||||
return cards[:4]
|
||||
|
||||
def build_animation_frames(state: LearnerState):
|
||||
concepts = sorted({ev.concept_id for ev in state.history} | {r.concept_id for r in state.records})
|
||||
frames = []
|
||||
running = {c: 0.0 for c in concepts}
|
||||
for idx, ev in enumerate(sorted(state.history, key=lambda x: x.timestamp)):
|
||||
running[ev.concept_id] = ev.score
|
||||
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,
|
||||
"concept_id": ev.concept_id,
|
||||
"scores": dict(running),
|
||||
})
|
||||
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})
|
||||
frames.append({"index": 0, "timestamp": "", "event_kind": "empty", "concept_id": "", "scores": dict(running)})
|
||||
return frames
|
||||
|
|
|
|||
|
|
@ -1,5 +1,9 @@
|
|||
from __future__ import annotations
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Literal
|
||||
|
||||
EvidenceKind = Literal["checkpoint", "project", "exercise", "review"]
|
||||
PolicyLane = Literal["personal", "community"]
|
||||
|
||||
class TokenPair(BaseModel):
|
||||
access_token: str
|
||||
|
|
@ -8,22 +12,58 @@ class TokenPair(BaseModel):
|
|||
username: str
|
||||
role: str
|
||||
|
||||
class ServiceToken(BaseModel):
|
||||
access_token: str
|
||||
token_type: str = "bearer"
|
||||
service_account_name: str
|
||||
scopes: list[str]
|
||||
|
||||
class LoginRequest(BaseModel):
|
||||
username: str
|
||||
password: str
|
||||
|
||||
class ServiceAccountLoginRequest(BaseModel):
|
||||
name: str
|
||||
secret: str
|
||||
|
||||
class ServiceAccountCreateRequest(BaseModel):
|
||||
name: str
|
||||
description: str = ""
|
||||
scopes: list[str] = Field(default_factory=list)
|
||||
|
||||
class ServiceAccountRotateRequest(BaseModel):
|
||||
name: str
|
||||
|
||||
class ServiceAccountStateRequest(BaseModel):
|
||||
is_active: bool
|
||||
|
||||
class RefreshRequest(BaseModel):
|
||||
refresh_token: str
|
||||
|
||||
class GraphPosition(BaseModel):
|
||||
x: float
|
||||
y: float
|
||||
class DeploymentPolicyProfile(BaseModel):
|
||||
profile_name: str
|
||||
default_personal_lane_enabled: bool = True
|
||||
default_community_lane_enabled: bool = True
|
||||
community_publish_requires_approval: bool = True
|
||||
personal_publish_direct: bool = True
|
||||
reviewer_assignment_required: bool = False
|
||||
description: str = ""
|
||||
|
||||
class CrossPackLink(BaseModel):
|
||||
source_concept_id: str
|
||||
target_pack_id: str
|
||||
target_concept_id: str
|
||||
relationship: str = "related"
|
||||
class AgentCapabilityManifest(BaseModel):
|
||||
supports_pack_listing: bool = True
|
||||
supports_pack_write_personal: bool = True
|
||||
supports_pack_submit_community: bool = True
|
||||
supports_recommendations: bool = True
|
||||
supports_learner_state_read: bool = True
|
||||
supports_learner_state_write: bool = True
|
||||
supports_evaluator_jobs: bool = True
|
||||
supports_governance_endpoints: bool = True
|
||||
supports_review_queue: bool = True
|
||||
supports_service_accounts: bool = True
|
||||
supports_agent_audit_logs: bool = True
|
||||
supports_service_account_rotation: bool = True
|
||||
supports_learner_runs: bool = True
|
||||
supports_learning_animation: bool = True
|
||||
|
||||
class PackConcept(BaseModel):
|
||||
id: str
|
||||
|
|
@ -31,8 +71,13 @@ class PackConcept(BaseModel):
|
|||
prerequisites: list[str] = Field(default_factory=list)
|
||||
masteryDimension: str = "mastery"
|
||||
exerciseReward: str = ""
|
||||
position: GraphPosition | None = None
|
||||
cross_pack_links: list[CrossPackLink] = Field(default_factory=list)
|
||||
|
||||
class PackCompliance(BaseModel):
|
||||
sources: int = 0
|
||||
attributionRequired: bool = False
|
||||
shareAlikeRequired: bool = False
|
||||
noncommercialOnly: bool = False
|
||||
flags: list[str] = Field(default_factory=list)
|
||||
|
||||
class PackData(BaseModel):
|
||||
id: str
|
||||
|
|
@ -41,12 +86,32 @@ 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 CreatePackRequest(BaseModel):
|
||||
pack: PackData
|
||||
policy_lane: PolicyLane = "personal"
|
||||
is_published: bool = False
|
||||
change_summary: str = ""
|
||||
|
||||
class CreateLearnerRequest(BaseModel):
|
||||
learner_id: str
|
||||
display_name: str = ""
|
||||
|
||||
class LearnerRunCreateRequest(BaseModel):
|
||||
learner_id: str
|
||||
pack_id: str
|
||||
title: str = ""
|
