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## Summary Aligns the Go ingestion pipeline with the Python implementation, closing several behavioral gaps found during the Python→Go migration (tracked in `docs/migration_python_go_diff.md`). Covers parser/media dispatch alignment, the PDF coordinate-chain (preview images, outline→title, chunk coordinate finalization), and the Chunker Token/QA batches below. Commits are grouped as follows. ### 1. Fix parser params (c524f450e) Fixes parser/media wiring and several dispatch gaps: - **docx/pdf vision dispatch**: correct parameter handling and VLM invocation. - **markdown vision (diff 2.5)**: also enhance items whose `doc_type_kwd` is `table`, not only `image` (parser/utils.py:181). - **media audio (diff 2.11)**: when `output_format` is `json`, carry the ASR transcription as a JSON item instead of only the `Text` field (the Invoke switch had no `json` branch and dropped it). - **email (diff 2.2)**: default `output_format` is `json` (parser.py:212), not `text`. - **tokenizer**: handle empty/whitespace-only names; trim before embedding. - **extractor**: tag-matching parameter wiring. - **split**: keyword-split regex now covers CJK/English separators. - **parser.go**: parser-param plumbing. ### 2. fix parser gap (373537da1) Image dispatch now mirrors `rag/app/picture.py:chunk()`: - Always OCR the image (PaddleOCR or local ONNX). - When OCR text is short, also call VLM (`describe`) and combine `OCR + VLM` text. - Emits a **structured JSON item** carrying the image data-URI and `doc_type_kwd:"image"`, instead of a bare `Text` string. This fixes the payload being rejected downstream by OneChunker/TokenChunker (JSON=nil). ### 3. PDF coordinate-chain fixes (55367a820,727f8167c) Closes three items from the migration tracker in the chunker/tokenizer/task layer: - **(Chunker-1.3) `restore_pdf_text_previews`** — `needsCrop` now also returns true for `text` chunks that carry PDF positions (`pdfcrop_cgo.go`), so text blocks get a rendered preview image uploaded to storage via `imageUploadDecorator`/`ChunkImageUploader`, matching Python `restore_pdf_text_previews` + `image2id`. - **(Chunker-1.5) PDF outline → title levels** — `title.go` adds `outlineSimilarity` (rune-bigram Jaccard, mirroring `common.py:_outline_similarity`), `resolveOutlineLevels` (matches text lines to outline entries at similarity > 0.8, with a sparse guard `len(outline)/len(records) <= 0.03`), and `outlineFromInputs` (reads `file.outline`). Wired into `newLevelContext` in both `group.go` and `hierarchy.go`; falls back to the title-shape heuristic when no outline is present. - **(Tokenizer-(T)1) `finalize_pdf_chunk`** — the coordinate → `position_int`/`page_num_int`/`top_int` conversion is owned by the task layer (`processChunkPositions`→`AddPositions`), which runs *after* the tokenizer and consumes the tokenizer-owned fields. The tokenizer only preserves the raw `positions`/`_pdf_positions` (no duplicate conversion), pinned by `TestChunkDocsToMaps_PreservesPDFPositions`. ### 4. Integration test made environment-free (`internal/ingestion/task/pipeline_real_integration_test.go`) - Removed the `//go:build integration` tag so the contract tests run under the default `build.sh --test` (which does not pass `-tags integration`). - External dependencies replaced with in-memory substitutes so no MySQL/MinIO/ES is required: - MySQL → on-disk sqlite (`glebarez/sqlite`) with the needed tables auto-migrated. - MinIO → `storage.NewMemoryStorage()`. - Elasticsearch → chunks captured via `WithInsertFunc` instead of `engine.InsertChunks`/`Search`. - `requireTokenizerPool` still skips gracefully when the native tokenizer pool is unavailable; `WithLogCreateFunc(noop)` avoids depending on the operation-log table. - Added `taskChunkFieldEqualsStr` to tolerate `kb_id` being a `[]string`/`[]any` in the raw chunk payload (the search engine flattens it to a string on read). ### 5. TokenChunker alignment — Batch 1 (`internal/ingestion/component/chunker/token.go`) Closes four Chunker items from the migration tracker: - **(Chunker-2.1) sentence delimiter** — the boundary regex now also breaks on ASCII `!