Refactor the Extractor component into a pure, unified **5-in-1 modular extraction engine** across both Dataset (`knowledgebase.parser_config`) and Pipeline (Canvas DSL).
This PR modularizes the **Extractor** component configuration with dedicated feature subtabs, adds independent system prompt configuration, fixes multi-node execution determinism and parameter persistence across save and page refresh, and ensures backward compatibility with legacy flat fields.
Add `ManualChunker`, the Go port of Python's `manual` doc-type chunk method (`rag/app/manual.py`). Like `GroupTitleChunker` it merges adjacent text records into heading-bounded groups, but it first re-sorts the records into physical reading order before grouping.
When `TokenChunker` starts a fresh chunk with an overlap prefix (Go `computeOverlapPrefix` / Python visible-text cut), the previous chunk's **tail PDF coordinates were dropped**. As a result, the overlap head of a PDF chunk is displayed but **not highlighted** — the highlight box is shifted/truncated relative to the displayed span (infiniflow/ragflow#18148).
Collapse the nine identical **"cut through the last `</think>`"**
implementations — mirroring Python's `re.sub(r"^.*</think>", "", s,
re.DOTALL)` — into one shared helper `common.StripThinkTrailing`,
preventing future behavior drift between copies.
Fix compilation template config validation for JSONMap; merge template groups into agents list ordered by category/name; install nav service in ingestor; write readable nav cluster/doc names and emit nav_doc leaves;
port tree-to-graph projection and full document structure graph endpoint parity.
Go's `TokenChunker` previously ignored **bare (non-backtick)
delimiters** such as `::`, `.`, or `；`. `compileDelimPattern` compiled
them with `keepBare=false`, so a bare delimiter produced a `nil` pattern
and the payload was routed to the single-section merge that never split
on it — diverging from Python's `naive_merge`, which splits on bare
delimiters and then merges by token size.
Make `ResolveModelContentLength` honor the per-model custom **context window length** (`content_length`) — stored in the Python-legacy `tenant_model.extra["max_tokens"]` field, whose semantic meaning is the context window, NOT the generation cap — **before** any provider-catalog read, and remove the parallel service-layer implementation so every consumer shares one resolution path.
Trim Extractor call prompts and the automatic tagger prompt to the chat model's context window (`content_length`) before sending, so oversized chunks or tag files are trimmed instead of rejected by the provider with a context-length error.
### Summary
- Propagate the dataset language through Go DOCX, Markdown, PDF
figure-enhancement, and standalone-image vision paths.
- Explicitly render the shared figure prompt's `{{ language }}`
placeholder in Go.
- Use English when the dataset language is empty.
- Make the default standalone-image prompt request the dataset language
while preserving visible text in its original language.
- Add focused tests for caller propagation, language fallback, prompt
rendering, and prompt-cache isolation.
Port the wiki_incremental dataset-level merge and make its rewrite
barrier durable and concurrency-safe. Wiki pages merge replace-only; the
barrier persists a monotonic numeric generation, and a scheduler-backed
per-dataset lock closes the cross-process TOCTOU window. Adds the
Compiler Plan toggle (frontend) with Mode A grouping.
Golden-parity test infrastructure for the **Go `TokenChunker` ↔ Python alignment**.
It runs the Go chunker over a committed case set (`testdata/parity/cases/`) and diffs each output against a captured Python golden (`testdata/parity/golden/`), honoring a `known_diffs.json` ratchet (`extra_fields` / `chunk_count` / `chunk_text`) so accepted divergences are tracked rather than silently widening.
Port dataset-level wiki incremental compile and refactor splitByTokens
token budgeting. Includes replace-only wiki merge, KNN dedup routing,
and template/config wiring.
Unifies the Go TokenChunker merge path on a single `mergeUnits` core and
fixes coordinate-tag drift in the Python JSON merge at `overlap > 0`.
Rebased on top of #17979 (delimiter_mode convergence).