||||
actor_kind: str = "human"
|
||||
|
||||
class WorkflowEventCreateRequest(BaseModel):
|
||||
run_id: int
|
||||
learner_id: str
|
||||
event_type: str
|
||||
concept_id: str = ""
|
||||
timestamp: str
|
||||
detail: dict = Field(default_factory=dict)
|
||||
|
||||
class MasteryRecord(BaseModel):
|
||||
concept_id: str
|
||||
dimension: str
|
||||
|
|
@ -61,10 +126,33 @@ class EvidenceEvent(BaseModel):
|
|||
score: float
|
||||
confidence_hint: float = 0.5
|
||||
timestamp: str
|
||||
kind: str = "exercise"
|
||||
kind: EvidenceKind = "exercise"
|
||||
source_id: str = ""
|
||||
|
||||
class LearnerState(BaseModel):
|
||||
learner_id: str
|
||||
records: list[MasteryRecord] = Field(default_factory=list)
|
||||
history: list[EvidenceEvent] = Field(default_factory=list)
|
||||
|
||||
class EvaluatorSubmission(BaseModel):
|
||||
pack_id: str
|
||||
concept_id: str
|
||||
submitted_text: str
|
||||
kind: str = "checkpoint"
|
||||
|
||||
class EvaluatorJobStatus(BaseModel):
|
||||
job_id: int
|
||||
status: str
|
||||
result_score: float | None = None
|
||||
result_confidence_hint: float | None = None
|
||||
result_notes: str = ""
|
||||
|
||||
class AgentLearnerPlanRequest(BaseModel):
|
||||
learner_id: str
|
||||
pack_id: str
|
||||
|
||||
class AgentLearnerPlanResponse(BaseModel):
|
||||
learner_id: str
|
||||
pack_id: str
|
||||
next_cards: list[dict] = Field(default_factory=list)
|
||||
suggested_actions: list[str] = Field(default_factory=list)
|
||||
|
|
|
|||
|
|
@ -10,6 +10,49 @@ class UserORM(Base):
|
|||
role: Mapped[str] = mapped_column(String(50), default="learner")
|
||||
is_active: Mapped[bool] = mapped_column(Boolean, default=True)
|
||||
|
||||
class ServiceAccountORM(Base):
|
||||
__tablename__ = "service_accounts"
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True)
|
||||
name: Mapped[str] = mapped_column(String(120), unique=True, index=True)
|
||||
owner_user_id: Mapped[int | None] = mapped_column(ForeignKey("users.id"), nullable=True)
|
||||
description: Mapped[str] = mapped_column(Text, default="")
|
||||
scopes_json: Mapped[str] = mapped_column(Text, default="[]")
|
||||
secret_hash: Mapped[str] = mapped_column(String(255))
|
||||
is_active: Mapped[bool] = mapped_column(Boolean, default=True)
|
||||
|
||||
class AgentAuditLogORM(Base):
|
||||
__tablename__ = "agent_audit_logs"
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True)
|
||||
service_account_id: Mapped[int] = mapped_column(ForeignKey("service_accounts.id"), index=True)
|
||||
service_account_name: Mapped[str] = mapped_column(String(120), index=True)
|
||||
action: Mapped[str] = mapped_column(String(120), index=True)
|
||||
target: Mapped[str] = mapped_column(String(255), default="")
|
||||
outcome: Mapped[str] = mapped_column(String(50), default="ok")
|
||||
detail_json: Mapped[str] = mapped_column(Text, default="{}")
|
||||
created_at: Mapped[str] = mapped_column(String(100), default="")
|
||||
|
||||
class LearnerRunORM(Base):
|
||||
__tablename__ = "learner_runs"
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True)
|
||||
learner_id: Mapped[str] = mapped_column(String(100), index=True)
|
||||
pack_id: Mapped[str] = mapped_column(String(100), index=True)
|
||||
actor_kind: Mapped[str] = mapped_column(String(50), default="human")
|
||||
actor_name: Mapped[str] = mapped_column(String(120), default="")
|
||||
title: Mapped[str] = mapped_column(String(255), default="")
|
||||
status: Mapped[str] = mapped_column(String(50), default="running")
|
||||
started_at: Mapped[str] = mapped_column(String(100), default="")
|
||||
ended_at: Mapped[str] = mapped_column(String(100), default="")
|
||||
|
||||
class WorkflowEventORM(Base):
|
||||
__tablename__ = "workflow_events"
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True)
|
||||
run_id: Mapped[int] = mapped_column(ForeignKey("learner_runs.id"), index=True)
|
||||
learner_id: Mapped[str] = mapped_column(String(100), index=True)
|
||||
event_type: Mapped[str] = mapped_column(String(100), index=True)
|
||||
concept_id: Mapped[str] = mapped_column(String(100), default="")
|
||||
timestamp: Mapped[str] = mapped_column(String(100), default="")
|
||||
detail_json: Mapped[str] = mapped_column(Text, default="{}")
|
||||
|
||||
class RefreshTokenORM(Base):
|
||||
__tablename__ = "refresh_tokens"
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True)
