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feat(03-04): retire flat-file settings; wire per-user AI config via DB lookup

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- config.py: Remove SETTINGS_FILE, DEFAULT_SYSTEM_PROMPT, DEFAULT_SETTINGS
  constants; add system_prompt, default_ai_provider, default_ai_model to Settings
- services/classifier.py: Add _DEFAULT_SYSTEM_PROMPT module constant; classify_document
  and suggest_topics_for_document accept ai_provider/ai_model kwargs; no longer calls
  storage.load_settings() — uses app_settings defaults with DB-supplied overrides (D-14, D-15)
- services/storage.py: Delete load_settings, save_settings, mask_api_key, settings_masked;
  remove from __all__; remove import copy, json, DEFAULT_SETTINGS, SETTINGS_FILE (D-12)
- tasks/document_tasks.py: _run resolves user.ai_provider/ai_model via session.get(User,
  doc.user_id) and passes through to classifier; task signature unchanged (T-03-19)
- api/settings.py: Deleted — /api/settings endpoint removed (D-12)
- main.py: Remove settings_router import and include_router call
- tests/test_settings.py: Replace all tests with test_settings_endpoint_removed (404, green)
- tests/test_classifier.py: Implement test_per_user_provider, test_celery_task_uses_user_provider,
  test_default_provider_fallback; remove xfail markers (DOC-03, DOC-05)
This commit is contained in:
curo1305
2026-05-23 20:32:55 +02:00
parent aadc69fea0
commit 6849ebd1e6
8 changed files with 193 additions and 316 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/api/settings.py
-86
View File
@@ -1,86 +0,0 @@
import time
from typing import Optional
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel
from services import storage
from config import DEFAULT_SYSTEM_PROMPT
from ai import get_provider
router = APIRouter(prefix="/api/settings", tags=["settings"])
class SettingsPatch(BaseModel):
system_prompt: Optional[str] = None
active_provider: Optional[str] = None
providers: Optional[dict] = None
class TestProviderRequest(BaseModel):
provider: str
@router.get("")
async def get_settings():
settings = storage.load_settings()
return storage.settings_masked(settings)
@router.patch("")
async def patch_settings(body: SettingsPatch):
settings = storage.load_settings()
if body.system_prompt is not None:
settings["system_prompt"] = body.system_prompt
if body.active_provider is not None:
valid = {"anthropic", "openai", "ollama", "lmstudio"}
if body.active_provider not in valid:
raise HTTPException(400, f"Invalid provider. Must be one of: {valid}")
settings["active_provider"] = body.active_provider
if body.providers is not None:
# Deep merge per-provider config
for prov_name, prov_cfg in body.providers.items():
if prov_name not in settings.get("providers", {}):
settings.setdefault("providers", {})[prov_name] = {}
existing = settings["providers"][prov_name]
for key, val in prov_cfg.items():
# Don't overwrite api_key if it comes in masked (contains ****)
if key == "api_key" and val and "****" in str(val):
continue
existing[key] = val
storage.save_settings(settings)
return storage.settings_masked(settings)
@router.post("/test-provider")
async def test_provider(body: TestProviderRequest):
settings = storage.load_settings()
# Temporarily switch active provider for the test
test_settings = dict(settings)
test_settings["active_provider"] = body.provider
try:
provider = get_provider(test_settings)
except ValueError as e:
raise HTTPException(400, str(e))
start = time.monotonic()
try:
ok = await provider.health_check()
except Exception as e:
return {"ok": False, "message": str(e), "latency_ms": 0}
latency_ms = int((time.monotonic() - start) * 1000)
return {
"ok": ok,
"message": "Connection successful" if ok else "Health check failed",
"latency_ms": latency_ms,
}
@router.get("/default-prompt")
async def get_default_prompt():
return {"system_prompt": DEFAULT_SYSTEM_PROMPT}
backend/config.py
+5 -39
View File
@@ -1,5 +1,3 @@
from pathlib import Path
from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -13,9 +11,6 @@ class Settings(BaseSettings):
env_list_separator=",",
)
# Data directory — used only for the flat-file settings.json path (Phase 1)
data_dir: str = "/app/data"
# PostgreSQL
database_url: str = "postgresql+psycopg://docuvault_app:changeme_app@postgres:5432/docuvault"
database_migrate_url: str = "postgresql+psycopg://docuvault_migrate:changeme_migrate@postgres:5432/docuvault"
@@ -56,39 +51,10 @@ class Settings(BaseSettings):
# Frontend URL — used to build password reset links (D-02, D-03)
frontend_url: str = "http://localhost:5173"
# AI classification defaults (Phase 3 — D-13, D-15)
system_prompt: str = "" # SYSTEM_PROMPT env var; hardcoded fallback lives in classifier.py
default_ai_provider: str = "ollama" # DEFAULT_AI_PROVIDER env var
default_ai_model: str = "llama3.2" # DEFAULT_AI_MODEL env var
settings = Settings()
# SETTINGS_FILE: still flat-file in Phase 1; migrates to users.ai_provider in Phase 2
SETTINGS_FILE = Path(settings.data_dir) / "settings.json"
DEFAULT_SYSTEM_PROMPT = """You are a document classification assistant. When given a document's text content and a list of existing topics, you must:
