## Summary
Adds page-range parsing support to the Go-native pipeline path and
introduces strict `parse_type` validation for both dataset and document
update endpoints.
## What changed
### Pages range parsing
- **`internal/utility/pdf_pages.go`** — `NormalizePDFPages`: normalizes
raw page ranges (list of `[from,to]` 1-indexed inclusive ranges) into
sorted, merged, deduplicated `[][]int`. Invalid ranges are dropped.
- **`internal/ingestion/pipeline/pdf_pages.go`** —
`NormalizeParserConfigPages`: walks any parser_config map and normalizes
`"pages"` values under every component → filetype setup, so the
persisted config always carries clean, merged ranges.
- **`internal/deepdoc/parser/pdf/parser.go`** — integrates
`resolvePagesToProcess` to filter parsed PDF pages by the configured
ranges.
- Pipeline integration (parser pages):
`internal/parser/parser/pdf_parser_common.go`, `chunk_process.go`, plus
associated e2e and unit tests.
### Parse type validation (shared logic)
- **`internal/service/parser_mode.go`** (new) — `ValidateParseTypeMode`:
shared function that validates `parse_type` (1=BuiltIn/parser_id,
2=Pipeline/pipeline_id) and ensures the corresponding field is present.
Used by both dataset and document update endpoints.
- **`internal/service/dataset/crud.go`** / `update.go` — replaces inline
`isPipelineMode`/`isBuiltinMode` computation with the shared
`service.ValidateParseTypeMode`.
- **`internal/service/document/document_dataset_update.go`** — adds
strict `parse_type` validation in `validateDatasetDocumentUpdate`,
simplifies the reparse logic to a two-way switch (isBuiltin/isPipeline)
now that parse_type is always valid.
- **`internal/service/document/document.go`** — adds `ParseType` field
to `UpdateDatasetDocumentRequest`.
- **`internal/service/document/document_dataset_update.go`** —
`updateDocumentParserConfig` fallback path when DSL loading fails.
- **`internal/service/parser_mode_test.go`** (new) — test coverage for
nil, invalid, and missing-field scenarios.
### Frontend
- **`web/src/interfaces/request/document.ts`** — adds `parseType` to
`IChangeParserRequestBody`.
- **`web/src/hooks/use-document-request.ts`** —
`useSetDocumentPipelineParser` sends `parse_type` in the PATCH payload.
- **`web/src/pages/dataset/dataset/use-change-document-parser.ts`** —
Go/Python branching for the document parser config dialog.
-
**`web/src/components/document-pipeline-dialog/use-document-pipeline-form.ts`**
— `buildSubmitData` returns `parseType` (bugfix: was dropped from the
return value).
### Test changes
- **Removed**: 2 tests that verified the old "mutually exclusive" error
(replaced by `ValidateParseTypeMode` coverage).
- **Modified**: 6 tests across document and dataset packages to include
`ParseType` in request structs.
- **Added**: new e2e tests for pages parsing (`pages_e2e_test.go`,
`pdf_parser_pages_e2e_test.go`) and unit tests for `NormalizePDFPages`,
`NormalizeParserConfigPages`, `resolvePagesToProcess`.
## Backward compatibility
- The `parse_type` field is **required** when `parser_id` or
`pipeline_id` is sent. This changes the contract for both dataset and
document PATCH endpoints, but aligns the Go backend with the existing
frontend behavior (the frontend already sends `parse_type`). Callers
that omit `parse_type` when updating parser/pipeline selections will
receive a clear error message.
- Existing callers that only update fields like `name`, `enabled`, or
`meta_fields` are unaffected.
- Test updates ensure all known call sites are compliant.
### Summary
As title:
Some operations on datasets have been fixed as they previously lacked
authentication, preventing team members from proper or correct usage.
---------
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
## Summary
Align the Go ingestion pipeline with Python's `image` → `img_id`
persistence semantics, and unify the chunk-id computation across all
paths.
### Changes
**1. Image upload at chunker stage **
- Add `ImageUploader` type and `DefaultImageUploader` in
`internal/ingestion/component/image_uploader.go` — the write-side
counterpart to `FetchBinary`, storing raw image bytes at `(bucket=kbID,
key=chunkID)`, no re-encoding.
- Add `uploadOneImage` — pure upload primitive (bytes in, `img_id` out),
does not touch chunk maps.
- Add `uploadChunkImages` / `uploadChunkImage` — caller-side helper:
decodes `image` from a chunk, uploads bytes, writes `ck["img_id"]`,
`delete(ck,"image")` , bounded by a process-wide semaphore (default 10,
env `MAX_CONCURRENT_MINIO`).