`/`?`. Extracted to a package-level `var sentenceDelimiter` and used in `mergeByTokenSize`, matching Python's full delimiter set. - **(Chunker-2.2) overlap tag leakage** — when a new chunk starts, its overlap prefix is taken from the previous chunk *after* `removeTag`, in both the text path (`mergeByTokenSize`) and the JSON path (`mergeByTokenSizeFromJSON`). Parser tags (`@@…##`) no longer leak into the overlap region (mirrors `nlp/__init__.py:1181`). - **(Chunker-2.11) empty-text merge** — merging a non-empty chunk into an empty previous chunk now assigns the text directly instead of being skipped (`mergeByTokenSizeFromJSON`), mirroring `token_chunker.py:236-239`. - **(Chunker-2.4) overlap token counting** — `takeFromEnd`/`takeFromStart` now count tokens exactly via `tokenizeStr` instead of the 4-bytes/token heuristic, fixing over-counting for CJK text. ### 6. QA Chunker alignment — Batch 2 (`internal/ingestion/component/chunker/qa.go` + `schema`) Closes three Chunker items from the migration tracker: - **(Chunker-2.13) default language** — an empty `lang` now defaults to Chinese prefixes (`问题:`/`回答:`) instead of English, matching `qa.py:299`. - **(Chunker-2.12) `rmQAPrefix` regex** — the separator is changed to `[\t:: ]+` (one-or-more), matching `qa.py:241`, so multiple separators (e.g. `Q:: answer`) are fully stripped. - **(Chunker-1.8 QA) missing chunk fields** — QA chunks now preserve: - `top_int` — the source row/record index, threaded through the tab/csv/markdown extractors (mirrors `qa.py` `beAdoc(..., row_num=i)`); - `image` + `doc_type_kwd:"image"`; - `_pdf_positions` / `positions` carried from the upstream JSON item. `schema.ChunkDoc` gains a `TopInt []int` field (serialized as `top_int`, registered in `UnmarshalJSON`). Note: the Tag/Table/Presentation/One chunker field gaps under 1.8 remain pending. ## Test plan - Added/updated unit tests: `pdfcrop_cgo_test.go` (`TestNeedsCrop`, `TestRestorePDFTextPreview`), `title_test.go` (`TestResolveOutlineLevels`, `TestResolveOutlineLevels_SparseGuard`, `TestNewLevelContext_OutlineBranch`, `TestOutlineFromInputs`), `tokenizer_unit_test.go` (`TestChunkDocsToMaps_PreservesPDFPositions`), `token_pdfpos_test.go`. - **Batch 1** — `token_batch1_test.go`: `TestSentenceDelimiterMatchesBangAndQuestion`, `TestMergeByTokenSizeFromJSON_OverlapStripsTags`, `TestMergeByTokenSizeFromJSON_EmptyPrevKeepsChunk`, `TestTakeFromEndRespectsTokenCount`, `TestTakeFromStartRespectsTokenCount`. - **Batch 2** — `qa_batch2_test.go`: `TestQAChunker_DefaultLangIsChinese`, `TestRmQAPrefixStripsMultipleSeparators`, `TestQAChunker_SetsTopInt`, `TestQAChunker_CarriesImageAndPositions`. Existing `qa_test.go` expectations were updated to the corrected language default / separator behavior. - `pipeline_real_integration_test.go` (`TestPipelineExecutor_Run_RealCanvasDSL_UsesGeneralPipeline`, `TestPipelineExecutor_Run_RealPDF_ProducesIndexedChunks`, `TestRunPipeline_RealPipelineOutput_ProducesIndexFields`) now runs without any external service. - `bash build.sh --test ./internal/ingestion/...` passes. - No files deleted.
273 lines
8.2 KiB
Go
273 lines
8.2 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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// DOCX vision figure dispatch: enriches the parse result with
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// LLM-generated descriptions of embedded images, mirroring
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// Python's enhance_media_sections_with_vision in
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// rag/flow/parser/utils.py (invoked from parser.py:_doc's JSON branch).