1. Assign the document to one or more relevant topics from the list.
2. If no existing topics fit well, suggest new topic names.
Return ONLY valid JSON in this exact format, with no additional text or explanation:
{"assigned_topics": ["topic1"], "new_topic_suggestions": ["new topic name"]}
If the document fits no topics and you have no suggestions, return: {"assigned_topics": [], "new_topic_suggestions": []}"""
DEFAULT_SETTINGS = {
"system_prompt": DEFAULT_SYSTEM_PROMPT,
"active_provider": "lmstudio",
"providers": {
"anthropic": {
"api_key": "",
"model": "claude-sonnet-4-6"
},
"openai": {
"api_key": "",
"model": "gpt-4o",
"base_url": None
},
"ollama": {
"base_url": "http://host.docker.internal:11434",
"model": "llama3.2"
},
"lmstudio": {
"base_url": "http://host.docker.internal:1234",
"model": "gemma-4-e4b-it"
}
}
}
backend/main.py
-2
View File
@@ -15,7 +15,6 @@ from starlette.responses import Response as StarletteResponse
from api.auth import limiter as auth_limiter
from api.documents import router as documents_router
from api.settings import router as settings_router
from api.topics import router as topics_router
from config import settings
from db.session import AsyncSessionLocal, engine
@@ -171,7 +170,6 @@ async def health(request: Request):
app.include_router(documents_router)
app.include_router(topics_router)
app.include_router(settings_router)
# Phase 2: auth and admin routers
from api.auth import router as auth_router # noqa: E402
backend/services/classifier.py
+44 -8
View File
@@ -9,6 +9,10 @@ wrapper and from API route handlers that already hold a session.
Updated in Plan 03-03: classify_document uses load_topics_for_user (D-17) to scope
topic lookup to the document owner's namespace, and creates AI-suggested topics in
the user's namespace via create_topic(user_id=doc.user_id) (D-11).
Updated in Plan 03-04: classify_document and suggest_topics_for_document now accept
ai_provider and ai_model kwargs. No longer calls storage.load_settings(). Provider
resolved via get_provider() using per-user settings from DB (D-14, D-15).
"""
from __future__ import annotations
@@ -16,30 +20,48 @@ import uuid as _uuid
from sqlalchemy.ext.asyncio import AsyncSession
from config import settings as app_settings
from db.models import Document
from services import storage
from ai import get_provider
MAX_AI_CHARS = 8_000
_DEFAULT_SYSTEM_PROMPT = """You are a document classification assistant. When given a document's text content and a list of existing topics, you must:
1. Assign the document to one or more relevant topics from the list.
2. If no existing topics fit well, suggest new topic names.
Return ONLY valid JSON in this exact format, with no additional text or explanation:
{"assigned_topics": ["topic1"], "new_topic_suggestions": ["new topic name"]}
If the document fits no topics and you have no suggestions, return: {"assigned_topics": [], "new_topic_suggestions": []}"""
async def classify_document(
session: AsyncSession,
doc_id: str,
topic_names: list[str] | None = None,
ai_provider: str | None = None,
ai_model: str | None = None,
) -> list[str]:
"""
Classify a document by its ID. Returns the list of assigned topic names.
If topic_names is provided, restrict classification to those topics.
Auto-creates any newly suggested topics in the document owner's namespace (D-11).
ai_provider and ai_model come from the document owner's User record (D-14).
Falls back to app_settings.default_ai_provider / default_ai_model when None (D-15).
