deer-flow/backend/docs/TUI.md
DanielWalnut 25ea6970a6
feat(runtime): implement goal continuations (#3858)
* implement goal continuations

* fix(goal): address review findings for goal continuations

- goal: key the no-progress breaker on a signature of the latest visible
  assistant evidence instead of the evaluator's volatile free-text, so it
  actually fires on stalled turns; thread the signature through every
  worker persist / no-progress call site
- goal: align _stand_down_reason default caps with should_continue_goal
  (8 / 2) so the two gate functions agree on goals missing the fields
- runtime: offload the synchronous checkpointer fallback via
  asyncio.to_thread (goal.py + worker.py) to keep blocking IO off the loop
- frontend: i18n the GoalStatus "Goal" label (goalLabel in en/zh/types)
- frontend: extract pure composer helpers into input-box-helpers.ts with
  unit tests (parseGoalCommand, readGoalResponseError, skill suggestions)
- tests: cover the evidence-based no-progress and default-cap behavior
- docs: align backend/AGENTS.md goal paragraph with actual behavior
- e2e: prettier-format chat.spec.ts (fixes the lint-frontend CI failure)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

* feat(frontend): hide goal continuation counter until the agent continues

The goal status bar rendered a raw "0/8" before any auto-continuation, which
read as a mysterious score. Now the counter is hidden until
continuation_count > 0, then shows "Continuing N/M" with a tooltip explaining
the auto-continuation cap.

- Extract getGoalContinuationDisplay into a pure helper (hides at 0) + unit tests
- Add goalContinuing / goalContinuationTooltip i18n keys (en/zh/types)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

* fix(goal): address review findings for goal continuations

Frontend correctness
- Fix the optimistic /goal result permanently shadowing server goal state:
  the streamed continuation counter never surfaced for a goal set in-session.
  Extract a shared useActiveGoal hook (used by both chat pages) that reconciles
  the optimistic copy with server state via a goalReconciliationKey, de-duping
  the copy-pasted goal block across the two pages.
- Stop /goal status|clear failures from escaping handleSubmit as unhandled
  rejections (handleGoalCommand now returns success; the run only starts when a
  goal was actually saved).
- Use a function replacer for the goal-status toast so an objective containing
  $&/$1 isn't treated as a replacement pattern.

Backend cleanliness / correctness
- De-duplicate four byte-identical helpers (_call_checkpointer_method,
  _message_type, _additional_kwargs, _is_visible_message) by importing them
  from runtime.goal instead of re-defining them in the run worker.
- Remove the dead `checkpoint_tuple.tasks` durability guard (CheckpointTuple has
  no tasks field) and document that pending_writes is the durability signal.
- Decompose the 176-line _prepare_goal_continuation_input: extract
  _reread_goal_and_checkpoint and a _persist closure so the thread-unchanged
  guard and stand-down persistence aren't open-coded three times. Document the
  last-writer-wins write-window limitation as a follow-up.
- Add a shared parse_goal_command helper and use it from the TUI and IM-channel
  /goal handlers (one place for the status/clear/set semantics).

Tests
- Restore the 11 command-registry tests dropped by the previous goal change
  (filter_commands ranking/description, build_registry builtins/skills, resolve
  cases) alongside the new goal tests.
- Add coverage for the IM-channel _handle_goal_command, the TUI _handle_goal
  handler, parse_goal_command, and goalReconciliationKey.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

* fix goal review feedback

* fix goal continuation checkpoint races

* prioritize goal commands while streaming

Route composer submits through a shared helper so /goal commands can be handled before the streaming stop shortcut, while ordinary streaming submits still stop the active run.

Testing: cd frontend && pnpm exec rstest run tests/unit/components/workspace/input-box-helpers.test.ts tests/unit/components/workspace/goal-status-helpers.test.ts; cd frontend && pnpm check

* preserve goal status during clarification

Keep omitted stream goal fields distinct from explicit null clears so clarification interrupts do not hide an active thread goal that is still present in the checkpoint.

Testing: pnpm exec rstest run tests/unit/components/workspace/use-active-goal.test.ts tests/unit/components/workspace/input-box-helpers.test.ts tests/unit/components/workspace/goal-status-helpers.test.ts; pnpm check; git diff --check

* style: format active goal hook

Run Prettier on use-active-goal.ts to satisfy the frontend lint workflow formatting gate.

