### What problem does this PR solve?
Closes#15872
On pages that contain both a textless equation and a figure, the layout
recognizer could merge the two unrelated regions into a single cropped
image with concatenated captions. This shows up most often on scientific
and technical PDFs.
The cause is a `layoutno` namespace collision in
`deepdoc/vision/layout_recognizer.py`. Text-overlapping boxes are tagged
per type by `findLayout`: figures become `figure-{ii}` using the
figure-only index, and equations become `equation-{ii}` using the
equation-only index. The fallback loop that handles textless regions,
however, indexes the combined figure plus equation list and always uses
a `figure` prefix.
Because the two paths use different index spaces and prefixes, a page
laid out as `[textless equation, figure with text]` produces two boxes
tagged `figure-0`. `_extract_table_figure` in
`deepdoc/parser/pdf_parser.py` buckets boxes by `f"{page}-{layoutno}"`,
so both fall into the same `page-figure-0` bucket, and `cropout`
stitches the disjoint regions into one image.
**Fix**
The fallback loop now iterates per type, indexes within each type's own
list, and reuses the type as the `layoutno` prefix (`figure-{i}` or
`equation-{i}`). This matches the namespace that `findLayout` already
assigns to text-overlapping boxes. Since the `visited` flag is shared by
reference, each layout is tagged by exactly one path, so per-type
indices stay collision free. Textless equations now land under
`equation-N`, consistent with text-overlapping equations, instead of the
old `figure-N`.
The same fix is applied to `AscendLayoutRecognizer`, which shared the
identical defect.
Downstream consumers of `layoutno` were checked and all treat it as an
opaque equality or bucketing key, so no other code paths are affected.
When a page has no equations, the combined index equals the figure-only
index and the output is unchanged.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
## Summary
- **Backend**: `_iter_session_completion_events` in `agent_api.py` was
filtering out `user_inputs` and `workflow_finished` SSE events, causing
agents with UserFillUp components to silently fail in explore mode — the
interactive form never appeared, while the same agent worked correctly
in run (editor) mode.
- **Frontend**: `SessionChat` component in explore mode was missing
`DebugContent` children rendering inside `MessageItem`, so even if the
backend forwarded the events, the form UI would not render. Added
`DebugContent`, `MarkdownContent`, `useAwaitCompentData` hook, and
input-disabling logic to match the run mode's `chat/box.tsx` behavior.
## What was changed
### Backend (`api/apps/restful_apis/agent_api.py`)
- Line 266: Added `"user_inputs"` and `"workflow_finished"` to the
allowed event filter in `_iter_session_completion_events`
### Frontend (`web/src/pages/agent/explore/components/session-chat.tsx`)
- Added imports: `DebugContent`, `MarkdownContent`,
`useAwaitCompentData`, `useParams`
- Added `sendFormMessage` from `useSendSessionMessage()` hook
- Added `useAwaitCompentData` hook for form state management
- Added `DebugContent` as `MessageItem` children for the latest
assistant message (renders UserFillUp form)
- Added `MarkdownContent` + submitted values display for previous
assistant messages
- Updated `NextMessageInput` disabled states to respect `isWaitting`
(form submission in progress)
## Test plan
- [x] Agent with UserFillUp component (e.g., email draft with
send/edit/cancel options) shows interactive form in **explore mode**
- [x] Same agent continues to work correctly in **run (editor) mode**
- [x] Form submission sends data back to the agent and workflow
continues
- [x] Input field is disabled while waiting for form submission
- [ ] Agents without UserFillUp components are unaffected in explore
mode
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
## Summary
- **Lazy img_np loading**: `np.array(img)` is now deferred until the
first OCR text extraction is actually needed, avoiding unnecessary
memory allocation for pages that already have text.
- **Chunked parse_into_bboxes**: Large PDFs (>50 pages, configurable via
`PDF_PARSER_PAGE_BATCH_SIZE`) are processed in batches. Each chunk's
boxes are normalized with `_to_global_boxes` to produce globally
consistent page numbers and position tags.
- **DLA early init**: Move remote-client initialization before model
loading in `LayoutRecognizer.__init__` so `DEEPDOC_URL` (or legacy
`TENSORRT_DLA_SVR`) short-circuits unnecessary model download for parser
containers relying on remote inference.
- **Fix outline regression**: Restore `self.outlines =
extract_pdf_outlines(fnm)` in `parse_into_bboxes`; this was dropped
during refactoring and is required by downstream `remove_toc` and
metadata handling in `rag/flow/parser/parser.py`.
## Test plan
- [ ] Small PDF (<=50 pages): verify parse succeeds and `self.outlines`
is populated
- [ ] Large PDF (>50 pages): verify chunked processing produces globally
consistent page numbers
- [ ] With `DEEPDOC_URL` set: verify remote DLA client is used and local
model is not downloaded
- [ ] With legacy `TENSORRT_DLA_SVR` set: verify backward compatibility
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
## Problem
When PDF fonts lack ToUnicode/CMap mappings, pdfplumber (pdfminer)
cannot map CIDs to correct Unicode characters, outputting PUA characters
(U+E000~U+F8FF) or `(cid:xxx)` placeholders. The original code fully
trusted pdfplumber text without any garbled detection, causing garbled
output in the final parsed result.
Relates to #13366
## Solution
### 1. Garbled text detection functions
- `_is_garbled_char(ch)`: Detects PUA characters (BMP/Plane 15/16),
replacement character U+FFFD, control characters, and
unassigned/surrogate codepoints
- `_is_garbled_text(text, threshold)`: Calculates garbled ratio and
detects `(cid:xxx)` patterns
### 2. Box-level fallback (in `__ocr()`)
When a text box has ≥50% garbled characters, discard pdfplumber text and
fallback to OCR recognition.
### 3. Page-level detection (in `__images__()`)
Sample characters from each page; if garbled rate ≥30%, clear all
pdfplumber characters for that page, forcing full OCR.
### 4. Layout recognizer CID filtering
Filter out `(cid:xxx)` patterns in `layout_recognizer.py` text
processing to prevent them from polluting layout analysis.
## Testing
- 29 unit tests covering: normal CJK/English text, PUA characters, CID
patterns, mixed text, boundary thresholds, edge cases
- All 85 existing project unit tests pass without regression
### What problem does this PR solve?
change:
remove garbage filtering rules
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Supports Ascend layout recognizer.
Use the environment variable `LAYOUT_RECOGNIZER_TYPE=ascend` to enable
the Ascend layout recognizer, and `ASCEND_LAYOUT_RECOGNIZER_DEVICE_ID=n`
(for example, n=0) to specify the Ascend device ID.
Ensure that you have installed the [ais
tools](https://gitee.com/ascend/tools/tree/master/ais-bench_workload/tool/ais_bench)
properly.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Optimize OCR garbage identification to reduce unnecessary filtering.
#5713
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Related source file is in Windows/DOS format, they are format to Unix
format.
### Type of change
- [x] Refactoring
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