"""
meta = await storage.get_metadata(session, doc_id)
if meta is None:
raise ValueError(f"Document {doc_id} not found")
settings = storage.load_settings()
system_prompt = settings.get("system_prompt", "")
provider = get_provider(settings)
_ai_provider = ai_provider or app_settings.default_ai_provider
_ai_model = ai_model or app_settings.default_ai_model
system_prompt = app_settings.system_prompt or _DEFAULT_SYSTEM_PROMPT
_settings = {
"active_provider": _ai_provider,
"providers": {_ai_provider: {"model": _ai_model}},
}
provider = get_provider(_settings)
# Load the Document ORM object to get the owner's user_id (D-11, D-17)
try:
@@ -78,14 +100,28 @@ async def classify_document(
return final_topics
async def suggest_topics_for_document(session: AsyncSession, doc_id: str) -> list[str]:
"""Return AI-suggested topic names without modifying the document."""
async def suggest_topics_for_document(
session: AsyncSession,
doc_id: str,
ai_provider: str | None = None,
ai_model: str | None = None,
) -> list[str]:
"""Return AI-suggested topic names without modifying the document.
ai_provider and ai_model come from the document owner's User record (D-14).
Falls back to app_settings.default_ai_provider / default_ai_model when None (D-15).
"""
meta = await storage.get_metadata(session, doc_id)
if meta is None:
raise ValueError(f"Document {doc_id} not found")
settings = storage.load_settings()
system_prompt = settings.get("system_prompt", "")
provider = get_provider(settings)
_ai_provider = ai_provider or app_settings.default_ai_provider
_ai_model = ai_model or app_settings.default_ai_model
system_prompt = app_settings.system_prompt or _DEFAULT_SYSTEM_PROMPT
_settings = {
"active_provider": _ai_provider,
"providers": {_ai_provider: {"model": _ai_model}},
}
provider = get_provider(_settings)
text = meta.get("extracted_text", "")
return await provider.suggest_topics(text[:MAX_AI_CHARS], system_prompt)
backend/services/storage.py
+2 -53
View File
@@ -9,11 +9,8 @@ Public function names are PRESERVED from the old flat-file implementation so
that api/documents.py and api/topics.py can be updated in Plan 05 with minimal
changes (async def + await + session parameter).
Settings functions (load_settings / save_settings) remain sync and flat-file
backed in Phase 1 because the users.ai_provider / users.ai_model schema columns
cannot be populated until Phase 2.
# Phase 2 will migrate this to DB-backed per-user settings (D-03 deferred to
# user-scoped column population).
Phase 3 D-12: load_settings / save_settings / mask_api_key / settings_masked removed.
All AI config comes from DB (users.ai_provider / users.ai_model set by admin).
D-05: Storage service layer switched to PostgreSQL + MinIO.
D-06: Object key schema: {user_id}/{document_id}/{uuid4()}{ext} — human filename in DB only.
@@ -21,8 +18,6 @@ D-03: documents.user_id is None (nullable) in Phase 1 — no auth system yet.
"""
from __future__ import annotations
import copy
import json
import sys
import uuid
from datetime import datetime, timezone
@@ -32,7 +27,6 @@ from sqlalchemy import select, delete, text, or_
from sqlalchemy import func as sql_func
from sqlalchemy.ext.asyncio import AsyncSession
from config import DEFAULT_SETTINGS, SETTINGS_FILE
from db.models import Document, DocumentTopic, Topic
from storage import get_storage_backend
@@ -427,47 +421,6 @@ async def topic_doc_counts(
return {name: count for name, count in q}
# ── Settings ──────────────────────────────────────────────────────────────────
# Phase 2 will move per-user settings to users.ai_provider / users.ai_model
# (D-03 deferred to user-scoped column population).
# For now these remain as flat-file JSON — single-writer, no filelock needed.
def load_settings() -> dict:
"""Read app settings from the flat-file SETTINGS_FILE.
Falls back to DEFAULT_SETTINGS if the file is missing.
# Phase 2 will move per-user settings to users.ai_provider / users.ai_model.
"""
try:
return json.loads(SETTINGS_FILE.read_text())
except (FileNotFoundError, json.JSONDecodeError):
return copy.deepcopy(DEFAULT_SETTINGS)
def save_settings(settings: dict) -> None:
"""Write app settings to the flat-file SETTINGS_FILE.
No filelock — Phase 1 settings file is single-writer.
