mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-05-21 15:36:48 +00:00
greatmengqi
27b66d6753
Introduce an always-on auth layer with auto-created admin on first boot, multi-tenant isolation for threads/stores, and a full setup/login flow. Backend - JWT access tokens with `ver` field for stale-token rejection; bump on password/email change - Password hashing, HttpOnly+Secure cookies (Secure derived from request scheme at runtime) - CSRF middleware covering both REST and LangGraph routes - IP-based login rate limiting (5 attempts / 5-min lockout) with bounded dict growth and X-Forwarded-For bypass fix - Multi-worker-safe admin auto-creation (single DB write, WAL once) - needs_setup + token_version on User model; SQLite schema migration - Thread/store isolation by owner; orphan thread migration on first admin registration - thread_id validated as UUID to prevent log injection - CLI tool to reset admin password - Decorator-based authz module extracted from auth core Frontend - Login and setup pages with SSR guard for needs_setup flow - Account settings page (change password / email) - AuthProvider + route guards; skips redirect when no users registered - i18n (en-US / zh-CN) for auth surfaces - Typed auth API client; parseAuthError unwraps FastAPI detail envelope Infra & tooling - Unified `serve.sh` with gateway mode + auto dep install - Public PyPI uv.toml pin for CI compatibility - Regenerated uv.lock with public index Tests - HTTP vs HTTPS cookie security tests - Auth middleware, rate limiter, CSRF, setup flow coverage
103 lines
3.6 KiB
Python
103 lines
3.6 KiB
Python
import asyncio
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from unittest.mock import AsyncMock, MagicMock
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from app.gateway.routers import suggestions
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def test_strip_markdown_code_fence_removes_wrapping():
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text = '```json\n["a"]\n```'
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assert suggestions._strip_markdown_code_fence(text) == '["a"]'
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def test_strip_markdown_code_fence_no_fence_keeps_content():
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text = ' ["a"] '
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assert suggestions._strip_markdown_code_fence(text) == '["a"]'
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def test_parse_json_string_list_filters_invalid_items():
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text = '```json\n["a", " ", 1, "b"]\n```'
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assert suggestions._parse_json_string_list(text) == ["a", "b"]
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def test_parse_json_string_list_rejects_non_list():
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text = '{"a": 1}'
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assert suggestions._parse_json_string_list(text) is None
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def test_format_conversation_formats_roles():
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messages = [
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suggestions.SuggestionMessage(role="User", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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suggestions.SuggestionMessage(role="system", content="note"),
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]
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assert suggestions._format_conversation(messages) == "User: Hi\nAssistant: Hello\nsystem: note"
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def test_generate_suggestions_parses_and_limits(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=3,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content='```json\n["Q1", "Q2", "Q3", "Q4"]\n```'))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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result = asyncio.run(suggestions.generate_suggestions("t1", req))
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assert result.suggestions == ["Q1", "Q2", "Q3"]
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def test_generate_suggestions_parses_list_block_content(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content=[{"type": "text", "text": '```json\n["Q1", "Q2"]\n```'}]))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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result = asyncio.run(suggestions.generate_suggestions("t1", req))
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assert result.suggestions == ["Q1", "Q2"]
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def test_generate_suggestions_parses_output_text_block_content(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content=[{"type": "output_text", "text": '```json\n["Q1", "Q2"]\n```'}]))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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result = asyncio.run(suggestions.generate_suggestions("t1", req))
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assert result.suggestions == ["Q1", "Q2"]
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def test_generate_suggestions_returns_empty_on_model_error(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[suggestions.SuggestionMessage(role="user", content="Hi")],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(side_effect=RuntimeError("boom"))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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result = asyncio.run(suggestions.generate_suggestions("t1", req))
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assert result.suggestions == []
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