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8616033605
Addresses both #1499 (onboarding wizard never probes the configured base URL) and #1500 (cross-tool env-var name divergence between webui and agent CLI). Surfaced together because they're both LM-Studio onboarding bugs that pile on top of each other — fixing only one leaves the broken UX. #1499 — Onboarding wizard probes <base_url>/models before persisting Pre-fix, `apply_onboarding_setup` accepted whatever `base_url` the user typed without ever fetching `<base_url>/models`. @chwps's log timeline in #1420 showed the wizard finishing in 239ms with zero outbound HTTP — onboarding silently persisted unreachable URLs and left users with empty model dropdowns they had to populate by hand-editing config.yaml. Backend: * New `probe_provider_endpoint(provider, base_url, api_key, timeout=5.0)` in `api/onboarding.py`. Stdlib-only (urllib + socket — no httpx dep). Returns `{ok, models}` on success; `{ok: False, error: <code>, detail}` on failure with stable error codes the frontend can switch on: invalid_url, dns, connect_refused, timeout, http_4xx, http_5xx, parse, unreachable. 256 KB response cap and 5s timeout keep a hostile or mis- pointed endpoint from blocking the wizard. * New `POST /api/onboarding/probe` route — thin JSON wrapper around the function above. Same local-network gate as `/api/onboarding/setup` because the body carries an `api_key` the user typed. * The probe response is NEVER persisted. Only the user's typed selection ends up in config.yaml; the probed model list just populates the wizard's dropdown. * SSRF: deliberately does NOT block private-IP ranges. The wizard is gated behind WebUI auth and the legitimate target IS a local LM Studio / Ollama / vLLM server. A "block private IPs" SSRF defense would make the feature useless for its primary use case. Frontend: * `static/onboarding.js`: - New `ONBOARDING.probe` state ({status, error, detail, models, probedKey}). - `_runOnboardingProbe()` — POSTs to /api/onboarding/probe, idempotent & cached on (provider, baseUrl, apiKey). - Debounced (400ms) on `oninput` of the base URL field. - Explicit "Test connection" button. - `nextOnboardingStep` blocks Continue at the setup step for any provider with `requires_base_url=True` until the probe succeeds. Same localized error renders inline. * `static/i18n.js`: 13 new keys × 9 locales (canonical English in `en`, English fallback with `// TODO: translate` markers in the other 8 — same convention as v0.50.271 #1488 voice-buttons). * `static/style.css`: probe banner + Test button styling (red-tinted error variant, green-tinted success variant, neutral probing state). Verified via manual repro on port 8789: * connect_refused → red banner, helpful "from Docker, try the host IP" hint, blocks Continue. * DNS failure → red banner, "could not resolve host '...'", blocks Continue. * Success against a mock /v1/models server → green banner, model dropdown populates from the probed list, Continue advances normally. #1500 — webui env var aligned with agent CLI (LM_API_KEY) The webui has long used `LMSTUDIO_API_KEY` for LM Studio's API key in both onboarding and Settings detection. The agent CLI runtime (hermes_cli/auth.py:177-183) reads `LM_API_KEY`. So a user who configured auth on their LM Studio instance got Settings → Providers reporting has_key=True (because webui saw its own LMSTUDIO_API_KEY) but the agent runtime ignored the key and fell back to LMSTUDIO_NOAUTH_PLACEHOLDER → 401 against the auth-enabled LM Studio server. Masked in practice for the no-auth majority. Picked Option B from the issue (defer to the agent — single source of truth) but mitigated the migration cliff by reading the legacy name as a fallback: * `api/onboarding.py:_SUPPORTED_PROVIDER_SETUPS["lmstudio"]`: - `env_var: "LM_API_KEY"` (canonical, what onboarding writes going forward). - `env_var_aliases: ["LMSTUDIO_API_KEY"]` (read-only fallback for pre-#1500 users so detection keeps working without forcing an .env rewrite). * `api/onboarding.py:_provider_api_key_present` reads aliases too. * `api/providers.py:_PROVIDER_ENV_VAR["lmstudio"] = "LM_API_KEY"`. * `api/providers.py:_PROVIDER_ENV_VAR_ALIASES["lmstudio"] = ("LMSTUDIO_API_KEY",)` — new dict, used by `_provider_has_key` and `get_providers`'s key_source resolution. Drops in cleanly when other providers later rename their env vars too. Verified: ``` before fix: webui writes LMSTUDIO_API_KEY → agent ignores it → 401 on chat after fix: webui writes