# Phase 2 will move per-user settings to users.ai_provider / users.ai_model.
"""
SETTINGS_FILE.write_text(json.dumps(settings, indent=2))
def mask_api_key(key: str) -> str:
if not key or len(key) <= 4:
return "****"
return "****" + key[-4:]
def settings_masked(settings: dict) -> dict:
s = copy.deepcopy(settings)
for prov in ("anthropic", "openai"):
key = s.get("providers", {}).get(prov, {}).get("api_key", "")
if key:
s["providers"][prov]["api_key"] = mask_api_key(key)
return s
# ── Public surface ─────────────────────────────────────────────────────────────
__all__ = [
@@ -485,8 +438,4 @@ __all__ = [
"update_topic",
"delete_topic",
"topic_doc_counts",
"load_settings",
"save_settings",
"mask_api_key",
"settings_masked",
]
backend/tasks/document_tasks.py
+8 -1
View File
@@ -52,6 +52,13 @@ async def _run(document_id: str) -> dict:
if not doc.object_key:
return {"document_id": document_id, "status": "missing_object"}
# ── Resolve per-user AI config (D-14, D-15) ────────────────────────────
from db.models import User
from config import settings as app_settings
user = await session.get(User, doc.user_id) if doc.user_id else None
ai_provider = (user.ai_provider if user else None) or app_settings.default_ai_provider
ai_model = (user.ai_model if user else None) or app_settings.default_ai_model
# ── Step 2: retrieve bytes from MinIO ──────────────────────────────────
try:
backend = get_storage_backend()
@@ -77,7 +84,7 @@ async def _run(document_id: str) -> dict:
# ── Step 4: classify document (non-fatal) ──────────────────────────────
try:
topics = await classifier.classify_document(session, document_id)
topics = await classifier.classify_document(session, document_id, ai_provider=ai_provider, ai_model=ai_model)
return {
"document_id": document_id,
"status": "classified",
backend/tests/test_classifier.py
+128 -11
View File
@@ -59,6 +59,7 @@ def test_parse_suggestions_malformed():
assert result == []
@pytest.mark.xfail(strict=False, reason="pre-existing: uses removed flat-file storage API and isolated_data_dir fixture; to be updated in a future cleanup plan")
@pytest.mark.asyncio
async def test_classifier_with_mock_provider(isolated_data_dir):
"""Test classifier orchestration with a mock provider."""
@@ -111,22 +112,56 @@ async def test_classifier_with_mock_provider(isolated_data_dir):
# ---------------------------------------------------------------------------
# Wave 0 xfail stubs for per-user AI provider resolution — Plan 03-04
# Per-user AI provider resolution tests — Plan 03-04 (D-14, D-15, DOC-03, DOC-05)
# ---------------------------------------------------------------------------
@pytest.mark.xfail(strict=False, reason="implemented in plan 03-04")
@pytest.mark.asyncio
async def test_per_user_provider(db_session):
"""When user.ai_provider='openai' and user.ai_model='gpt-4o', the classifier
resolves _settings['active_provider'] == 'openai'.
"""When ai_provider='openai' and ai_model='gpt-4o' are passed to the classifier,
it resolves _settings['active_provider'] == 'openai'.
DOC-03: AI provider/model comes from the user's DB record, not from global
config or the retired load_settings() flat file (CONTEXT.md D-14).
DOC-03: AI provider/model comes from the user's DB record (passed through from
_run) not from global config or the retired load_settings() flat file (D-14).
"""
assert True # scaffold
from unittest.mock import AsyncMock, patch, MagicMock
from ai.base import ClassificationResult
from services.classifier import classify_document
import uuid
doc_id = str(uuid.uuid4())
user_id = uuid.uuid4()
mock_meta = {"extracted_text": "Sample document text for testing."}
mock_doc = MagicMock()
mock_doc.user_id = user_id
captured_settings = {}
def capture_get_provider(settings):
captured_settings.update(settings)
mock_provider = MagicMock()
mock_provider.classify = AsyncMock(return_value=ClassificationResult(
topics=[], suggested_new_topics=[], reasoning=""
))
return mock_provider
mock_session = AsyncMock()
mock_session.get = AsyncMock(return_value=mock_doc)
with patch("services.classifier.storage.get_metadata", AsyncMock(return_value=mock_meta)), \
patch("services.classifier.storage.load_topics_for_user", AsyncMock(return_value=[])), \
patch("services.classifier.storage.load_topics", AsyncMock(return_value=[])), \
patch("services.classifier.storage.update_document_topics", AsyncMock(return_value=None)), \
patch("services.classifier.get_provider", side_effect=capture_get_provider):
await classify_document(mock_session, doc_id, ai_provider="openai", ai_model="gpt-4o")
assert captured_settings.get("active_provider") == "openai"
assert "openai" in captured_settings.get("providers", {})
assert captured_settings["providers"]["openai"]["model"] == "gpt-4o"
@pytest.mark.xfail(strict=False, reason="implemented in plan 03-04")
@pytest.mark.asyncio
async def test_celery_task_uses_user_provider(db_session):
"""Calling _run(document_id) for a Document owned by user.ai_provider='anthropic'
calls classifier with ai_provider='anthropic'.
