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fix: correct typos in code comments, docstrings and docs (#13931)
## Summary - Fix `a image` → `an image` in README and log message - Fix `colomn` → `column` in table structure recognizer comment - Fix `formated` → `formatted` in confluence connector docstring - Fix `tabel of content` → `table of contents` in TOC prompt ## Test plan - [ ] Documentation and comment changes, no functional impact 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: yuj <yuj@ztjzsoft.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Jin Hai <haijin.chn@gmail.com>
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@@ -920,7 +920,7 @@ def extract_text_from_confluence_html(
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confluence_client (Confluence): Confluence client
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fetched_titles (set[str]): The titles of the pages that have already been fetched
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Returns:
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str: loaded and formated Confluence page
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str: loaded and formatted Confluence page
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"""
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body = confluence_object["body"]
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object_html = body.get("storage", body.get("view", {})).get("value")
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@@ -98,7 +98,7 @@ We use vision information to resolve problems as human being.
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```bash
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python deepdoc/vision/t_recognizer.py --inputs=path_to_images_or_pdfs --threshold=0.2 --mode=tsr --output_dir=path_to_store_result
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```
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The inputs could be directory to images or PDF, or a image or PDF.
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The inputs could be directory to images or PDF, or an image or PDF.
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You can look into the folder 'path_to_store_result' where has both images and html pages which demonstrate the detection results as following:
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<div align="center" style="margin-top:20px;margin-bottom:20px;">
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<img src="https://github.com/infiniflow/ragflow/assets/12318111/cb24e81b-f2ba-49f3-ac09-883d75606f4c" width="1000"/>
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@@ -708,7 +708,7 @@ class RAGFlowPdfParser:
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def __ocr(self, pagenum, img, chars, ZM=3, device_id: int | None = None):
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start = timer()
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bxs = self.ocr.detect(np.array(img), device_id)
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logging.info(f"__ocr detecting boxes of a image cost ({timer() - start}s)")
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logging.info(f"__ocr detecting boxes of an image cost ({timer() - start}s)")
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start = timer()
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if not bxs:
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@@ -394,7 +394,7 @@ class TableStructureRecognizer(Recognizer):
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@staticmethod
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def __desc_table(cap, hdr_rowno, tbl, is_english):
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# get text of every colomn in header row to become header text
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# get text of every column in header row to become header text
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clmno = len(tbl[0])
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rowno = len(tbl)
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headers = {}
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@@ -1,4 +1,4 @@
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You are given a JSON array of TOC(tabel of content) items. Each item has at least {"title": string} and may include an existing title hierarchical level.
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You are given a JSON array of TOC(table of contents) items. Each item has at least {"title": string} and may include an existing title hierarchical level.
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Task
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- For each item, assign a depth label using Arabic numerals only: top-level = 1, second-level = 2, third-level = 3, etc.
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