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## 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.
284 lines
8.5 KiB
Go
284 lines
8.5 KiB
Go
//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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package task
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import (
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"fmt"
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"strings"
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"time"
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"ragflow/internal/common"
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"ragflow/internal/utility"
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)
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// RenameTextToContentWithWeight renames the "text" key to "content_with_weight".
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// If "content_with_weight" already exists, the "text" key is simply removed.
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// Mirrors Python: ck["content_with_weight"] = ck["text"]; del ck["text"]
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func RenameTextToContentWithWeight(chunk map[string]any) {
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if _, exists := chunk["content_with_weight"]; !exists {
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if text, ok := chunk["text"]; ok {
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chunk["content_with_weight"] = text
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}
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}
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delete(chunk, "text")
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}
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// GetEmbeddingTokenConsumption extracts the embedding token consumption from pipeline output.
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// Handles both int (Go native) and float64 (after JSON round-trip).
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func GetEmbeddingTokenConsumption(output map[string]any) int {
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if output == nil {
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return 0
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}
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switch v := output[EmbeddingTokenConsumptionKey].(type) {
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case int:
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return v
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case float64:
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return int(v)
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default:
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common.Warn(fmt.Sprintf("unexpected type %T for embedding token consumption, key=%q", v, EmbeddingTokenConsumptionKey))
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return 0
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}
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}
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// ProcessChunksForPipeline mutates chunks into the pre-index structure used by
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// the pipeline and returns merged metadata. It returns an error if a chunk's
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// "text" field is present but not a string: that is an upstream contract
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// violation (the chunker/parser must emit string text), and continuing would
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// collapse every such chunk onto the same empty-text ChunkID, silently
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// overwriting each other in the index. The caller fails the task so the
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// violation surfaces instead of corrupting the index.
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func ProcessChunksForPipeline(
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chunks []map[string]any,
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docID string,
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kbID string,
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docName string,
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now time.Time,
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) (map[string]any, error) {
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if chunks == nil {
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return nil, nil
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}
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metadata := make(map[string]any)
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timeStr := now.Format("2006-01-02 15:04:05")
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timestamp := float64(now.UnixMicro()) / 1e6
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for _, ck := range chunks {
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ck["doc_id"] = docID
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ck["kb_id"] = []string{kbID}
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ck["docnm_kwd"] = docName
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ck["create_time"] = timeStr
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ck["create_timestamp_flt"] = timestamp
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if _, exists := ck["id"]; !exists {
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text, _ := ck["text"].(string)
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ck["id"] = common.ChunkID(docID, text)
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}
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cleanupConsumedChunkFields(ck)
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metadata = mergeChunkMetadata(metadata, ck)
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RenameTextToContentWithWeight(ck)
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processChunkPositions(ck)
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}
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return metadata, nil
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}
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// cleanupConsumedChunkFields materializes the stored array form of the
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// questions/keywords fields (when the upstream Tokenizer did not already set
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// them) and strips the consumed source fields (questions/keywords/summary)
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// before persist. This is persist-schema mapping, NOT linguistic tokenization:
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// question_tks / important_tks / content_ltks are owned by the Tokenizer
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// component; the executor no longer falls back to producing them.
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func cleanupConsumedChunkFields(ck map[string]any) {
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if q, ok := ck["questions"].(string); ok {
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if _, has := ck["question_kwd"]; !has {
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ck["question_kwd"] = utility.SplitQuestions(q)
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}
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}
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delete(ck, "questions")
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if kws, ok := ck["keywords"].(string); ok {
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if _, has := ck["important_kwd"]; !has {
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ck["important_kwd"] = utility.SplitKeywords(kws)
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}
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}
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delete(ck, "keywords")
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delete(ck, "summary")
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}
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func mergeChunkMetadata(metadata map[string]any, ck map[string]any) map[string]any {
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metaVal, exists := ck["metadata"]
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if !exists {
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return metadata
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}
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if metaMap, ok := metaVal.(map[string]any); ok {
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metadata = utility.UpdateMetadataTo(metadata, metaMap)
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}
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delete(ck, "metadata")
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return metadata
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}
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// processChunkPositions converts the raw "positions" field into indexable
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// position fields (page_num_int, top_int, position_int) via AddPositions,
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// then removes the raw "positions" and the sibling "_pdf_positions" internal
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// field. _pdf_positions is the parser-emitted position matrix consumed by
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// the chunker's image-crop pass (pdfcrop_cgo.go); after the chunker it is
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// dead weight with no index column, so it is pruned unconditionally —
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// independent of "positions" and not gated on the early-return below.