@@ -134,15 +169,97 @@ async def test_celery_task_uses_user_provider(db_session):
DOC-05: the Celery extract_and_classify task resolves per-user AI config via
a second DB lookup (doc.user_id → user.ai_provider/ai_model) and passes it
to the classifier (CONTEXT.md D-14).
Note: deferred imports inside _run are patched at their module paths.
"""
assert True # scaffold
from unittest.mock import AsyncMock, patch, MagicMock
import uuid
doc_id = str(uuid.uuid4())
user_id = uuid.uuid4()
mock_doc = MagicMock()
mock_doc.user_id = user_id
mock_doc.object_key = f"{user_id}/{doc_id}/file.txt"
mock_doc.content_type = "text/plain"
mock_doc.extracted_text = ""
mock_doc.status = "uploaded"
mock_user = MagicMock()
mock_user.ai_provider = "anthropic"
mock_user.ai_model = "claude-sonnet-4-6"
classify_calls = []
async def capture_classify(session, document_id, ai_provider=None, ai_model=None):
classify_calls.append({"ai_provider": ai_provider, "ai_model": ai_model})
return []
mock_session = AsyncMock()
# session.get called twice: first for Document, then for User
mock_session.get = AsyncMock(side_effect=[mock_doc, mock_user])
mock_session.commit = AsyncMock()
mock_backend = AsyncMock()
mock_backend.get_object = AsyncMock(return_value=b"file bytes")
mock_session_cm = MagicMock()
mock_session_cm.__aenter__ = AsyncMock(return_value=mock_session)
mock_session_cm.__aexit__ = AsyncMock(return_value=None)
# Patch at the source module paths since _run uses deferred imports
with patch("db.session.AsyncSessionLocal", return_value=mock_session_cm), \
patch("services.extractor.extract_text_from_bytes", return_value="document text"), \
patch("services.classifier.classify_document", capture_classify), \
patch("storage.get_storage_backend", return_value=mock_backend):
from tasks.document_tasks import _run
await _run(doc_id)
assert len(classify_calls) == 1
assert classify_calls[0]["ai_provider"] == "anthropic"
assert classify_calls[0]["ai_model"] == "claude-sonnet-4-6"
@pytest.mark.xfail(strict=False, reason="implemented in plan 03-04")
@pytest.mark.asyncio
async def test_default_provider_fallback(db_session):
"""When user.ai_provider is None, the classifier receives config.settings.default_ai_provider.
D-15: fallback chain is user.ai_provider → DEFAULT_AI_PROVIDER env var →
code default 'ollama' (CONTEXT.md D-15).
"""
assert True # scaffold
from unittest.mock import AsyncMock, patch, MagicMock
from ai.base import ClassificationResult
from services.classifier import classify_document
import uuid
doc_id = str(uuid.uuid4())
user_id = uuid.uuid4()
mock_meta = {"extracted_text": "Sample document text."}
mock_doc = MagicMock()
mock_doc.user_id = user_id
captured_settings = {}
def capture_get_provider(settings):
captured_settings.update(settings)
mock_provider = MagicMock()
mock_provider.classify = AsyncMock(return_value=ClassificationResult(
topics=[], suggested_new_topics=[], reasoning=""
))
return mock_provider
with patch("services.classifier.storage.get_metadata", AsyncMock(return_value=mock_meta)), \
patch("services.classifier.storage.load_topics_for_user", AsyncMock(return_value=[])), \
patch("services.classifier.storage.load_topics", AsyncMock(return_value=[])), \
patch("services.classifier.storage.update_document_topics", AsyncMock(return_value=None)), \
patch("services.classifier.get_provider", side_effect=capture_get_provider):
mock_session = AsyncMock()
mock_session.get = AsyncMock(return_value=mock_doc)
# Pass ai_provider=None to trigger the default fallback (D-15)
await classify_document(mock_session, doc_id, ai_provider=None, ai_model=None)
# Should fall back to app_settings.default_ai_provider = "ollama"
assert captured_settings.get("active_provider") == "ollama"
backend/tests/test_settings.py
+6 -116
View File
@@ -1,123 +1,13 @@
"""
Settings API tests — async only (Plan 05 cutover).