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//
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// Unlike the PDF vision path (which replaces dispatchParse entirely),
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// DOCX vision is a post-processing step. It mirrors Python exactly:
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// vision enrichment happens ONLY on the JSON output path, where each
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// item carries a doc_type_kwd and an optional image. The markdown path
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// performs no vision enrichment in Python, so it must not here either.
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package component
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import (
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"context"
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"fmt"
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"os"
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"path/filepath"
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"strings"
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"sync"
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"ragflow/internal/entity"
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modelModule "ragflow/internal/entity/models"
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"ragflow/internal/ingestion/component/schema"
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"ragflow/internal/utility"
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)
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var (
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docxVisionPromptBuilder = buildDOCXVisionPrompt
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visionChatInvoker = defaultVisionChatInvoker
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docxVisionConcurrency uint = 10
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)
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const (
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docxVisionPromptFile = "vision_llm_figure_describe_prompt.md"
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docxVisionPromptWithContextFile = "vision_llm_figure_describe_prompt_with_context.md"
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)
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var (
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docxVisionPromptsBase string
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docxVisionPromptsOnce sync.Once
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docxVisionPromptCache = make(map[string]string)
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docxVisionPromptMu sync.RWMutex
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)
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// maybeDispatchDOCXVision enriches a DOCX parse result with vision-model
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// descriptions of embedded images. It mirrors Python's
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// enhance_media_sections_with_vision (rag/flow/parser/utils.py:162), which
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// runs only in the JSON output branch of parser.py:_doc.
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//
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// For each JSON item whose doc_type_kwd is "image" or "table" AND that
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// carries a non-empty "image" field, the vision model describes the image
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// and the description is appended to the item's text (Python:
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// item["text"] = f"{text}\n{parsed_text}" if text else parsed_text). Items
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// without an image (e.g. DOCX tables) are left untouched, exactly as Python
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// skips them via `if item.get("image") is None: continue`.
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//
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// The markdown output path receives no vision enrichment — Python's DOCX
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// markdown branch only concatenates text and never calls the vision model.
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func maybeDispatchDOCXVision(
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ctx context.Context,
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fileType utility.FileType,
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dispatched parserDispatchResult,
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inputs map[string]any,
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setups map[string]schema.ParserSetup,
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) (parserDispatchResult, bool, error) {
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if fileType != utility.FileTypeDOCX {
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return dispatched, false, nil
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}
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// Python triggers vision enrichment only on the JSON path
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// (parser.py:_doc → enhance_media_sections_with_vision).
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if dispatched.Err != nil || dispatched.OutputFormat != "json" || len(dispatched.JSON) == 0 {
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return dispatched, false, nil
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}
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tenantID := getStringOr(inputs, "tenant_id", "")
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if tenantID == "" {
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return dispatched, false, nil
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}
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// Resolve the tenant's IMAGE2TEXT model.
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driver, modelName, apiConfig, _, err := resolveTenantModelByType(tenantID, entity.ModelTypeImage2Text)
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if err != nil {
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// Model not available — skip vision enhancement silently,
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// matching Python's try/except pass behaviour.
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return dispatched, false, nil
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}
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// Collect the indices of JSON items that carry an embeddable image.
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type target struct {
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idx int
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}
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var targets []target
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for i, item := range dispatched.JSON {
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kd, _ := item["doc_type_kwd"].(string)
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if kd != "image" && kd != "table" {
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continue
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}
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img, _ := item["image"].(string)
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if img == "" {
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continue
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}
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targets = append(targets, target{idx: i})
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}
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if len(targets) == 0 {
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return dispatched, false, nil
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}
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descriptions := make([]string, len(targets))
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var wg sync.WaitGroup
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sem := make(chan struct{}, docxVisionConcurrency)
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for slot, tg := range targets {
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wg.Add(1)
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go func(slot int, itemIdx int) {
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defer wg.Done()
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sem <- struct{}{}
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defer func() { <-sem }()
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img, _ := dispatched.JSON[itemIdx]["image"].(string)
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if img == "" {
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return
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}
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// DOCX JSON items have no surrounding context (unlike the
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// former markdown path), so use the bare figure prompt —
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// matching Python's VisionFigureParser(context_size=0).
