## Summary
Fixes the agent `Switch` component matching an **empty/all-skipped
condition** unconditionally because `all([]) is True`.
## Root cause
`res` only accumulates for items with a non-empty `cpn_id` (blank ones
`continue`). For a condition with empty `items` (or all-blank `cpn_id`),
`res == []`, and `if all(res):` is `True`, so the Switch routes to that
condition's `to` target before reaching the else/`end_cpn_ids` branch.
## Fix
```diff
- if all(res):
+ if res and all(res):
```
An empty result set no longer counts as a match; genuinely-satisfied
"and" conditions still route (the real `all(res)` path is preserved).
## Files changed
- `agent/component/switch.py`
- `test/unit_test/agent/component/test_switch_empty_condition.py` (new)
## Verification
- `ruff check` / `ruff format --check` — clean
- Added unit tests (mirroring the existing `_FakeCanvas` component-test
pattern): an empty/all-skipped "and" condition now falls through to
`end_cpn_ids`; a genuinely-satisfied "and" condition still routes to its
target.
- Local full pytest not run (heavy RAG deps); CI validates.
## Note
Implemented with LLM assistance (model: claude-opus-4-8).
Closes#15643
---------
Co-authored-by: seekmistar01 <seekmistar01@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
## Summary
#16332 fixed the missing `return` in DeepL's except branch, but
`ComponentBase.be_output` was removed during the agent refactor (#9113)
while several components still call it. DeepL (and other tools) would
raise `AttributeError` before any error message could be returned.
- Restore `ComponentBase.be_output` as `pd.DataFrame([{"content": v}])`
(same as pre-refactor behavior)
- Add regression test that `_run` returns the `**Error**:` message when
translation fails
Related to #16329
## Test plan
- [x] `test_run_returns_error_on_translation_failure`
- [x] Existing `test_deepl.py` check() tests still pass
---------
Co-authored-by: Harsh Kashyap <harshkashyap@Harshs-MacBook-Pro.local>
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
### What problem does this PR solve?
`DeepLParam.check()` validated `self.top_n`, but DeepL has no such
parameter (it is not defined on the param class or its base), so
`check()` always raised `AttributeError` and a DeepL component could
never pass validation. Removed the bogus `top_n` check.
Also fixed the `_run` except branch, which computed
`be_output("**Error**...")` but never returned it, silently dropping the
error message.
Closes#16329
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Add test cases
### Testing
Added `test/unit_test/agent/component/test_deepl.py` covering
`DeepLParam.check()` with valid defaults and rejection of invalid
source/target languages.
### What problem does this PR solve?
Browser parsed sys.query from prompts but never called set_input_value,
so node_finished inputs displayed null in the agent orchestration run
log.
Additionally, Browser’s tenant-model path could trigger unsupported
structured-output modes (response_format/tool_choice) for some
OpenAI-compatible providers (notably DeepSeek thinking models), causing
step failures.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
## What
- make `Switch` ignore conditions that have no evaluable items
- add a regression for blank `cpn_id` items falling through to the else
branch
- keep the existing non-empty `and` condition behavior covered
Fixes#15643.
## Verified
- `python -m py_compile agent\component\switch.py
test\unit_test\agent\component\test_switch.py`
- `python -m pytest test\unit_test\agent\component\test_switch.py -q` ->
`2 passed`
- `python -m ruff check agent\component\switch.py
test\unit_test\agent\component\test_switch.py`
- `git diff --check`
I also checked `python -m ruff format --check` on the touched files. It
would reformat pre-existing style in `agent/component/switch.py` beyond
this bug fix, so I kept the patch scoped instead of reformatting the
whole file.
### What problem does this PR solve?
This PR adds a new `Browser` operator to Agent workflows, enabling
prompt-driven browser automation in RAGFlow.Technically based
‘Browser-Use’
It includes:
- Backend browser component execution with tenant LLM integration
- Upload source support (file IDs, URLs, variables, CSV/JSON array)
- Downloaded file persistence to RAGFlow storage
- Frontend node/operator integration, form config, icon, and i18n
updates
- Unit tests for upload/download and ID parsing logic
- Dependency and Docker updates for browser-use runtime support
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
