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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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@@ -29,6 +29,22 @@ _CORRECTION_PATTERNS = (
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re.compile(r"改用"),
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)
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_REINFORCEMENT_PATTERNS = (
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re.compile(r"\byes[,.]?\s+(?:exactly|perfect|that(?:'s| is) (?:right|correct|it))\b", re.IGNORECASE),
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re.compile(r"\bperfect(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"\bexactly\s+(?:right|correct)\b", re.IGNORECASE),
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re.compile(r"\bthat(?:'s| is)\s+(?:exactly\s+)?(?:right|correct|what i (?:wanted|needed|meant))\b", re.IGNORECASE),
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re.compile(r"\bkeep\s+(?:doing\s+)?that\b", re.IGNORECASE),
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re.compile(r"\bjust\s+(?:like\s+)?(?:that|this)\b", re.IGNORECASE),
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re.compile(r"\bthis is (?:great|helpful)\b(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"\bthis is what i wanted\b(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"对[,,]?\s*就是这样(?:[。!?!?.]|$)"),
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re.compile(r"完全正确(?:[。!?!?.]|$)"),
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re.compile(r"(?:对[,,]?\s*)?就是这个意思(?:[。!?!?.]|$)"),
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re.compile(r"正是我想要的(?:[。!?!?.]|$)"),
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re.compile(r"继续保持(?:[。!?!?.]|$)"),
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)
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class MemoryMiddlewareState(AgentState):
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"""Compatible with the `ThreadState` schema."""
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@@ -132,6 +148,29 @@ def detect_correction(messages: list[Any]) -> bool:
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return False
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def detect_reinforcement(messages: list[Any]) -> bool:
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"""Detect explicit positive reinforcement signals in recent conversation turns.
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Complements detect_correction() by identifying when the user confirms the
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agent's approach was correct. This allows the memory system to record what
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worked well, not just what went wrong.
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The queue keeps only one pending context per thread, so callers pass the
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latest filtered message list. Checking only recent user turns keeps signal
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detection conservative while avoiding stale signals from long histories.
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"""
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recent_user_msgs = [msg for msg in messages[-6:] if getattr(msg, "type", None) == "human"]
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for msg in recent_user_msgs:
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content = _extract_message_text(msg).strip()
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if not content:
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continue
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if any(pattern.search(content) for pattern in _REINFORCEMENT_PATTERNS):
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return True
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return False
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class MemoryMiddleware(AgentMiddleware[MemoryMiddlewareState]):
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"""Middleware that queues conversation for memory update after agent execution.
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@@ -196,12 +235,14 @@ class MemoryMiddleware(AgentMiddleware[MemoryMiddlewareState]):
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# Queue the filtered conversation for memory update
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correction_detected = detect_correction(filtered_messages)
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reinforcement_detected = not correction_detected and detect_reinforcement(filtered_messages)
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queue = get_memory_queue()
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queue.add(
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thread_id=thread_id,
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messages=filtered_messages,
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agent_name=self._agent_name,
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correction_detected=correction_detected,
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reinforcement_detected=reinforcement_detected,
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)
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return None
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