|
||||
|
|
@ -26,6 +69,10 @@ class PackORM(Base):
|
|||
subtitle: Mapped[str] = mapped_column(Text, default="")
|
||||
level: Mapped[str] = mapped_column(String(100), default="novice-friendly")
|
||||
data_json: Mapped[str] = mapped_column(Text)
|
||||
validation_json: Mapped[str] = mapped_column(Text, default="{}")
|
||||
provenance_json: Mapped[str] = mapped_column(Text, default="{}")
|
||||
governance_state: Mapped[str] = mapped_column(String(50), default="draft")
|
||||
current_version: Mapped[int] = mapped_column(Integer, default=1)
|
||||
is_published: Mapped[bool] = mapped_column(Boolean, default=False)
|
||||
|
||||
class LearnerORM(Base):
|
||||
|
|
@ -56,3 +103,16 @@ 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="")
|
||||
trace_json: Mapped[str] = mapped_column(Text, default="{}")
|
||||
|
|
|
|||
|
|
@ -1,10 +1,28 @@
|
|||
from __future__ import annotations
|
||||
import json
|
||||
from datetime import datetime, timezone
|
||||
from sqlalchemy import select
|
||||
from .db import SessionLocal
|
||||
from .orm import UserORM, RefreshTokenORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM
|
||||
from .models import PackData, LearnerState, MasteryRecord, EvidenceEvent
|
||||
from .auth import verify_password
|
||||
from .orm import UserORM, ServiceAccountORM, AgentAuditLogORM, LearnerRunORM, WorkflowEventORM, RefreshTokenORM, PackORM, LearnerORM, MasteryRecordORM, EvidenceEventORM, EvaluatorJobORM
|
||||
from .models import PackData, LearnerState, MasteryRecord, EvidenceEvent, DeploymentPolicyProfile
|
||||
from .auth import verify_password, hash_password
|
||||
from .config import load_settings
|
||||
|
||||
settings = load_settings()
|
||||
|
||||
def now_iso() -> str:
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
def deployment_policy_profile() -> DeploymentPolicyProfile:
|
||||
return DeploymentPolicyProfile(
|
||||
profile_name=settings.deployment_policy_profile,
|
||||
default_personal_lane_enabled=True,
|
||||
default_community_lane_enabled=True,
|
||||
community_publish_requires_approval=True,
|
||||
personal_publish_direct=True,
|
||||
reviewer_assignment_required=False,
|
||||
description="Deployment policy scaffold."
|
||||
)
|
||||
|
||||
def get_user_by_username(username: str):
|
||||
with SessionLocal() as db:
|
||||
|
|
@ -20,6 +38,153 @@ def authenticate_user(username: str, password: str):
|
|||
return None
|
||||
return user
|
||||
|
||||
def create_service_account(name: str, owner_user_id: int | None, description: str, scopes: list[str], secret: str):
|
||||
with SessionLocal() as db:
|
||||
sa = ServiceAccountORM(
|
||||
name=name,
|
||||
owner_user_id=owner_user_id,
|
||||
description=description,
|
||||
scopes_json=json.dumps(scopes),
|
||||
secret_hash=hash_password(secret),
|
||||
is_active=True,
|
||||
)
|
||||
db.add(sa)
|
||||
db.commit()
|
||||
db.refresh(sa)
|
||||
return sa
|
||||
|
||||
def list_service_accounts():
|
||||
with SessionLocal() as db:
|
||||
rows = db.execute(select(ServiceAccountORM).order_by(ServiceAccountORM.id)).scalars().all()
|
||||
return [{"id": r.id, "name": r.name, "owner_user_id": r.owner_user_id, "description": r.description, "scopes": json.loads(r.scopes_json or "[]"), "is_active": r.is_active} for r in rows]
|
||||
|
||||
def get_service_account_by_name(name: str):
|
||||
with SessionLocal() as db:
|
||||
return db.execute(select(ServiceAccountORM).where(ServiceAccountORM.name == name)).scalar_one_or_none()
|
||||
|
||||
def authenticate_service_account(name: str, secret: str):
|
||||
sa = get_service_account_by_name(name)
|
||||
if sa is None or not sa.is_active or not verify_password(secret, sa.secret_hash):
|
||||
return None
|
||||
return sa
|
||||
|
||||
def rotate_service_account_secret(name: str, new_secret: str):
|
||||
with SessionLocal() as db:
|
||||
sa = db.execute(select(ServiceAccountORM).where(ServiceAccountORM.name == name)).scalar_one_or_none()
|
||||
if sa is None:
|
||||
return None
|
||||
sa.secret_hash = hash_password(new_secret)
|
||||
db.commit()
|
||||
db.refresh(sa)
|
||||
return sa
|
||||
|
||||
def set_service_account_active(name: str, is_active: bool):
|
||||
with SessionLocal() as db:
|
||||
sa = db.execute(select(ServiceAccountORM).where(ServiceAccountORM.name == name)).scalar_one_or_none()
|
||||
if sa is None:
|
||||
return None
|
