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
This commit is contained in:
greatmengqi
2026-04-08 00:31:43 +08:00
parent 636053fb6d
commit 27b66d6753
214 changed files with 18830 additions and 1065 deletions
@@ -10,10 +10,52 @@ from langchain_core.messages import HumanMessage
from langgraph.runtime import Runtime
from deerflow.config.paths import Paths, get_paths
from deerflow.utils.file_conversion import extract_outline
logger = logging.getLogger(__name__)
_OUTLINE_PREVIEW_LINES = 5
def _extract_outline_for_file(file_path: Path) -> tuple[list[dict], list[str]]:
"""Return the document outline and fallback preview for *file_path*.
Looks for a sibling ``<stem>.md`` file produced by the upload conversion
pipeline.
Returns:
(outline, preview) where:
- outline: list of ``{title, line}`` dicts (plus optional sentinel).
Empty when no headings are found or no .md exists.
- preview: first few non-empty lines of the .md, used as a content
anchor when outline is empty so the agent has some context.
Empty when outline is non-empty (no fallback needed).
"""
md_path = file_path.with_suffix(".md")
if not md_path.is_file():
return [], []
outline = extract_outline(md_path)
if outline:
logger.debug("Extracted %d outline entries from %s", len(outline), file_path.name)
return outline, []
# outline is empty — read the first few non-empty lines as a content preview
preview: list[str] = []
try:
with md_path.open(encoding="utf-8") as f:
for line in f:
stripped = line.strip()
if stripped:
preview.append(stripped)
if len(preview) >= _OUTLINE_PREVIEW_LINES:
break
except Exception:
logger.debug("Failed to read preview lines from %s", md_path, exc_info=True)
return [], preview
class UploadsMiddlewareState(AgentState):
"""State schema for uploads middleware."""
@@ -39,12 +81,38 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
super().__init__()
self._paths = Paths(base_dir) if base_dir else get_paths()
def _format_file_entry(self, file: dict, lines: list[str]) -> None:
"""Append a single file entry (name, size, path, optional outline) to lines."""
size_kb = file["size"] / 1024
size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
lines.append(f"- {file['filename']} ({size_str})")
lines.append(f" Path: {file['path']}")
outline = file.get("outline") or []
if outline:
truncated = outline[-1].get("truncated", False)
visible = [e for e in outline if not e.get("truncated")]
lines.append(" Document outline (use `read_file` with line ranges to read sections):")
for entry in visible:
lines.append(f" L{entry['line']}: {entry['title']}")
if truncated:
lines.append(f" ... (showing first {len(visible)} headings; use `read_file` to explore further)")
else:
preview = file.get("outline_preview") or []
if preview:
lines.append(" No structural headings detected. Document begins with:")
for text in preview:
lines.append(f" > {text}")
lines.append(" Use `grep` to search for keywords (e.g. `grep(pattern='keyword', path='/mnt/user-data/uploads/')`).")
lines.append("")
def _create_files_message(self, new_files: list[dict], historical_files: list[dict]) -> str:
"""Create a formatted message listing uploaded files.
Args:
new_files: Files uploaded in the current message.
historical_files: Files uploaded in previous messages.
Each file dict may contain an optional ``outline`` key — a list of
``{title, line}`` dicts extracted from the converted Markdown file.
Returns:
Formatted string inside <uploaded_files> tags.
@@ -55,25 +123,24 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
lines.append("")
if new_files:
for file in new_files:
size_kb = file["size"] / 1024
size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
lines.append(f"- {file['filename']} ({size_str})")
lines.append(f" Path: {file['path']}")
lines.append("")
self._format_file_entry(file, lines)
else:
lines.append("(empty)")
lines.append("")
if historical_files:
lines.append("The following files were uploaded in previous messages and are still available:")
lines.append("")
for file in historical_files:
size_kb = file["size"] / 1024
size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
lines.append(f"- {file['filename']} ({size_str})")
lines.append(f" Path: {file['path']}")
lines.append("")
self._format_file_entry(file, lines)
lines.append("You can read these files using the `read_file` tool with the paths shown above.")
lines.append("To work with these files:")
lines.append("- Read from the file first — use the outline line numbers and `read_file` to locate relevant sections.")
lines.append("- Use `grep` to search for keywords when you are not sure which section to look at")
lines.append(" (e.g. `grep(pattern='revenue', path='/mnt/user-data/uploads/')`).")
lines.append("- Use `glob` to find files by name pattern")
lines.append(" (e.g. `glob(pattern='**/*.md', path='/mnt/user-data/uploads/')`).")
lines.append("- Only fall back to web search if the file content is clearly insufficient to answer the question.")
lines.append("</uploaded_files>")
return "\n".join(lines)
@@ -147,6 +214,13 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
# Resolve uploads directory for existence checks
thread_id = (runtime.context or {}).get("thread_id")
if thread_id is None:
try:
from langgraph.config import get_config
thread_id = get_config().get("configurable", {}).get("thread_id")
except RuntimeError:
pass # get_config() raises outside a runnable context (e.g. unit tests)
uploads_dir = self._paths.sandbox_uploads_dir(thread_id) if thread_id else None
# Get newly uploaded files from the current message's additional_kwargs.files
@@ -159,15 +233,26 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
for file_path in sorted(uploads_dir.iterdir()):
if file_path.is_file() and file_path.name not in new_filenames:
stat = file_path.stat()
outline, preview = _extract_outline_for_file(file_path)
historical_files.append(
{
"filename": file_path.name,
"size": stat.st_size,
"path": f"/mnt/user-data/uploads/{file_path.name}",
"extension": file_path.suffix,
"outline": outline,
"outline_preview": preview,
}
)
# Attach outlines to new files as well
if uploads_dir:
for file in new_files:
phys_path = uploads_dir / file["filename"]
outline, preview = _extract_outline_for_file(phys_path)
file["outline"] = outline
file["outline_preview"] = preview
if not new_files and not historical_files:
return None