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https://github.com/usestrix/strix.git
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Jonathan SingerandClaude Fable 5
d35af02e47
Add an OAuth-based path to run Strix on a user's ChatGPT Plus/Pro subscription instead of a metered API key, modeled on OpenAI's Codex CLI. Auth: - strix/auth: Codex OAuth login (authorization-code + PKCE), a 0600 token store, refresh-on-expiry, and an AsyncOpenAI client that routes inference through the ChatGPT backend (chatgpt.com/backend-api/codex) with a per-request auth hook so long scans survive token expiry. - `strix auth login|logout|status` CLI (browser loopback on :1455 with a manual-paste fallback); STRIX_AUTH_MODE=subscription persisted to config. Inference wiring: - Subscription branch in configure_sdk_model_defaults installs the Codex client and the Responses API. - _CodexResponsesModel always streams (the backend rejects non-streamed requests) and aggregates back for the non-streaming get_response path. - store=false + encrypted reasoning for the stateless backend; models coerced to plan-available names (default gpt-5.4 — 5.5+ apply stricter content moderation that interferes with security testing). UX / reporting: - Track tokens but report $0.00 in the TUI, completion panel, and web viewer run details; record auth_mode in run.json and PostHog/Scarf. - Graceful, actionable errors for unavailable models and expired sign-in. - Restyled OAuth callback page (Strix branding + link to strix.ai). Tests: PKCE/URL/redirect parsing, token refresh + account-id, streaming aggregation, cost zeroing, CLI routing/provider aliasing. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
92 lines
3.7 KiB
Python
92 lines
3.7 KiB
Python
"""Tests for graceful handling of persistent RateLimitError in run_strix_scan."""
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from __future__ import annotations
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import logging
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import types
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from typing import Any
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import httpx
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import pytest
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from openai import RateLimitError
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import strix.tools.notes.tools as notes_tools
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import strix.tools.todo.tools as todo_tools
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from strix.core import runner
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from strix.core.agents import AgentCoordinator
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def _make_rate_limit_error() -> RateLimitError:
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request = httpx.Request("POST", "https://api.openai.com/v1/responses")
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response = httpx.Response(status_code=429, request=request)
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return RateLimitError("rate limited", response=response, body=None)
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@pytest.mark.asyncio
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async def test_persistent_rate_limit_stops_gracefully(
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monkeypatch: pytest.MonkeyPatch, tmp_path: Any, caplog: pytest.LogCaptureFixture
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) -> None:
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"""A persistent RateLimitError stops the scan (root -> 'stopped') without raising."""
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monkeypatch.setattr(runner, "run_dir_for", lambda _scan_id: tmp_path)
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monkeypatch.setattr(runner, "runtime_state_dir", lambda _run_dir: tmp_path)
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monkeypatch.setattr(runner, "setup_scan_logging", lambda _run_dir: lambda: None)
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monkeypatch.setattr(runner, "set_scan_id", lambda _scan_id: None)
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settings = types.SimpleNamespace(
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llm=types.SimpleNamespace(
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model="openai/gpt-4o",
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auth_mode="api_key",
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reasoning_effort="high",
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force_required_tool_choice=False,
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timeout=300,
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),
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runtime=types.SimpleNamespace(max_context_images=3),
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)
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monkeypatch.setattr(runner, "load_settings", lambda: settings)
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monkeypatch.setattr(runner, "configure_sdk_model_defaults", lambda _settings: None)
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monkeypatch.setattr(
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runner, "uses_chat_completions_tool_schema", lambda _model, _settings: False
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)
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monkeypatch.setattr(todo_tools, "hydrate_todos_from_disk", lambda _state_dir: None)
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monkeypatch.setattr(notes_tools, "hydrate_notes_from_disk", lambda _state_dir: None)
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async def _create_or_reuse(*_args: Any, **_kwargs: Any) -> dict[str, Any]:
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return {"client": object(), "session": object(), "caido_client": None}
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async def _cleanup(*_args: Any, **_kwargs: Any) -> None:
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return None
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monkeypatch.setattr(runner.session_manager, "create_or_reuse", _create_or_reuse) # type: ignore[attr-defined]
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monkeypatch.setattr(runner.session_manager, "cleanup", _cleanup) # type: ignore[attr-defined]
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monkeypatch.setattr(runner, "build_root_task", lambda _scan_config: "task")
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monkeypatch.setattr(runner, "build_scope_context", lambda _scan_config: "")
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monkeypatch.setattr(runner, "make_model_settings", lambda *_args, **_kwargs: object())
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monkeypatch.setattr(runner, "build_strix_agent", lambda **_kwargs: object())
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monkeypatch.setattr(runner, "make_child_factory", lambda **_kwargs: lambda **_k: object())
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monkeypatch.setattr(runner, "open_agent_session", lambda _root_id, _db: object())
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async def _raise_rate_limit(*_args: Any, **_kwargs: Any) -> None:
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raise _make_rate_limit_error()
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monkeypatch.setattr(runner, "run_agent_loop", _raise_rate_limit)
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coordinator = AgentCoordinator()
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with caplog.at_level(logging.WARNING):
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result = await runner.run_strix_scan(
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scan_config={"targets": [], "scan_mode": "deep"},
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scan_id="scan-test",
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image="img",
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coordinator=coordinator,
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)
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assert result is None
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root_ids = [aid for aid, parent in coordinator.parent_of.items() if parent is None]
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assert len(root_ids) == 1
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assert coordinator.statuses[root_ids[0]] == "stopped"
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# the resume hint must carry the real scan id, not a literal placeholder
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assert "strix --resume scan-test" in caplog.text
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assert "<run_name>" not in caplog.text
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