LM_API_KEY → agent picks it up → chat works pre-#1500 .env with LMSTUDIO_API_KEY → still has_key=True in Settings → key_source='env_file' ``` Tests * `tests/test_issue1499_onboarding_probe.py` — 17 tests: 3 invalid_url variants, dns, connect_refused, success (OpenAI shape), success (bare-list shape), http_4xx, http_5xx, parse non-JSON, parse wrong-shape, api_key authorization header passthrough, "probe must not write to config.yaml or .env", PROBE_ERROR_CODES contract pin, 3 end-to-end route-level smoke tests against the live server fixture. * `tests/test_issue1500_lmstudio_env_var_alignment.py` — 5 tests: onboarding declares LM_API_KEY canonical with LMSTUDIO_API_KEY alias, onboarding writes ONLY the canonical name, legacy env var still detected post-migration, canonical takes precedence when both are set, _provider_api_key_present reads aliases. * `tests/test_issue1420_lmstudio_provider_env_var.py` — updated: the original 5-test #1420 suite now pins LM_API_KEY as canonical and LMSTUDIO_API_KEY as alias. Full suite: 3879 → 3901 passing (+22), 0 failures. Out of scope (explicitly NOT addressed here) The third LM Studio onboarding sub-bug from #1420's thread — that `apply_onboarding_setup` requires a non-empty api_key for lmstudio even though most LM Studio installs run keyless — remains. The agent's `LMSTUDIO_NOAUTH_PLACEHOLDER` substitution kicks in at runtime, but the onboarding wizard rejects the empty-key case at submit. Fixing this requires a UX decision (auto-write a sentinel? loosen the required-key check for self-hosted providers?) and is left as a separate follow-up. Closes #1499 Closes #1500 Co-authored-by: chwps <106549456+chwps@users.noreply.github.com> Co-authored-by: AdoneyGalvan <25235323+AdoneyGalvan@users.noreply.github.com>
200 lines
8.9 KiB
Python
200 lines
8.9 KiB
Python
"""Regression: webui aligns LM Studio env var with the agent CLI (#1500).
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Pre-#1500 the WebUI used `LMSTUDIO_API_KEY` everywhere — onboarding wrote it,
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Settings detection read it. The agent CLI runtime (hermes_cli/auth.py:182,
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api_key_env_vars=("LM_API_KEY",)) reads `LM_API_KEY`. So a user who configured
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auth on their LM Studio instance and entered the key in the WebUI got:
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- Settings → Providers reporting has_key=True (because WebUI saw its own
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LMSTUDIO_API_KEY)
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- Agent runtime ignoring the key (because it reads LM_API_KEY)
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- Chat falling back to LMSTUDIO_NOAUTH_PLACEHOLDER → 401 from the
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auth-enabled LM Studio server
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Masked in practice for the no-auth majority. Real bug for anyone with
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auth enabled.
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This file pins the post-#1500 contract:
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1. Onboarding writes the canonical `LM_API_KEY` (NOT `LMSTUDIO_API_KEY`).
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2. Settings detection reads the canonical first.
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3. Settings detection ALSO reads the legacy `LMSTUDIO_API_KEY` as a
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read-only alias, so users with the old name in their .env don't see
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Settings flip to "no key" on upgrade.
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"""
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from __future__ import annotations
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import sys
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import types
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from pathlib import Path
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import api.config as config
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import api.profiles as profiles
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def _install_fake_hermes_cli(monkeypatch):
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"""Stub hermes_cli modules so tests are deterministic and offline."""