Re-materialize wiki page graph from merged wiki_page rows after each
batch merge. Adds ProjectWikiGraph/DropWikiGraph, full page_type/slug
identity, delete-then-insert, tests.
Converge `TokenChunker.delimiter_mode` from three values (`token_size`,
`delimiter`, `one`) to two (`delimiter`, `one`). The unified `delimiter`
mode now carries the old `token_size` semantics: when no active
(backtick) delimiter is present, text/JSON chunks are merged up to
`chunk_token_size`; when a backtick delimiter is present, the text is
split by it and not merged. `one` continues to be handled by the
separate `OneChunker`.
Restore the deduplication that was dropped when #17926 was merged.
`CompileDelimiterPatternList` now keeps a `seen` set and collapses
equivalent active entries (both backtick-inner and bare) into a single
alternation. This PR also removes the dead code that the re-review
surfaced.
`compileChildrenPattern` re-implemented the delimiter-list compile
inline with two divergences from the shared
`CompileDelimiterListPattern`:
- It never stripped backticks, so a backtick-wrapped
`children_delimiter` like `` `###` `` matched the **literal wrapped
token** rather than the inner `###`.
- It sorted by **byte length** instead of rune count (`sortSlice`), so
multi-byte delimiters could be ordered incorrectly and a longer
delimiter could fail to win over a shorter prefix.
Ports dataset knowledge compilation (wiki/graph/tree/mindmap) to the Go
scheduler with a status contract, aligns wiki storage/retrieval with
Python, sizes prompts by content_length, and resolves embedding batch
size from provider capability.
## Summary
Port the DSL tokenizer's `important_kwd` splitting into the Go
`Tokenizer` component so the indexed keyword array is byte-compatible
with the Python DSL pipeline and with the keyword-extraction prompt
contract.
- **Problem:** The Go component split `keywords` on the full ASCII+CJK
delimiter set (`utility.SplitKeywords`, regex `[,，;；、\r\n]+`), while the
DSL baseline `rag/flow/tokenizer/tokenizer.py:153` uses
`keywords.split(",")`, and `rag/prompts/keyword_prompt.md` instructs the
LLM to delimit keywords by **ENGLISH COMMA**. For a dataflow canvas that
includes the Tokenizer component, this divergence made Go's indexed
`important_kwd` differ from the Python-DSL-built index (CJK
commas/semicolons were split in Go but kept whole in Python).
- **Fix:** Use `strings.Split(kw, ",")` at `tokenizer.go:701`,
preserving empty middle elements to match Python's `"a,,b".split(",") ==
["a","","b"]`. The indexing fallback layer
(`internal/ingestion/task/indexdoc/process.go`) already mirrors the
Python multi-delimiter fallback (`dataflow_service.py:322`), so only the
component layer diverged and only it is changed.
## Test plan
- `TestTokenizerComponent_ImportantKwd_CommaOnly` (no build tag, default
`go test ./...`): switches the tokenizer to the identity engine (no CGo
pool needed) and asserts `"kw1,kw2;kw3，kw4"` → `["kw1","kw2;kw3，kw4"]`;
also asserts `important_tks` still tokenizes the full keyword string.
- `TestTokenizerComponent_Invoke_KeywordSplitCommaOnly` (`integration`
tag, real CGo analyzer): covers comma-split, CJK/semicolon-not-split,
and empty-middle preservation.
- Both tiers pass (unit `ok`, integration `ok`).
## Regression notes
- Intentional behavior change for canvases that include the Tokenizer
component: keywords containing `;`/`、`/newlines now stay as one keyword
(matching Python DSL) instead of being split. Re-indexing existing
Go-built data will change the `important_kwd` set — expected parity
cost, documented in code comments and commit message.
- Canvases without a Tokenizer component are unaffected (they hit the
unchanged multi-delimiter fallback).
- Other fields (`important_tks`, `questions`, `summary`, `text`) are
untouched; the `utility` import was removed cleanly.
