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https://github.com/bytedance/deer-flow.git
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feat(auth): authentication module with multi-tenant isolation (RFC-001)
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
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@@ -1,5 +1,6 @@
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"""Tests for LoopDetectionMiddleware."""
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import copy
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from unittest.mock import MagicMock
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from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
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@@ -19,8 +20,13 @@ def _make_runtime(thread_id="test-thread"):
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def _make_state(tool_calls=None, content=""):
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"""Build a minimal AgentState dict with an AIMessage."""
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msg = AIMessage(content=content, tool_calls=tool_calls or [])
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"""Build a minimal AgentState dict with an AIMessage.
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Deep-copies *content* when it is mutable (e.g. list) so that
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successive calls never share the same object reference.
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"""
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safe_content = copy.deepcopy(content) if isinstance(content, list) else content
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msg = AIMessage(content=safe_content, tool_calls=tool_calls or [])
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return {"messages": [msg]}
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@@ -229,3 +235,114 @@ class TestLoopDetection:
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mw._apply(_make_state(tool_calls=call), runtime)
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assert "default" in mw._history
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class TestAppendText:
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"""Unit tests for LoopDetectionMiddleware._append_text."""
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def test_none_content_returns_text(self):
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result = LoopDetectionMiddleware._append_text(None, "hello")
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assert result == "hello"
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def test_str_content_concatenates(self):
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result = LoopDetectionMiddleware._append_text("existing", "appended")
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assert result == "existing\n\nappended"
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def test_empty_str_content_concatenates(self):
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result = LoopDetectionMiddleware._append_text("", "appended")
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assert result == "\n\nappended"
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def test_list_content_appends_text_block(self):
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"""List content (e.g. Anthropic thinking mode) should get a new text block."""
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content = [
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{"type": "thinking", "text": "Let me think..."},
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{"type": "text", "text": "Here is my answer"},
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]
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result = LoopDetectionMiddleware._append_text(content, "stop msg")
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assert isinstance(result, list)
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assert len(result) == 3
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assert result[0] == content[0]
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assert result[1] == content[1]
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assert result[2] == {"type": "text", "text": "\n\nstop msg"}
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def test_empty_list_content_appends_text_block(self):
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result = LoopDetectionMiddleware._append_text([], "stop msg")
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assert isinstance(result, list)
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assert len(result) == 1
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assert result[0] == {"type": "text", "text": "\n\nstop msg"}
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def test_unexpected_type_coerced_to_str(self):
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"""Unexpected content types should be coerced to str as a fallback."""
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result = LoopDetectionMiddleware._append_text(42, "stop msg")
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assert isinstance(result, str)
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assert result == "42\n\nstop msg"
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def test_list_content_not_mutated_in_place(self):
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"""_append_text must not modify the original list."""
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original = [{"type": "text", "text": "hello"}]
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result = LoopDetectionMiddleware._append_text(original, "appended")
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assert len(original) == 1 # original unchanged
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assert len(result) == 2 # new list has the appended block
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class TestHardStopWithListContent:
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"""Regression tests: hard stop must not crash when AIMessage.content is a list."""
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def test_hard_stop_with_list_content(self):
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"""Hard stop on list content should not raise TypeError (regression)."""
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mw = LoopDetectionMiddleware(warn_threshold=2, hard_limit=4)
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runtime = _make_runtime()
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call = [_bash_call("ls")]
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# Build state with list content (e.g. Anthropic thinking mode)
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list_content = [
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{"type": "thinking", "text": "Let me think..."},
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{"type": "text", "text": "I'll run ls"},
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]
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for _ in range(3):
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mw._apply(_make_state(tool_calls=call, content=list_content), runtime)
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# Fourth call triggers hard stop — must not raise TypeError
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result = mw._apply(_make_state(tool_calls=call, content=list_content), runtime)
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assert result is not None
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msg = result["messages"][0]
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assert isinstance(msg, AIMessage)
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assert msg.tool_calls == []
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# Content should remain a list with the stop message appended
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assert isinstance(msg.content, list)
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assert len(msg.content) == 3
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assert msg.content[2]["type"] == "text"
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assert _HARD_STOP_MSG in msg.content[2]["text"]
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def test_hard_stop_with_none_content(self):
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"""Hard stop on None content should produce a plain string."""
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mw = LoopDetectionMiddleware(warn_threshold=2, hard_limit=4)
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runtime = _make_runtime()
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call = [_bash_call("ls")]
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for _ in range(3):
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mw._apply(_make_state(tool_calls=call), runtime)
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# Fourth call with default empty-string content
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result = mw._apply(_make_state(tool_calls=call), runtime)
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assert result is not None
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msg = result["messages"][0]
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assert isinstance(msg.content, str)
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assert _HARD_STOP_MSG in msg.content
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def test_hard_stop_with_str_content(self):
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"""Hard stop on str content should concatenate the stop message."""
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mw = LoopDetectionMiddleware(warn_threshold=2, hard_limit=4)
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runtime = _make_runtime()
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call = [_bash_call("ls")]
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for _ in range(3):
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mw._apply(_make_state(tool_calls=call, content="thinking..."), runtime)
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result = mw._apply(_make_state(tool_calls=call, content="thinking..."), runtime)
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assert result is not None
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msg = result["messages"][0]
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assert isinstance(msg.content, str)
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assert msg.content.startswith("thinking...")
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assert _HARD_STOP_MSG in msg.content
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