||||
sa.is_active = is_active
|
||||
db.commit()
|
||||
db.refresh(sa)
|
||||
return sa
|
||||
|
||||
def add_agent_audit_log(service_account_id: int, service_account_name: str, action: str, target: str, outcome: str, detail: dict):
|
||||
with SessionLocal() as db:
|
||||
db.add(AgentAuditLogORM(
|
||||
service_account_id=service_account_id,
|
||||
service_account_name=service_account_name,
|
||||
action=action,
|
||||
target=target,
|
||||
outcome=outcome,
|
||||
detail_json=json.dumps(detail),
|
||||
created_at=now_iso(),
|
||||
))
|
||||
db.commit()
|
||||
|
||||
def list_agent_audit_logs(limit: int = 200):
|
||||
with SessionLocal() as db:
|
||||
rows = db.execute(select(AgentAuditLogORM).order_by(AgentAuditLogORM.id.desc())).scalars().all()[:limit]
|
||||
return [{
|
||||
"id": r.id,
|
||||
"service_account_id": r.service_account_id,
|
||||
"service_account_name": r.service_account_name,
|
||||
"action": r.action,
|
||||
"target": r.target,
|
||||
"outcome": r.outcome,
|
||||
"detail": json.loads(r.detail_json or "{}"),
|
||||
"created_at": r.created_at,
|
||||
} for r in rows]
|
||||
|
||||
def create_learner_run(learner_id: str, pack_id: str, actor_kind: str, actor_name: str, title: str):
|
||||
with SessionLocal() as db:
|
||||
row = LearnerRunORM(
|
||||
learner_id=learner_id,
|
||||
pack_id=pack_id,
|
||||
actor_kind=actor_kind,
|
||||
actor_name=actor_name,
|
||||
title=title,
|
||||
status="running",
|
||||
started_at=now_iso(),
|
||||
ended_at="",
|
||||
)
|
||||
db.add(row)
|
||||
db.commit()
|
||||
db.refresh(row)
|
||||
return row.id
|
||||
|
||||
def end_learner_run(run_id: int):
|
||||
with SessionLocal() as db:
|
||||
row = db.get(LearnerRunORM, run_id)
|
||||
if row is None:
|
||||
return None
|
||||
row.status = "completed"
|
||||
row.ended_at = now_iso()
|
||||
db.commit()
|
||||
return row
|
||||
|
||||
def list_learner_runs(learner_id: str):
|
||||
with SessionLocal() as db:
|
||||
rows = db.execute(select(LearnerRunORM).where(LearnerRunORM.learner_id == learner_id).order_by(LearnerRunORM.id.desc())).scalars().all()
|
||||
return [{
|
||||
"run_id": r.id,
|
||||
"learner_id": r.learner_id,
|
||||
"pack_id": r.pack_id,
|
||||
"actor_kind": r.actor_kind,
|
||||
"actor_name": r.actor_name,
|
||||
"title": r.title,
|
||||
"status": r.status,
|
||||
"started_at": r.started_at,
|
||||
"ended_at": r.ended_at,
|
||||
} for r in rows]
|
||||
|
||||
def add_workflow_event(run_id: int, learner_id: str, event_type: str, concept_id: str, timestamp: str, detail: dict):
|
||||
with SessionLocal() as db:
|
||||
row = WorkflowEventORM(
|
||||
run_id=run_id,
|
||||
learner_id=learner_id,
|
||||
event_type=event_type,
|
||||
concept_id=concept_id,
|
||||
timestamp=timestamp,
|
||||
detail_json=json.dumps(detail),
|
||||
)
|
||||
db.add(row)
|
||||
db.commit()
|
||||
db.refresh(row)
|
||||
return row.id
|
||||
|
||||
def list_workflow_events(run_id: int):
|
||||
with SessionLocal() as db:
|
||||
rows = db.execute(select(WorkflowEventORM).where(WorkflowEventORM.run_id == run_id).order_by(WorkflowEventORM.id)).scalars().all()
|
||||
return [{
|
||||
"id": r.id,
|
||||
"run_id": r.run_id,
|
||||
"learner_id": r.learner_id,
|
||||
"event_type": r.event_type,
|
||||
"concept_id": r.concept_id,
|
||||
"timestamp": r.timestamp,
|
||||
"detail": json.loads(r.detail_json or "{}"),
|
||||
} for r in rows]
|
||||
|
||||
def store_refresh_token(user_id: int, token_id: str):
|
||||
with SessionLocal() as db:
|
||||
db.add(RefreshTokenORM(user_id=user_id, token_id=token_id, is_revoked=False))
|
||||
|
|
@ -60,7 +225,9 @@ 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, submitted_by_user_id: int, policy_lane: str = "personal", is_published: bool = False, change_summary: str = ""):
|
||||
validation = {"ok": len(pack.concepts) > 0, "warnings": [] if len(pack.concepts) > 0 else ["Pack has no concepts."], "errors": []}
|
||||
provenance = {"source_count": pack.compliance.sources, "restrictive_flags": list(pack.compliance.flags)}
|
||||
with SessionLocal() as db:
|
||||
row = db.get(PackORM, pack.id)
|
||||
payload = json.dumps(pack.model_dump())
|
||||
|
|
@ -73,6 +240,10 @@ def upsert_pack(pack: PackData, submitted_by_user_id: int, policy_lane: str = "p
|
|||
subtitle=pack.subtitle,
|
||||
level=pack.level,
|
||||
data_json=payload,
|
||||
validation_json=json.dumps(validation),