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fake_pkg = types.ModuleType("hermes_cli")
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fake_pkg.__path__ = []
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fake_models = types.ModuleType("hermes_cli.models")
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fake_models.list_available_providers = lambda: []
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fake_models.provider_model_ids = lambda pid: []
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fake_auth = types.ModuleType("hermes_cli.auth")
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fake_auth.get_auth_status = lambda _pid: {}
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monkeypatch.setitem(sys.modules, "hermes_cli", fake_pkg)
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monkeypatch.setitem(sys.modules, "hermes_cli.models", fake_models)
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monkeypatch.setitem(sys.modules, "hermes_cli.auth", fake_auth)
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monkeypatch.delitem(sys.modules, "agent.credential_pool", raising=False)
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monkeypatch.delitem(sys.modules, "agent", raising=False)
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try:
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from api.config import invalidate_models_cache
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invalidate_models_cache()
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except Exception:
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pass
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def _swap_in_test_config(extra_cfg):
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old_cfg = dict(config.cfg)
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old_mtime = config._cfg_mtime
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config.cfg.clear()
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config.cfg["model"] = {}
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config.cfg.update(extra_cfg)
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try:
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config._cfg_mtime = config.Path(config._get_config_path()).stat().st_mtime
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except Exception:
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config._cfg_mtime = 0.0
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def _restore():
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config.cfg.clear()
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config.cfg.update(old_cfg)
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config._cfg_mtime = old_mtime
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return _restore
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class TestIssue1500EnvVarAlignment:
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def test_onboarding_supported_provider_setup_uses_lm_api_key(self):
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"""The wizard's lmstudio entry must declare the canonical env var name."""
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from api.onboarding import _SUPPORTED_PROVIDER_SETUPS
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assert "lmstudio" in _SUPPORTED_PROVIDER_SETUPS
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meta = _SUPPORTED_PROVIDER_SETUPS["lmstudio"]
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assert meta["env_var"] == "LM_API_KEY", (
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f"Onboarding's lmstudio.env_var must be the canonical 'LM_API_KEY' "
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f"(matching hermes_cli/auth.py:182 api_key_env_vars=('LM_API_KEY',)). "
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f"Got {meta['env_var']!r}."
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)
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# Legacy alias preserved for read-only fallback.
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aliases = list(meta.get("env_var_aliases") or [])
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assert "LMSTUDIO_API_KEY" in aliases, (
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f"Onboarding's lmstudio.env_var_aliases must include the legacy "
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f"'LMSTUDIO_API_KEY' name so existing users' detection keeps "
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f"working. Got aliases={aliases!r}."
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)
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def test_onboarding_writes_canonical_name_only(self, monkeypatch, tmp_path):
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"""`apply_onboarding_setup` must write LM_API_KEY (not LMSTUDIO_API_KEY)."""
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_install_fake_hermes_cli(monkeypatch)
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# Redirect every write target to the tmp_path so we don't touch the real
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# ~/.hermes — pattern from webui-onboarding-provider-readiness skill.
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from api import onboarding as ob
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monkeypatch.setattr(ob, "_get_active_hermes_home", lambda: tmp_path)
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cfg_path = tmp_path / "config.yaml"
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monkeypatch.setattr(ob, "_get_config_path", lambda: cfg_path)
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monkeypatch.setattr(profiles, "get_active_hermes_home", lambda: tmp_path)
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monkeypatch.delenv("HERMES_WEBUI_SKIP_ONBOARDING", raising=False)
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monkeypatch.delenv("LM_API_KEY", raising=False)
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monkeypatch.delenv("LMSTUDIO_API_KEY", raising=False)
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ob.apply_onboarding_setup({
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"provider": "lmstudio",
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"model": "qwen3-27b",
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"base_url": "http://example.local:1234/v1",
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"api_key": "fresh-canon",
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})
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env_path = tmp_path / ".env"
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assert env_path.exists(), "onboarding must write .env"
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env_text = env_path.read_text(encoding="utf-8")
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assert "LM_API_KEY=" in env_text, (
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f"Onboarding must write the canonical LM_API_KEY name. .env now reads:\n{env_text}"
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)
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assert "LMSTUDIO_API_KEY=" not in env_text, (
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f"Onboarding must NOT write the legacy LMSTUDIO_API_KEY name "
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f"(should only be canonical going forward). .env now reads:\n{env_text}"
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)
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def test_legacy_lmstudio_env_var_still_detected(self, monkeypatch, tmp_path):
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"""Pre-#1500 users with LMSTUDIO_API_KEY still see has_key=True after upgrade."""