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prompt, perr := docxVisionPromptBuilder("", "")
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if perr != nil {
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return
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}
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messages := buildVisionMessages(prompt, img)
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resp, ierr := visionChatInvoker(ctx, driver, modelName, messages, apiConfig)
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if ierr != nil {
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return
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}
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descriptions[slot] = extractDOCXVisionAnswer(resp)
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}(slot, tg.idx)
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}
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wg.Wait()
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modified := false
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for slot, tg := range targets {
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desc := strings.TrimSpace(descriptions[slot])
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if desc == "" {
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continue
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}
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existing, _ := dispatched.JSON[tg.idx]["text"].(string)
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if existing != "" {
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dispatched.JSON[tg.idx]["text"] = existing + "\n" + desc
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} else {
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dispatched.JSON[tg.idx]["text"] = desc
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}
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modified = true
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}
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return dispatched, modified, nil
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}
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// buildDOCXVisionPrompt loads the figure-describe prompt template
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// and, when context text is available, renders it with the
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// with-context variant. Mirrors Python:
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//
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// if context_above or context_below:
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// prompt = vision_llm_figure_describe_prompt_with_context(context_above, context_below)
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// else:
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// prompt = vision_llm_figure_describe_prompt()
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func buildDOCXVisionPrompt(contextAbove, contextBelow string) (string, error) {
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hasContext := strings.TrimSpace(contextAbove) != "" || strings.TrimSpace(contextBelow) != ""
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var templateName string
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if hasContext {
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templateName = docxVisionPromptWithContextFile
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} else {
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templateName = docxVisionPromptFile
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}
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template, err := loadDOCXVisionPromptFile(templateName)
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if err != nil {
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return "", err
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}
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if hasContext {
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template = strings.ReplaceAll(template, "{{ context_above }}", contextAbove)
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template = strings.ReplaceAll(template, "{{ context_below }}", contextBelow)
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}
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return template, nil
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}
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func loadDOCXVisionPromptFile(filename string) (string, error) {
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docxVisionPromptMu.RLock()
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if cached, ok := docxVisionPromptCache[filename]; ok {
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docxVisionPromptMu.RUnlock()
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return cached, nil
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}
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docxVisionPromptMu.RUnlock()
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baseDir, err := docxVisionPromptsBaseDir()
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if err != nil {
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return "", err
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}
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promptPath := filepath.Join(baseDir, "rag", "prompts", filename)
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content, err := os.ReadFile(promptPath)
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if err != nil {
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return "", fmt.Errorf("docx vision prompt %q: %w", filename, err)
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}
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cached := strings.TrimSpace(string(content))
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docxVisionPromptMu.Lock()
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docxVisionPromptCache[filename] = cached
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docxVisionPromptMu.Unlock()
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return cached, nil
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}
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func docxVisionPromptsBaseDir() (string, error) {
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var initErr error
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docxVisionPromptsOnce.Do(func() {
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root := utility.GetProjectRoot()
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if _, statErr := os.Stat(filepath.Join(root, "rag", "prompts")); statErr == nil {
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docxVisionPromptsBase = root
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return
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}
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initErr = fmt.Errorf("rag/prompts not found under project root %q", root)
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})
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if initErr != nil {
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return "", initErr
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}
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return docxVisionPromptsBase, nil
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}
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func buildVisionMessages(prompt, imageBase64 string) []modelModule.Message {
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dataURI := "data:image/png;base64," + imageBase64
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return []modelModule.Message{{
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Role: "user",
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Content: []interface{}{
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map[string]any{"type": "text", "text": prompt},
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map[string]any{"type": "image_url", "image_url": map[string]any{"url": dataURI}},
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},
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}}
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}
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func extractDOCXVisionAnswer(resp *modelModule.ChatResponse) string {
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if resp == nil || resp.Answer == nil {
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return ""
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}
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return strings.TrimSpace(*resp.Answer)
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}
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func defaultVisionChatInvoker(
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ctx context.Context,
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driver modelModule.ModelDriver,
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modelName string,
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messages []modelModule.Message,
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apiConfig *modelModule.APIConfig,
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) (*modelModule.ChatResponse, error) {
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vision := true
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return driver.ChatWithMessages(ctx, modelName, messages, apiConfig, &modelModule.ChatConfig{Vision: &vision}, nil)
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}
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