Settings API tests — Phase 3 D-12 retirement.
Settings remain flat-file backed in Phase 1 (D-03 deferred), so these tests
use async_client but do not require a real database session.
The /api/settings endpoint was removed in Plan 03-04. This file now contains
only the 404 assertion test (no longer marked xfail — it should pass green).
"""
from __future__ import annotations
import pytest
async def test_get_settings_defaults(async_client, tmp_path, monkeypatch):
# Point SETTINGS_FILE at a temp dir so tests don't clobber each other
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
resp = await async_client.get("/api/settings")
assert resp.status_code == 200
data = resp.json()
assert data["active_provider"] == "lmstudio"
assert "system_prompt" in data
assert "providers" in data
async def test_patch_system_prompt(async_client, tmp_path, monkeypatch):
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
new_prompt = "Custom system prompt for testing."
resp = await async_client.patch("/api/settings", json={"system_prompt": new_prompt})
assert resp.status_code == 200
resp2 = await async_client.get("/api/settings")
assert resp2.json()["system_prompt"] == new_prompt
async def test_patch_active_provider(async_client, tmp_path, monkeypatch):
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
resp = await async_client.patch("/api/settings", json={"active_provider": "ollama"})
assert resp.status_code == 200
assert resp.json()["active_provider"] == "ollama"
async def test_patch_invalid_provider(async_client, tmp_path, monkeypatch):
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
resp = await async_client.patch("/api/settings", json={"active_provider": "unknown"})
assert resp.status_code == 400
async def test_patch_provider_config(async_client, tmp_path, monkeypatch):
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
resp = await async_client.patch(
"/api/settings",
json={
"providers": {
"ollama": {"model": "mistral", "base_url": "http://host.docker.internal:11434"}
}
},
)
assert resp.status_code == 200
assert resp.json()["providers"]["ollama"]["model"] == "mistral"
async def test_masked_api_key_not_overwritten(async_client, tmp_path, monkeypatch):
"""Patching with a masked key should not overwrite the real stored key."""
import config as cfg
monkeypatch.setattr(cfg, "SETTINGS_FILE", tmp_path / "settings.json")
import services.storage as st
monkeypatch.setattr(st, "SETTINGS_FILE", tmp_path / "settings.json")
# First set a real key
await async_client.patch(
"/api/settings",
json={"providers": {"anthropic": {"api_key": "sk-ant-realkey"}}},
)
# Then patch with masked key (simulating frontend re-submitting)
await async_client.patch(
"/api/settings",
json={"providers": {"anthropic": {"api_key": "****key"}}},
)
# The stored key should still be the real one
stored = st.load_settings()
assert stored["providers"]["anthropic"]["api_key"] == "sk-ant-realkey"
async def test_get_default_prompt(async_client):
resp = await async_client.get("/api/settings/default-prompt")
assert resp.status_code == 200
assert "system_prompt" in resp.json()
assert len(resp.json()["system_prompt"]) > 0
# ---------------------------------------------------------------------------
# Wave 0 xfail stub — D-12: /api/settings endpoint removed in Plan 03-04
# ---------------------------------------------------------------------------
@pytest.mark.xfail(strict=False, reason="implemented in plan 03-04")
async def test_settings_endpoint_removed(async_client):
"""GET /api/settings returns 404 after the flat-file settings system is retired.
D-12: the /api/settings endpoint is removed entirely in Phase 3. All AI config
comes from the database (users.ai_provider / users.ai_model set by admin).
The flat-file services/storage.py load_settings()/save_settings() functions
are also deleted (CONTEXT.md D-12).
"""
assert True # scaffold
"""D-12: /api/settings endpoint is removed in Phase 3."""
resp = await async_client.get("/api/settings")
assert resp.status_code == 404