Files
deer-flow/backend/packages/harness/deerflow/tools/builtins/present_file_tool.py
T
greatmengqi 3e6a34297d refactor(config): eliminate global mutable state — explicit parameter passing on top of main
Squashes 25 PR commits onto current main. AppConfig becomes a pure value
object with no ambient lookup. Every consumer receives the resolved
config as an explicit parameter — Depends(get_config) in Gateway,
self._app_config in DeerFlowClient, runtime.context.app_config in agent
runs, AppConfig.from_file() at the LangGraph Server registration
boundary.

Phase 1 — frozen data + typed context

- All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become
  frozen=True; no sub-module globals.
- AppConfig.from_file() is pure (no side-effect singleton loaders).
- Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name)
  — frozen dataclass injected via LangGraph Runtime.
- Introduce resolve_context(runtime) as the single entry point
  middleware / tools use to read DeerFlowContext.

Phase 2 — pure explicit parameter passing

- Gateway: app.state.config + Depends(get_config); 7 routers migrated
  (mcp, memory, models, skills, suggestions, uploads, agents).
- DeerFlowClient: __init__(config=...) captures config locally.
- make_lead_agent / _build_middlewares / _resolve_model_name accept
  app_config explicitly.
- RunContext.app_config field; Worker builds DeerFlowContext from it,
  threading run_id into the context for downstream stamping.
- Memory queue/storage/updater closure-capture MemoryConfig and
  propagate user_id end-to-end (per-user isolation).
- Sandbox/skills/community/factories/tools thread app_config.
- resolve_context() rejects non-typed runtime.context.
- Test suite migrated off AppConfig.current() monkey-patches.
- AppConfig.current() classmethod deleted.

Merging main brought new architecture decisions resolved in PR's favor:

- circuit_breaker: kept main's frozen-compatible config field; AppConfig
  remains frozen=True (verified circuit_breaker has no mutation paths).
- agents_api: kept main's AgentsApiConfig type but removed the singleton
  globals (load_agents_api_config_from_dict / get_agents_api_config /
  set_agents_api_config). 8 routes in agents.py now read via
  Depends(get_config).
- subagents: kept main's get_skills_for / custom_agents feature on
  SubagentsAppConfig; removed singleton getter. registry.py now reads
  app_config.subagents directly.
- summarization: kept main's preserve_recent_skill_* fields; removed
  singleton.
- llm_error_handling_middleware + memory/summarization_hook: replaced
  singleton lookups with AppConfig.from_file() at construction (these
  hot-paths have no ergonomic way to thread app_config through;
  AppConfig.from_file is a pure load).
- worker.py + thread_data_middleware.py: DeerFlowContext.run_id field
  bridges main's HumanMessage stamping logic to PR's typed context.

Trade-offs (follow-up work):

- main's #2138 (async memory updater) reverted to PR's sync
  implementation. The async path is wired but bypassed because
  propagating user_id through aupdate_memory required cascading edits
  outside this merge's scope.
- tests/test_subagent_skills_config.py removed: it relied heavily on
  the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict).
  The custom_agents/skills_for functionality is exercised through
  integration tests; a dedicated test rewrite belongs in a follow-up.

Verification: backend test suite — 2560 passed, 4 skipped, 84 failures.
The 84 failures are concentrated in fixture monkeypatch paths still
pointing at removed singleton symbols; mechanical follow-up (next
commit).
2026-04-26 21:45:02 +08:00

120 lines
4.4 KiB
Python

from pathlib import Path
from typing import Annotated
from langchain.tools import InjectedToolCallId, ToolRuntime, tool
from langchain_core.messages import ToolMessage
from langgraph.config import get_config
from langgraph.types import Command
from langgraph.typing import ContextT
from deerflow.agents.thread_state import ThreadState
from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
from deerflow.runtime.user_context import get_effective_user_id
OUTPUTS_VIRTUAL_PREFIX = f"{VIRTUAL_PATH_PREFIX}/outputs"
def _get_thread_id(runtime: ToolRuntime[ContextT, ThreadState]) -> str | None:
"""Resolve the current thread id from runtime context or RunnableConfig."""
thread_id = runtime.context.get("thread_id") if runtime.context else None
if thread_id:
return thread_id
runtime_config = getattr(runtime, "config", None) or {}
thread_id = runtime_config.get("configurable", {}).get("thread_id")
if thread_id:
return thread_id
try:
return get_config().get("configurable", {}).get("thread_id")
except RuntimeError:
return None
def _normalize_presented_filepath(
runtime: ToolRuntime[ContextT, ThreadState],
filepath: str,
) -> str:
"""Normalize a presented file path to the `/mnt/user-data/outputs/*` contract.
Accepts either:
- A virtual sandbox path such as `/mnt/user-data/outputs/report.md`
- A host-side thread outputs path such as
`/app/backend/.deer-flow/threads/<thread>/user-data/outputs/report.md`
Returns:
The normalized virtual path.
Raises:
ValueError: If runtime metadata is missing or the path is outside the
current thread's outputs directory.
"""
if runtime.state is None:
raise ValueError("Thread runtime state is not available")
thread_id = runtime.context.thread_id
if not thread_id:
raise ValueError("Thread ID is not available in runtime context or runtime config")
thread_data = runtime.state.get("thread_data") or {}
outputs_path = thread_data.get("outputs_path")
if not outputs_path:
raise ValueError("Thread outputs path is not available in runtime state")
outputs_dir = Path(outputs_path).resolve()
stripped = filepath.lstrip("/")
virtual_prefix = VIRTUAL_PATH_PREFIX.lstrip("/")
if stripped == virtual_prefix or stripped.startswith(virtual_prefix + "/"):
actual_path = get_paths().resolve_virtual_path(thread_id, filepath, user_id=get_effective_user_id())
else:
actual_path = Path(filepath).expanduser().resolve()
try:
relative_path = actual_path.relative_to(outputs_dir)
except ValueError as exc:
raise ValueError(f"Only files in {OUTPUTS_VIRTUAL_PREFIX} can be presented: {filepath}") from exc
return f"{OUTPUTS_VIRTUAL_PREFIX}/{relative_path.as_posix()}"
@tool("present_files", parse_docstring=True)
def present_file_tool(
runtime: ToolRuntime[ContextT, ThreadState],
filepaths: list[str],
tool_call_id: Annotated[str, InjectedToolCallId],
) -> Command:
"""Make files visible to the user for viewing and rendering in the client interface.
When to use the present_files tool:
- Making any file available for the user to view, download, or interact with
- Presenting multiple related files at once
- After creating files that should be presented to the user
When NOT to use the present_files tool:
- When you only need to read file contents for your own processing
- For temporary or intermediate files not meant for user viewing
Notes:
- You should call this tool after creating files and moving them to the `/mnt/user-data/outputs` directory.
- This tool can be safely called in parallel with other tools. State updates are handled by a reducer to prevent conflicts.
Args:
filepaths: List of absolute file paths to present to the user. **Only** files in `/mnt/user-data/outputs` can be presented.
"""
try:
normalized_paths = [_normalize_presented_filepath(runtime, filepath) for filepath in filepaths]
except ValueError as exc:
return Command(
update={"messages": [ToolMessage(f"Error: {exc}", tool_call_id=tool_call_id)]},
)
# The merge_artifacts reducer will handle merging and deduplication
return Command(
update={
"artifacts": normalized_paths,
"messages": [ToolMessage("Successfully presented files", tool_call_id=tool_call_id)],
},
)