|
||||
provenance_json=json.dumps(provenance),
|
||||
governance_state="personal_ready" if policy_lane == "personal" else "draft",
|
||||
current_version=1,
|
||||
is_published=is_published if policy_lane == "personal" else False,
|
||||
)
|
||||
db.add(row)
|
||||
|
|
@ -83,6 +254,9 @@ def upsert_pack(pack: PackData, submitted_by_user_id: int, policy_lane: str = "p
|
|||
row.subtitle = pack.subtitle
|
||||
row.level = pack.level
|
||||
row.data_json = payload
|
||||
row.validation_json = json.dumps(validation)
|
||||
row.provenance_json = json.dumps(provenance)
|
||||
row.current_version += 1
|
||||
if policy_lane == "personal":
|
||||
row.is_published = is_published
|
||||
db.commit()
|
||||
|
|
@ -118,3 +292,32 @@ 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):
|
||||
with SessionLocal() as db:
|
||||
job = EvaluatorJobORM(learner_id=learner_id, pack_id=pack_id, concept_id=concept_id, submitted_text=submitted_text, status="queued", trace_json=json.dumps({"notes": ["Job queued"]}))
|
||||
db.add(job)
|
||||
db.commit()
|
||||
db.refresh(job)
|
||||
return job.id
|
||||
|
||||
def list_evaluator_jobs_for_learner(learner_id: str):
|
||||
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 = "", trace: dict | None = None):
|
||||
with SessionLocal() as db:
|
||||
job = db.get(EvaluatorJobORM, job_id)
|
||||
if job is None:
|
||||
return
|
||||
job.status = status
|
||||
job.result_score = score
|
||||
job.result_confidence_hint = confidence_hint
|
||||
job.result_notes = notes
|
||||
if trace is not None:
|
||||
job.trace_json = json.dumps(trace)
|
||||
db.commit()
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@ from .db import Base, engine, SessionLocal
|
|||
from .orm import UserORM
|
||||
from .auth import hash_password
|
||||
from .repository import upsert_pack, create_learner
|
||||
from .models import PackData, PackConcept, GraphPosition, CrossPackLink
|
||||
from .models import PackData, PackConcept, PackCompliance
|
||||
|
||||
def main():
|
||||
Base.metadata.create_all(bind=engine)
|
||||
|
|
@ -20,15 +20,14 @@ def main():
|
|||
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)),
|
||||
PackConcept(id="intro", title="Intro", prerequisites=[], masteryDimension="mastery", exerciseReward="Intro marker"),
|
||||
PackConcept(id="second", title="Second concept", prerequisites=["intro"], masteryDimension="mastery", exerciseReward="Second marker"),
|
||||
],
|
||||
onboarding={"headline":"Start privately"},
|
||||
compliance={}
|
||||
onboarding={"headline":"Start privately","body":"Personal pack lane.","checklist":["Create pack","Use pack"]},
|
||||
compliance=PackCompliance()
|
||||
),
|
||||
submitted_by_user_id=1,
|
||||
policy_lane="personal",
|
||||
is_published=True,
|
||||
change_summary="Initial personal pack"
|
||||
)
|
||||
|
|
|
|||
|
|
@ -8,17 +8,14 @@ def process_job(job_id: int):
|
|||
job = get_evaluator_job(job_id)
|
||||
if job is None:
|
||||
return
|
||||
update_evaluator_job(job_id, "running", trace={"rubric_dimension_scores": [{"dimension": "mastery", "score": 0.35}], "notes": ["Job running", "Prototype trace generated"], "token_count_estimate": len(job.submitted_text.split())})
|
||||
score = 0.78 if len(job.submitted_text.strip()) > 20 else 0.62
|
||||
confidence_hint = 0.72 if len(job.submitted_text.strip()) > 20 else 0.45
|
||||
notes = "Prototype evaluator: longer responses scored somewhat higher."
|
||||
trace = {"rubric_dimension_scores": [{"dimension": "mastery", "score": score}], "notes": ["Prototype evaluator completed", notes], "token_count_estimate": len(job.submitted_text.split()), "decision_basis": ["response length heuristic", "single-dimension mastery proxy"]}
|
||||
update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes, trace=trace)
|
||||
update_evaluator_job(job_id, "completed", score=score, confidence_hint=confidence_hint, notes=notes, trace={"notes": ["completed"]})
|
||||
state = load_learner_state(job.learner_id)
|
||||
state = apply_evidence(state, EvidenceEvent(concept_id=job.concept_id, dimension="mastery", score=score, confidence_hint=confidence_hint, timestamp="2026-03-13T12:00:00+00:00", kind="review", source_id=f"evaluator-job-{job_id}"))
|
||||
save_learner_state(state)
|
||||
|
||||
def main():
|
||||
print("Didactopus worker scaffold running. Replace this with a real queue worker.")