- Wire via `imageUploadDecorator` in `register.go`: every chunker runs
the upload pass at invocation time, writing `ck["id"]` before upload and
dropping image bytes right after — peak memory = single chunk image
lifetime.
**2. Unify chunk-id computation**
- Consolidate three separate id-computation paths (`component.ChunkID`,
`task.ChunkID`, inline `FormatUint` in API) into one:
`common.ChunkID(docID, text string)`, using `%016x` +
`xxhash.Sum64String(text+docID)` (matching Python `hexdigest()`).
- The chunker decorator writes `ck["id"]` via `common.ChunkID`; the
persist stage (`ProcessChunksForPipeline`) falls back to the same
function (`if !exists id`).
- The API AddChunk path now also calls `common.ChunkID` instead of the
divergent `FormatUint(xxhash.Sum64(...))` — fixing a pre-existing
inconsistency.
- Delete `internal/ingestion/component/chunk_id.go` and
`internal/ingestion/task/chunk_builder.go` (both were pure forwarding
shells).
**3. Preserve `img_id` (never deleted)**
- `img_id` is a persistent index field (Infinity, OB) and the only
consumer-side reference for image retrieval; it is NEVER removed from
the chunk map. Only `image` (raw data URL) is dropped after upload.
**4. PPT parser support**
Previously PPT parsing failed. Add support to parse.
### Key design decisions
| Decision | Choice |
|----------|--------|
| Upload timing | Chunker stage (not persist), so image bytes are
dropped immediately — bounds peak memory to one chunk image |
| Upload concurrency | Process-wide semaphore, default 10 (matches
Python `minio_limiter`), env `MAX_CONCURRENT_MINIO` |
| Image encoding | Store as-is, no JPEG re-encoding (unlike Python) |
| `img_id` format | `"<kb_id>-<chunk_id>"` — matches Python
task_executor path |
| id function | Single `common.ChunkID(docID, text)`, concatenation
`text+docID` inside hash (matching Python) |
| `removeInternalChunkFields` | Retains `delete(ck,"image")` as
defensive fallback for non-chunker paths |
### Files touched
| File | Change |
|------|--------|
| `internal/common/format.go` | Add `ChunkID(docID, text)` |
| `internal/common/format_test.go` | Add ChunkID golden-value test |
| `internal/ingestion/component/image_uploader.go` | Add `ImageUploader`
type + `DefaultImageUploader` |
| `internal/ingestion/component/chunker/image_upload.go` | Add
`uploadOneImage`, `uploadChunkImages`, `uploadChunkImage`,
`decodeChunkImage`, semaphore |
| `internal/ingestion/component/chunker/image_upload_test.go` | Tests:
upload/drop, skip, no-image, concurrency, missing-id error |
| `internal/ingestion/component/chunker/register.go` | Add
`imageUploadDecorator` (writes `ck["id"]`, runs upload) |
| `internal/ingestion/task/chunk_process.go` | Use `common.ChunkID` for
persist fallback |
| `internal/service/chunk/chunk.go` | Use `common.ChunkID` instead of
`FormatUint` |
| `internal/ingestion/component/chunk_id.go` | **Deleted** (moved to
`common`) |
| `internal/ingestion/task/chunk_builder.go` | **Deleted** (shell, no
callers left) |
| `internal/ingestion/task/chunk_builder_test.go` | **Deleted** (test
migrated to `common/format_test.go`) |
### Verification
```
bash build.sh --test ./internal/service/chunk/... ./internal/common/... ./internal/ingestion/component/... ./internal/ingestion/task/...
→ ok service/chunk / common / component / chunker / schema / task
```
### Summary
1. list and get by id API for builtin DSL
2. add DSL default component param values validation
3. remove all hard code keys for parser config
### Summary
```
RAGFlow(api/default)> CHAT WITH 'glm-4-flash@new_test@zhipu-ai' MESSAGE '30 words describes LLM';
Answer: Hello! I'm ChatGLM, an AI assistant. Feel free to ask me any questions or request help with any tasks.
Input tokens: 5
Output tokens: 28
Time: 12.748241
```
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- Preserve request-scoped system variables such as files and user IDs
during Canvas execution.
- Persist conversation history, turn counts, and tool memory in the
session DSL across turns.
- Parse agent uploads into `sys.files` and align system variable
rendering with Python.
## Testing
- `bash build.sh --test ./internal/agent/...`
- `bash build.sh --test ./internal/service/...`
<img width="1896" height="1232" alt="image"
src="https://github.com/user-attachments/assets/b420cd97-53c3-470f-a3e1-d39cea26a213"
/>
### What problem does this PR solve?
Await Response incorrectly consumed the initial `sys.query` as its
input, so the first user interaction was skipped.
This change makes Await Response wait for actual user input while
preserving the existing initial-query behavior for the Begin node.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
