993e370cea
Brings the new app to full parity with the original L'Oréal SPA and
beyond. Backend 59/59 tests (was 40, +19). Frontend typecheck/lint/build
clean. Main entry chunk 15.76 KB gz (budget 30 KB).
Backend — new endpoints + services:
- POST /api/deliverable/parse — parse Deliverable Summary CSV/XLSX
- POST /api/projectsummary/parse — parse Project Summary CSV/XLSX
- GET /api/timelog/rows — paginated, searchable, sortable view
over the parsed Zoho upload
- GET /api/forecast — 4-week pipeline + capacity decision
- GET /api/project-types — hours/asset, duration, concentration
per project type + auto-insights
- POST /api/chat — Claude API proxy. 503s gracefully
when ANTHROPIC_API_KEY is unset.
Prompt-cached system prompt;
rate-limited 20/min/IP.
- GET /api/auth/me now returns role.
Backend — services:
- zoho_parse.py: extracts ~20 fields (brand, division, hub, userRole,
projectType, assetCount, projectStatus, project start/end dates,
userAgency, employingCompany, sageJobProfile, …) with back-compat
aliases so existing callers keep working.
- parse_store.py: in-process TTL-cached registry of parsed uploads keyed
by content hash. Lets endpoints reference an upload without re-sending it.
- forecast.py: working-day overlap math, exit-rate, weekly throughput
baseline, capacity decision string mirroring the original wording.
- project_types.py: per-type aggregation + concentration-risk insights.
- timelog_filters.py: server-side filter by brands/divisions/hubs/roles.
- ai_context.py: builds the dashboard context block fed to Claude.
Frontend — new pages + components:
- pages/Forecast.tsx — ComposedChart (stacked bars + line)
+ capacity-decision banner + table
- pages/ProjectTypeSummary.tsx — sortable table + small trend chart
- pages/TimeLogDetail.tsx — virtualised, searchable, sortable
view over all parsed timelog rows
- components/ChatView.tsx — floating side panel with Claude.
6 preset prompts mirroring the
original. Visible only for roles
with chat access.
- components/ChatToggle.tsx — bottom-right FAB.
- components/StatsBar.tsx — always-visible: Time Entries /
People / Projects / Total Hours /
Date Range.
- hooks/useDataContext.tsx — single source of truth for filter
state + parsed upload + filter
dimensions (brands/divs/hubs/
roles derived from uploads).
Frontend — modified:
- App.tsx, Navbar.tsx — 7 tabs + role gating per the
original TAB_ACCESS matrix.
- hooks/useAuth.tsx — role + canAccess(tab).
- lib/filters.ts, FilterBar.tsx — Brand / Division / Hub / Role
multiselects added (additive — keep
Department / Name / Billing).
- pages/Department, Resourcing,
Bookings, Tutorial.tsx — wired into DataContext; tutorial
is now a single 9-step global tour
mirroring the original's narrative.
Config:
- backend/.env.example: ADMIN_ROLE, ANTHROPIC_API_KEY, ANTHROPIC_MODEL.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
"""Chat endpoint tests."""
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from __future__ import annotations
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import os
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import pytest
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from fastapi.testclient import TestClient
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def _client_with_bypass():
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os.environ["DEV_AUTH_BYPASS"] = "true"
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os.environ["ANTHROPIC_API_KEY"] = ""
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from app.config import get_settings
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get_settings.cache_clear()
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import importlib
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import app.main as main_mod
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importlib.reload(main_mod)
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return TestClient(main_mod.app, base_url="https://testserver")
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def teardown_module(_mod):
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os.environ["DEV_AUTH_BYPASS"] = "false"
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os.environ.pop("ANTHROPIC_API_KEY", None)
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from app.config import get_settings
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get_settings.cache_clear()
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import importlib
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import app.main as main_mod
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importlib.reload(main_mod)
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def test_chat_503_when_no_api_key():
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c = _client_with_bypass()
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r = c.post("/api/chat", json={
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"messages": [{"role": "user", "content": "hi"}],
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})
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assert r.status_code == 503
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body = r.json()
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assert "AI chat is not configured" in body["detail"]
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def test_chat_400_when_empty_messages():
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# Even with the key set, we should refuse empty messages.
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os.environ["DEV_AUTH_BYPASS"] = "true"
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os.environ["ANTHROPIC_API_KEY"] = "sk-test"
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from app.config import get_settings
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get_settings.cache_clear()
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import importlib
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import app.main as main_mod
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importlib.reload(main_mod)
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c = TestClient(main_mod.app, base_url="https://testserver")
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r = c.post("/api/chat", json={"messages": []})
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# 422 from pydantic validation or 400 from our own check — either is acceptable.
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assert r.status_code in (400, 422)
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