|
||||
while True:
|
||||
time.sleep(60)
|
||||
|
|
|
|||
|
|
@ -3,5 +3,5 @@ from pathlib import Path
|
|||
def test_scaffold_files_exist():
|
||||
assert Path("src/didactopus/api.py").exists()
|
||||
assert Path("src/didactopus/repository.py").exists()
|
||||
assert Path("src/didactopus/export_svg.py").exists()
|
||||
assert Path("webui/src/App.jsx").exists()
|
||||
assert Path("webui/src/api.js").exists()
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@
|
|||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Didactopus Layout-Aware Graph</title>
|
||||
<title>Didactopus Learning Animation</title>
|
||||
<script type="module" src="/src/main.jsx"></script>
|
||||
</head>
|
||||
<body><div id="root"></div></body>
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
{
|
||||
"name": "didactopus-layout-aware-graph-ui",
|
||||
"name": "didactopus-learning-animation-ui",
|
||||
"private": true,
|
||||
"version": "0.1.0",
|
||||
"type": "module",
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import React, { useEffect, useState } from "react";
|
||||
import { login, refresh, fetchPacks, fetchLearnerState, putLearnerState, fetchGraphAnimation } from "./api";
|
||||
import React, { useEffect, useMemo, useState } from "react";
|
||||
import { login, refresh, fetchPacks, fetchLearnerState, putLearnerState, createLearnerRun, addWorkflowEvent, fetchAnimation } from "./api";
|
||||
import { loadAuth, saveAuth, clearAuth } from "./authStore";
|
||||
|
||||
function LoginView({ onAuth }) {
|
||||
|
|
@ -26,41 +26,23 @@ function LoginView({ onAuth }) {
|
|||
);
|
||||
}
|
||||
|
||||
function nodeColor(status) {
|
||||
if (status === "mastered") return "#1f7a1f";
|
||||
if (status === "active") return "#2d6cdf";
|
||||
if (status === "available") return "#c48a00";
|
||||
return "#9aa4b2";
|
||||
}
|
||||
|
||||
function GraphView({ frame }) {
|
||||
function AnimationBars({ frame, concepts }) {
|
||||
if (!frame) return null;
|
||||
return (
|
||||
<svg viewBox="0 0 960 560" className="graph">
|
||||
{frame.edges.map((edge, idx) => {
|
||||
const s = frame.nodes.find((n) => n.id === edge.source);
|
||||
const t = frame.nodes.find((n) => n.id === edge.target);
|
||||
if (!s || !t) return null;
|
||||
return <line key={idx} x1={s.x} y1={s.y} x2={t.x} y2={t.y} stroke="#b8c2cf" strokeWidth="3" markerEnd="url(#arrow)" />;
|
||||
<div className="bars">
|
||||
{concepts.map((concept) => {
|
||||
const value = frame.scores?.[concept] ?? 0;
|
||||
return (
|
||||
<div className="bar-row" key={concept}>
|
||||
<div className="bar-label">{concept}</div>
|
||||
<div className="bar-track">
|
||||
<div className="bar-fill" style={{ width: `${Math.max(0, Math.min(100, value * 100))}%` }} />
|
||||
</div>
|
||||
<div className="bar-value">{value.toFixed(2)}</div>
|
||||
</div>
|
||||
);
|
||||
})}
|
||||
{frame.cross_pack_links.map((edge, idx) => {
|
||||
const s = frame.nodes.find((n) => n.id === edge.source);
|
||||
if (!s) return null;
|
||||
return <line key={`c${idx}`} x1={s.x} y1={s.y} x2={s.x + 120} y2={s.y - 60} stroke="#cc4bc2" strokeWidth="2" strokeDasharray="8 6" />;
|
||||
})}
|
||||
<defs>
|
||||
<marker id="arrow" markerWidth="10" markerHeight="10" refX="8" refY="3" orient="auto" markerUnits="strokeWidth">
|
||||
<path d="M0,0 L0,6 L9,3 z" fill="#b8c2cf" />
|
||||
</marker>
|
||||
</defs>
|
||||
{frame.nodes.map((node) => (
|
||||
<g key={node.id}>
|
||||
<circle cx={node.x} cy={node.y} r={node.size} fill={nodeColor(node.status)} opacity="0.92" />
|
||||
<text x={node.x} y={node.y - 4} textAnchor="middle" className="svg-label">{node.title}</text>
|
||||
<text x={node.x} y={node.y + 14} textAnchor="middle" className="svg-small">{node.score.toFixed(2)} · {node.status}</text>
|
||||
</g>
|
||||
))}
|
||||
</svg>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
|
|
@ -69,7 +51,7 @@ export default function App() {
|
|||
const [packs, setPacks] = useState([]);
|
||||
const [learnerId] = useState("wesley-learner");
|
||||
const [packId, setPackId] = useState("");
|
||||
const [graphData, setGraphData] = useState(null);
|
||||
const [animation, setAnimation] = useState(null);
|
||||
const [frameIndex, setFrameIndex] = useState(0);
|
||||
const [playing, setPlaying] = useState(false);
|
||||
const [message, setMessage] = useState("");
|
||||
|
|
@ -97,9 +79,9 @@ export default function App() {
|
|||
}
|
||||
}
|
||||
|
||||
async function reload(pid) {
|
||||
const data = await guarded((token) => fetchGraphAnimation(token, learnerId, pid));
|
||||
setGraphData(data);
|
||||
async function reloadAnimation(pid) {
|
||||
const data = await guarded((token) => fetchAnimation(token, learnerId, pid));
|
||||
setAnimation(data);
|
||||
setFrameIndex(0);
|
||||
}
|
||||
|
||||
|
|
@ -110,80 +92,92 @@ export default function App() {
|
|||
setPacks(p);
|
||||
const pid = p[0]?.id || "";
|
||||
setPackId(pid);
|
||||
if (pid) await reload(pid);
|
||||
if (pid) await reloadAnimation(pid);
|
||||
}
|
||||
load();
|
||||
}, [auth]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!playing || !graphData?.frames?.length) return;
|
||||
if (!playing || !animation?.frames?.length) return;
|
||||
const t = setInterval(() => {
|
||||
