mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-09 11:17:53 +02:00
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@@ -213,41 +213,6 @@ def _get_imports(
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return imports
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class ImportPreprocessor(Preprocessor):
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"""A preprocessor to replace imports in each Python code cell with links to their
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documentation and append the import info in a comment."""
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def preprocess(self, nb, resources):
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self.all_imports = []
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file_name = os.path.basename(resources.get("metadata", {}).get("name", ""))
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_DOC_TITLE = _get_doc_title(nb.cells[0].source, file_name)
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cells = []
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for cell in nb.cells:
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if cell.cell_type == "code":
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cells.append(cell)
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imports = _get_imports(
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cell.source, _DOC_TITLE, "langchain"
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) + _get_imports(cell.source, _DOC_TITLE, "langgraph")
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if not imports:
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continue
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cells.append(
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nbformat.v4.new_markdown_cell(
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source=f"""
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<div>
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<b>API Reference:</b>
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{' | '.join(f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports)}
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</div>
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"""
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)
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)
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else:
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cells.append(cell)
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nb.cells = cells
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return nb, resources
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def get_imports(code: str, doc_title: str) -> List[ImportInformation]:
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"""Retrieve all import references from the given code for specified ecosystems.
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@@ -107,7 +107,6 @@ exporter = MarkdownExporter(
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preprocessors=[
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EscapePreprocessor,
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ExtractAttachmentsPreprocessor,
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ImportPreprocessor,
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],
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template_name="mdoutput",
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extra_template_basedirs=[
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@@ -112,11 +112,9 @@ def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
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if page.file.src_path.endswith(".ipynb"):
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logger.info("Processing Jupyter notebook: %s", page.file.src_path)
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markdown = convert_notebook(page.file.abs_src_path)
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else:
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# Append API reference links to code blocks
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# This logic is already applied for notebooks in `convert_notebook`.
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# We add it here to apply it to regular markdown files.
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markdown = update_markdown_with_imports(markdown)
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# Append API reference links to code blocks
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markdown = update_markdown_with_imports(markdown)
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# Apply highlight comments to code blocks
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markdown = _highlight_code_blocks(markdown)
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return markdown
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