Testing: pnpm format; pnpm exec rstest run tests/unit/components/workspace/use-active-goal.test.ts tests/unit/components/workspace/input-box-helpers.test.ts tests/unit/components/workspace/goal-status-helpers.test.ts; pnpm check; git diff --check

* fix goal review followups

---------

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-03 08:49:33 +08:00

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5.3 KiB
Markdown

# DeerFlow Terminal Workbench (TUI)
`deerflow` is a terminal-native workbench for the DeerFlow harness. It runs
**embedded** over `DeerFlowClient` — no Gateway, frontend, nginx, or Docker
services required — while honoring the same `config.yaml`, checkpointer, skills,
memory, MCP, and sandbox settings as the rest of DeerFlow.
![DeerFlow TUI](../../docs/tui/tui-preview.svg)
## Install & run
The TUI ships as an optional extra so the core harness install stays lean:
```bash
uv pip install 'deerflow-harness[tui]' # or: pip install textual
```
Launch modes:
| Command | Behavior |
|---|---|
| `deerflow` | Launch the TUI when stdin/stdout are TTYs |
| `deerflow --tui` | Force the TUI (clear diagnostic if `textual` is missing) |
| `deerflow --cli` | Force headless/classic mode for one invocation |
| `deerflow chat` | Same TUI conversation surface |
| `deerflow --continue` | Resume the most recent thread |
| `deerflow --resume THREAD` | Resume a thread by id |
| `deerflow --print "question"` | Headless one-shot answer to stdout |
| `deerflow --json "question"` | Headless newline-delimited `StreamEvent`s |
| `echo "q" \| deerflow --print` | Read the message from stdin |
| `DEER_FLOW_TUI=1 deerflow` | Force the TUI via environment |
If no TTY is available and no headless flag is given, `deerflow` prints guidance
instead of hanging.
## Surface
- **Header** — model, thread, project root, skill/tool counts.
- **Transcript** — user prompts, assistant answers, and compact tool cards
(`⚙ Read path ✓`) with dimmed result previews. Finalized assistant messages
render as Markdown (headings, bold, lists, code, links); the actively-streaming
message stays plain text to avoid reflow jumpiness and snaps to Markdown when
it completes. Transcript re-renders are coalesced (~16 fps) so streaming stays
smooth on long threads.
- **Status line** — run state + animated spinner, model, thread title, token
usage, and an `esc interrupt` hint while a run is active.
- **Composer** — rounded input box. `/` opens the command palette.
### Keys
| Key | Action |
|---|---|
| `Enter` | Send message / accept palette selection |
| `/` | Open the slash-command palette |
| `↑` / `↓` | Palette navigation, or input history when the palette is closed |
| `Tab` | Complete the highlighted command (adds a trailing space) |
| `Esc` | Close the palette / overlay |
| `Ctrl+C` | Interrupt the active run, or quit when idle |
| `Ctrl+L` | Redraw · `Ctrl+U` clear composer |
### Slash commands
`/help` `/new` `/goal` `/threads` (`/switch`) `/model` `/skills` `/tools`
`/mcp` `/memory` `/uploads` `/usage` `/config` `/quit`, plus
`/<skill-name> task` to activate any enabled skill for the current turn (same
semantics as elsewhere in DeerFlow). `/model` and `/threads` open modal pickers.
Use `/goal <condition>` to set the active thread goal, `/goal` to show it, and
`/goal clear` to clear it.
## Architecture
The TUI is a UI shell over the existing embedded harness — it does **not** fork
agent behavior.
```
cli.py launch-mode planning (pure) + headless print/json + entry point
session.py builds DeerFlowClient (+ checkpointer) and the persistence writer
runtime.py StreamEvent -> reducer actions (pure translate + threaded driver)
view_state.py ViewState + reduce(state, action) (pure, the testable heart)
message_format compact tool summaries / truncation (pure)
command_registry slash-command registry + resolve (pure)
input_history bounded ↑/↓ history (pure)
render.py Rich renderers for header / transcript / status / palette (pure)
theme.py palette + symbols
app.py Textual App: composes widgets, drives runs on a worker thread,
marshals actions back to the UI thread, renders ViewState
persistence.py writes threads_meta so sessions appear in the Web UI (below)
```
`DeerFlowClient.stream()` is a **synchronous** generator, so the app runs it on a
Textual worker *thread* and marshals each yielded action back to the UI thread
via `call_from_thread`. The pure layers (everything except `app.py`) have no
Textual dependency and are unit-tested directly with synthetic `StreamEvent`s.
## Web UI visibility (shared persistence)
The Web UI lists conversations from the `threads_meta` SQL table (filtered by
`user_id`), **not** from the checkpointer. An embedded run only writes the
checkpointer, so a TUI thread would otherwise be invisible in the sidebar.
`persistence.py` closes that gap: on the first turn of a thread it writes a
`threads_meta` row — owned by the local default user (`"default"`) — into the
**same** database the Gateway reads, and syncs the generated title afterward.
This requires only the shared `threads_meta` store (built via
`deerflow.persistence.engine.init_engine_from_config`), **not** the Gateway
process. When the database backend is `memory` (no SQL store) the writer
degrades to a silent no-op and the TUI still works.
All DB work runs on one long-lived background event loop, because a SQLAlchemy
async engine is bound to the loop that created it.
## Tests
Pure layers are TDD'd in `backend/tests/test_tui_*.py`; the Textual app, slash
palette, and modal overlays are exercised through Textual's pilot harness with a
fake in-process session (no live model). `test_tui_persistence.py` proves the
`threads_meta` write/read round-trip.
```bash
cd backend && PYTHONPATH=. uv run pytest tests/ -k tui -q
```