setFrameIndex((idx) => idx >= graphData.frames.length - 1 ? 0 : idx + 1);
|
||||
setFrameIndex((idx) => {
|
||||
if (idx >= animation.frames.length - 1) {
|
||||
return 0;
|
||||
}
|
||||
return idx + 1;
|
||||
});
|
||||
}, 900);
|
||||
return () => clearInterval(t);
|
||||
}, [playing, graphData]);
|
||||
}, [playing, animation]);
|
||||
|
||||
async function generateDemo() {
|
||||
const currentFrame = animation?.frames?.[frameIndex];
|
||||
const concepts = useMemo(() => animation?.concepts || [], [animation]);
|
||||
|
||||
async function simulateLearning() {
|
||||
const run = await guarded((token) => createLearnerRun(token, { learner_id: learnerId, pack_id: packId, title: "Demo animation run", actor_kind: "human" }));
|
||||
let state = await guarded((token) => fetchLearnerState(token, learnerId));
|
||||
const base = Date.now();
|
||||
const events = [
|
||||
["intro", 0.30, "exercise", 0],
|
||||
["intro", 0.78, "review", 1000],
|
||||
["second", 0.42, "exercise", 2000],
|
||||
["second", 0.72, "review", 3000],
|
||||
["third", 0.25, "exercise", 4000],
|
||||
["branch", 0.60, "exercise", 5000],
|
||||
];
|
||||
const latest = {}
|
||||
for (const [cid, score, kind, offset] of events) {
|
||||
const ts = new Date(base + offset).toISOString();
|
||||
state.history.push({ concept_id: cid, dimension: "mastery", score, confidence_hint: 0.6, timestamp: ts, kind, source_id: `demo-${cid}-${offset}` });
|
||||
latest[cid] = { concept_id: cid, dimension: "mastery", score, confidence: Math.min(0.9, score), evidence_count: (latest[cid]?.evidence_count || 0) + 1, last_updated: ts };
|
||||
}
|
||||
state.records = Object.values(latest);
|
||||
const now1 = new Date().toISOString();
|
||||
state.history.push({ concept_id: "intro", dimension: "mastery", score: 0.35, confidence_hint: 0.5, timestamp: now1, kind: "exercise", source_id: "demo-1" });
|
||||
state.records = [{ concept_id: "intro", dimension: "mastery", score: 0.35, confidence: 0.35, evidence_count: 1, last_updated: now1 }];
|
||||
await guarded((token) => putLearnerState(token, learnerId, state));
|
||||
await reload(packId);
|
||||
setMessage("Stable-layout graph demo generated.");
|
||||
await guarded((token) => addWorkflowEvent(token, { run_id: run.run_id, learner_id: learnerId, event_type: "exercise_completed", concept_id: "intro", timestamp: now1, detail: { score: 0.35 } }));
|
||||
|
||||
const now2 = new Date(Date.now() + 1000).toISOString();
|
||||
state.history.push({ concept_id: "intro", dimension: "mastery", score: 0.75, confidence_hint: 0.7, timestamp: now2, kind: "review", source_id: "demo-2" });
|
||||
state.records = [{ concept_id: "intro", dimension: "mastery", score: 0.75, confidence: 0.68, evidence_count: 2, last_updated: now2 }];
|
||||
await guarded((token) => putLearnerState(token, learnerId, state));
|
||||
await guarded((token) => addWorkflowEvent(token, { run_id: run.run_id, learner_id: learnerId, event_type: "review_completed", concept_id: "intro", timestamp: now2, detail: { score: 0.75 } }));
|
||||
|
||||
const now3 = new Date(Date.now() + 2000).toISOString();
|
||||
state.history.push({ concept_id: "second", dimension: "mastery", score: 0.45, confidence_hint: 0.5, timestamp: now3, kind: "exercise", source_id: "demo-3" });
|
||||
state.records = [
|
||||
{ concept_id: "intro", dimension: "mastery", score: 0.75, confidence: 0.68, evidence_count: 2, last_updated: now2 },
|
||||
{ concept_id: "second", dimension: "mastery", score: 0.45, confidence: 0.40, evidence_count: 1, last_updated: now3 },
|
||||
];
|
||||
await guarded((token) => putLearnerState(token, learnerId, state));
|
||||
await guarded((token) => addWorkflowEvent(token, { run_id: run.run_id, learner_id: learnerId, event_type: "unlock_progress", concept_id: "second", timestamp: now3, detail: { score: 0.45 } }));
|
||||
|
||||
await reloadAnimation(packId);
|
||||
setMessage(`Demo run ${run.run_id} generated animation frames.`);
|
||||
}
|
||||
|
||||
if (!auth) return <LoginView onAuth={setAuth} />;
|
||||
|
||||
const frame = graphData?.frames?.[frameIndex];
|
||||
|
||||
return (
|
||||
<div className="page">
|
||||
<header className="hero">
|
||||
<div>
|
||||
<h1>Didactopus layout-aware graph engine</h1>
|
||||
<p>Stable node positions, cross-pack links, and export-ready graph frames.</p>
|
||||
<h1>Didactopus learning animation</h1>
|
||||
<p>Replay mastery changes for human or AI learners over time.</p>
|
||||
<div className="muted">{message}</div>
|
||||
</div>
|
||||
<div className="controls">
|
||||
<label>Pack
|
||||
<select value={packId} onChange={async (e) => { setPackId(e.target.value); await reload(e.target.value); }}>
|
||||
<select value={packId} onChange={async (e) => { setPackId(e.target.value); await reloadAnimation(e.target.value); }}>
|
||||
{packs.map((p) => <option key={p.id} value={p.id}>{p.title}</option>)}
|
||||
</select>
|
||||
</label>
|
||||
<button onClick={() => setPlaying((x) => !x)}>{playing ? "Pause" : "Play"}</button>
|
||||
<button onClick={generateDemo}>Generate demo</button>
|
||||
<button onClick={simulateLearning}>Generate demo run</button>
|
||||
<button onClick={() => { clearAuth(); setAuth(null); }}>Logout</button>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<main className="layout twocol">