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_install_fake_hermes_cli(monkeypatch)
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monkeypatch.setattr(profiles, "get_active_hermes_home", lambda: tmp_path)
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monkeypatch.delenv("LM_API_KEY", raising=False)
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monkeypatch.setenv("LMSTUDIO_API_KEY", "lm-studio-legacy")
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restore = _swap_in_test_config({"model": {"provider": "lmstudio"}})
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try:
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from api.providers import get_providers
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result = get_providers()
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by_id = {p["id"]: p for p in result["providers"]}
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assert by_id["lmstudio"]["has_key"] is True, (
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"Pre-#1500 users with the legacy LMSTUDIO_API_KEY env var must "
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"continue to see has_key=True after upgrade — that's the whole "
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"point of the alias fallback in _PROVIDER_ENV_VAR_ALIASES."
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)
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assert by_id["lmstudio"]["key_source"] in {"env_file", "env_var"}, (
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f"Legacy alias detection should report env_file / env_var as "
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f"key_source (the key really IS in .env), got "
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f"{by_id['lmstudio']['key_source']!r} — this is the post-#1500 "
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f"key_source-via-alias path."
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)
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finally:
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restore()
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def test_canonical_takes_precedence_over_legacy(self, monkeypatch, tmp_path):
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"""When both env vars are set, canonical wins (rare migration edge)."""
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_install_fake_hermes_cli(monkeypatch)
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monkeypatch.setattr(profiles, "get_active_hermes_home", lambda: tmp_path)
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monkeypatch.setenv("LM_API_KEY", "canonical-wins")
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monkeypatch.setenv("LMSTUDIO_API_KEY", "legacy-loses")
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restore = _swap_in_test_config({"model": {"provider": "lmstudio"}})
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try:
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from api.providers import get_providers, _provider_has_key
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assert _provider_has_key("lmstudio") is True
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# Both lead to has_key=True; the contract is that canonical is
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# checked first (so it's definitely returning True and not just
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# falling through to the alias). We can't easily assert ordering
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# from this layer, but the existence of both detection paths is
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# captured by test_legacy_lmstudio_env_var_still_detected and
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# test_lmstudio_has_key_true_when_env_var_set in the #1420 file.
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result = get_providers()
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by_id = {p["id"]: p for p in result["providers"]}
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assert by_id["lmstudio"]["has_key"] is True
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assert by_id["lmstudio"]["configurable"] is True
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finally:
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restore()
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def test_provider_api_key_present_reads_aliases(self, monkeypatch, tmp_path):
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"""`_provider_api_key_present` (onboarding-side) reads aliases too.
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The onboarding readiness pipeline (_status_from_runtime → chat_ready)
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relies on this function. If aliases aren't honored here, an upgrading
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user gets a re-firing wizard even though their LM Studio is configured.
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"""
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from api.onboarding import _provider_api_key_present
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cfg = {"model": {"provider": "lmstudio"}}
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# Only the legacy name set in .env values — onboarding must still see it.
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env_values = {"LMSTUDIO_API_KEY": "x"}
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assert _provider_api_key_present("lmstudio", cfg, env_values) is True
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# Only the canonical name set — also detected.
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env_values = {"LM_API_KEY": "x"}
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assert _provider_api_key_present("lmstudio", cfg, env_values) is True
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# Neither set — not detected.
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env_values = {"OPENAI_API_KEY": "x"}
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assert _provider_api_key_present("lmstudio", cfg, env_values) is False
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