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//
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// Two source types reach this point:
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// - []float64 — flat array of 5-tuples [page,left,right,top,bottom,…] from
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// parsers that emit positions directly as a flat float64 slice.
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// - [][]float64 — the production path: positions flow through ChunkDoc
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// (json.RawMessage → decodeStructuredValue) which produces a slice of
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// 5-element groups.
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//
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// Both are flattened into a single []float64 for AddPositions, which groups
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// by 5 internally. Unexpected types are logged and discarded.
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func processChunkPositions(ck map[string]any) {
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delete(ck, "_pdf_positions")
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poss, exists := ck["positions"]
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if !exists {
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return
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}
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switch v := poss.(type) {
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case []float64:
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AddPositions(ck, v)
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case [][]float64:
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flat := make([]float64, 0, len(v)*5)
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for _, group := range v {
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flat = append(flat, group...)
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}
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AddPositions(ck, flat)
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default:
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common.Warn(fmt.Sprintf("chunk positions unexpected type %T; discarding", poss))
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}
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delete(ck, "positions")
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}
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// AggregateTableDocMetadata collects unique per-column values across all chunks
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// for columns with role "metadata" or "both", merges them into document metadata.
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// Mirrors Python: rag/utils/table_es_metadata.py:aggregate_table_doc_metadata
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func AggregateTableDocMetadata(chunks []map[string]any, parserConfig map[string]interface{}) map[string]any {
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mode, roles, tableColumnNames := resolveTableColumnConfig(parserConfig)
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if mode == "" {
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mode = "auto"
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}
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if mode != "auto" && mode != "manual" {
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return nil
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}
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if roles == nil {
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roles = map[string]interface{}{}
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}
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var metaCols []string
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if len(tableColumnNames) > 0 {
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for _, n := range tableColumnNames {
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col, _ := n.(string)
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if col == "" {
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continue
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}
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role, _ := roles[col].(string)
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if role == "" {
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role = "both"
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}
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if role == "metadata" || role == "both" {
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metaCols = append(metaCols, col)
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}
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}
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} else {
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for col, v := range roles {
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role, _ := v.(string)
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if role == "metadata" || role == "both" {
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metaCols = append(metaCols, col)
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}
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}
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}
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if len(metaCols) == 0 {
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return nil
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}
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acc := make(map[string]map[string]struct{}, len(metaCols))
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for _, col := range metaCols {
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acc[col] = make(map[string]struct{})
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}
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for _, ck := range chunks {
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cd, _ := ck["chunk_data"].(map[string]interface{})
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if cd == nil {
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continue
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}
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for _, col := range metaCols {
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val, ok := cd[col]
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if !ok {
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continue
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}
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s, _ := val.(string)
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if s == "" {
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continue
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}
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acc[col][s] = struct{}{}
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}
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}
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out := make(map[string]any, len(acc))
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for col, vals := range acc {
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if len(vals) == 0 {
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continue
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}
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deduped := make([]string, 0, len(vals))
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for v := range vals {
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deduped = append(deduped, v)
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}
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out[col] = deduped
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}
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return out
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}
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// resolveTableColumnConfig reads table column settings from parser_config.
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// Tries root-level flat keys first; falls back to resolving from a Parser
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// component entry's spreadsheet config in a component-ID-keyed parser_config.
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func resolveTableColumnConfig(parserConfig map[string]interface{}) (mode string, roles map[string]interface{}, names []interface{}) {
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mode, _ = parserConfig["table_column_mode"].(string)
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roles, _ = parserConfig["table_column_roles"].(map[string]interface{})
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rawNames, _ := parserConfig["table_column_names"].([]interface{})
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if mode != "" || roles != nil || len(rawNames) > 0 {
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return mode, roles, rawNames
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}
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for cid, raw := range parserConfig {
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if !strings.HasPrefix(cid, "Parser:") {
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continue
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}
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comp, _ := raw.(map[string]interface{})
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if comp == nil {
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continue
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}
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ss, _ := comp["spreadsheet"].(map[string]interface{})
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if ss == nil {
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continue
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}
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if v, ok := ss["column_mode"].(string); ok {
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mode = v
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}
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if v, ok := ss["column_roles"].(map[string]interface{}); ok {
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roles = v
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}
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if v, ok := ss["column_names"].([]interface{}); ok {
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rawNames = v
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}
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return mode, roles, rawNames
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}
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return "", nil, nil
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}
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