|
||||
<section className="card">
|
||||
<h2>Graph animation</h2>
|
||||
<h2>Current frame</h2>
|
||||
<div className="frame-meta">
|
||||
<div><strong>Frame:</strong> {frameIndex + 1} / {graphData?.frames?.length || 0}</div>
|
||||
<div><strong>Event:</strong> {frame?.event_kind || "-"}</div>
|
||||
<div><strong>Focus:</strong> {frame?.focus_concept_id || "-"}</div>
|
||||
<div><strong>Timestamp:</strong> {frame?.timestamp || "-"}</div>
|
||||
<div><strong>Frame:</strong> {frameIndex + 1} / {animation?.frames?.length || 0}</div>
|
||||
<div><strong>Event:</strong> {currentFrame?.event_kind || "-"}</div>
|
||||
<div><strong>Concept:</strong> {currentFrame?.concept_id || "-"}</div>
|
||||
<div><strong>Timestamp:</strong> {currentFrame?.timestamp || "-"}</div>
|
||||
</div>
|
||||
<GraphView frame={frame} />
|
||||
<AnimationBars frame={currentFrame} concepts={concepts} />
|
||||
</section>
|
||||
|
||||
<section className="card">
|
||||
<h2>Frame payload</h2>
|
||||
<pre className="prebox">{JSON.stringify(graphData, null, 2)}</pre>
|
||||
<h2>Animation data</h2>
|
||||
<pre className="prebox">{JSON.stringify(animation, null, 2)}</pre>
|
||||
</section>
|
||||
</main>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -19,4 +19,6 @@ export async function refresh(refreshToken) {
|
|||
export async function fetchPacks(token) { const res = await fetch(`${API}/packs`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchPacks failed"); return await res.json(); }
|
||||
export async function fetchLearnerState(token, learnerId) { const res = await fetch(`${API}/learners/${learnerId}/state`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchLearnerState failed"); return await res.json(); }
|
||||
export async function putLearnerState(token, learnerId, state) { const res = await fetch(`${API}/learners/${learnerId}/state`, { method: "PUT", headers: authHeaders(token), body: JSON.stringify(state) }); if (!res.ok) throw new Error("putLearnerState failed"); return await res.json(); }
|
||||
export async function fetchGraphAnimation(token, learnerId, packId) { const res = await fetch(`${API}/learners/${learnerId}/graph-animation/${packId}`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchGraphAnimation failed"); return await res.json(); }
|
||||
export async function createLearnerRun(token, payload) { const res = await fetch(`${API}/learner-runs`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) }); if (!res.ok) throw new Error("createLearnerRun failed"); return await res.json(); }
|
||||
export async function addWorkflowEvent(token, payload) { const res = await fetch(`${API}/workflow-events`, { method: "POST", headers: authHeaders(token), body: JSON.stringify(payload) }); if (!res.ok) throw new Error("addWorkflowEvent failed"); return await res.json(); }
|
||||
export async function fetchAnimation(token, learnerId, packId) { const res = await fetch(`${API}/learners/${learnerId}/animation/${packId}`, { headers: authHeaders(token, false) }); if (!res.ok) throw new Error("fetchAnimation failed"); return await res.json(); }
|
||||
|
|
|
|||
|
|
@ -10,19 +10,23 @@ body { margin:0; font-family:Arial, Helvetica, sans-serif; background:var(--bg);
|
|||
label { display:block; font-weight:600; }
|
||||
input, select { width:100%; margin-top:6px; border:1px solid var(--border); border-radius:10px; padding:10px; font:inherit; background:white; }
|
||||
button { border:1px solid var(--border); background:white; border-radius:12px; padding:10px 14px; cursor:pointer; }
|
||||
.primary { background:var(--accent); color:white; border-color:var(--accent); }
|
||||
.card { background:var(--card); border:1px solid var(--border); border-radius:18px; padding:18px; }
|
||||
.narrow { margin-top:60px; }
|
||||
.layout { display:grid; gap:16px; }
|
||||
.twocol { grid-template-columns:1fr 1fr; }
|
||||
.prebox { background:#f7f8fa; border:1px solid var(--border); border-radius:12px; padding:12px; overflow:auto; max-height:460px; }
|
||||
.prebox { background:#f7f8fa; border:1px solid var(--border); border-radius:12px; padding:12px; overflow:auto; max-height:420px; }
|
||||
.muted { color:var(--muted); }
|
||||
.error { color:#b42318; margin-top:10px; }
|
||||
.frame-meta { display:grid; grid-template-columns:1fr 1fr; gap:10px; margin-bottom:16px; }
|
||||
.graph { width:100%; height:auto; border:1px solid var(--border); border-radius:16px; background:#fbfcfe; }
|
||||
.svg-label { font-size:12px; fill:#fff; font-weight:bold; }
|
||||
.svg-small { font-size:10px; fill:#fff; }
|
||||
.bars { display:grid; gap:12px; }
|
||||
.bar-row { display:grid; grid-template-columns:140px 1fr 70px; gap:10px; align-items:center; }
|
||||
.bar-track { height:22px; border-radius:999px; background:#eef2f7; overflow:hidden; border:1px solid var(--border); }
|
||||
.bar-fill { height:100%; background:var(--accent); border-radius:999px; }
|
||||
.bar-label, .bar-value { font-size:14px; }
|
||||
@media (max-width:1100px) {
|
||||
.hero { flex-direction:column; }
|
||||
.twocol { grid-template-columns:1fr; }
|
||||
.frame-meta { grid-template-columns:1fr; }
|
||||
.bar-row { grid-template-columns:1fr; }
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue