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langchain/docs/scripts/notebook_convert.py

176 lines
5.6 KiB
Python

import multiprocessing
import os
import re
import sys
from pathlib import Path
from typing import Iterable, Tuple
import nbformat
from nbconvert.exporters import MarkdownExporter
from nbconvert.preprocessors import Preprocessor
class EscapePreprocessor(Preprocessor):
def preprocess_cell(self, cell, resources, cell_index):
if cell.cell_type == "markdown":
# find all occurrences of ```{=mdx} blocks and remove wrapper
if "```{=mdx}\n" in cell.source:
cell.source = re.sub(
r"```{=mdx}\n(.*?)\n```", r"\1", cell.source, flags=re.DOTALL
)
if ":::{.callout" in cell.source:
cell.source = re.sub(
r":::{.callout-([^}]*)}(.*?):::",
r":::\1\2:::",
cell.source,
flags=re.DOTALL,
)
# rewrite .ipynb links to .md
cell.source = re.sub(
r"\[([^\]]*)\]\((?![^\)]*//)([^)]*)\.ipynb\)",
r"[\1](\2.md)",
cell.source,
)
return cell, resources
class ExtractAttachmentsPreprocessor(Preprocessor):
"""
Extracts all of the outputs from the notebook file. The extracted
outputs are returned in the 'resources' dictionary.
"""
def preprocess_cell(self, cell, resources, cell_index):
"""
Apply a transformation on each cell,
Parameters
----------
cell : NotebookNode cell
Notebook cell being processed
resources : dictionary
Additional resources used in the conversion process. Allows
preprocessors to pass variables into the Jinja engine.
cell_index : int
Index of the cell being processed (see base.py)
"""
# Get files directory if it has been specified
# Make sure outputs key exists
if not isinstance(resources["outputs"], dict):
resources["outputs"] = {}
# Loop through all of the attachments in the cell
for name, attach in cell.get("attachments", {}).items():
for mime, data in attach.items():
if mime not in {
"image/png",
"image/jpeg",
"image/svg+xml",
"application/pdf",
}:
continue
# attachments are pre-rendered. Only replace markdown-formatted
# images with the following logic
attach_str = f"({name})"
if attach_str in cell.source:
data = f"(data:{mime};base64,{data})"
cell.source = cell.source.replace(attach_str, data)
return cell, resources
class CustomRegexRemovePreprocessor(Preprocessor):
def check_conditions(self, cell):
pattern = re.compile(r"(?s)(?:\s*\Z)|(?:.*#\s*\|\s*output:\s*false.*)")
rtn = not pattern.match(cell.source)
if not rtn:
return False
else:
return True
def preprocess(self, nb, resources):
nb.cells = [cell for cell in nb.cells if self.check_conditions(cell)]
return nb, resources
exporter = MarkdownExporter(
preprocessors=[
EscapePreprocessor,
ExtractAttachmentsPreprocessor,
CustomRegexRemovePreprocessor,
],
template_name="mdoutput",
extra_template_basedirs=["./scripts/notebook_convert_templates"],
)
def _process_path(tup: Tuple[Path, Path, Path]):
notebook_path, intermediate_docs_dir, output_docs_dir = tup
relative = notebook_path.relative_to(intermediate_docs_dir)
output_path = output_docs_dir / relative.parent / (relative.stem + ".md")
_convert_notebook(notebook_path, output_path, intermediate_docs_dir)
def _modify_frontmatter(
body: str, notebook_path: Path, intermediate_docs_dir: Path
) -> str:
# if frontmatter exists
rel_path = notebook_path.relative_to(intermediate_docs_dir).as_posix()
edit_url = (
f"https://github.com/langchain-ai/langchain/edit/master/docs/docs/{rel_path}"
)
if re.match(r"^[\s\n]*---\n", body):
# if custom_edit_url already exists, leave it
if re.match(r"custom_edit_url: ", body):
return body
else:
return re.sub(
r"^[\s\n]*---\n", f"---\ncustom_edit_url: {edit_url}\n", body, count=1
)
else:
return f"---\ncustom_edit_url: {edit_url}\n---\n{body}"
def _convert_notebook(
notebook_path: Path, output_path: Path, intermediate_docs_dir: Path
) -> Path:
with open(notebook_path) as f:
nb = nbformat.read(f, as_version=4)
body, resources = exporter.from_notebook_node(nb)
body = _modify_frontmatter(body, notebook_path, intermediate_docs_dir)
output_path.parent.mkdir(parents=True, exist_ok=True)
with open(output_path, "w") as f:
f.write(body)
return output_path
if __name__ == "__main__":
intermediate_docs_dir = Path(sys.argv[1])
output_docs_dir = Path(sys.argv[2])
source_paths_arg = os.environ.get("SOURCE_PATHS")
source_paths: Iterable[Path]
if source_paths_arg:
source_path_strs = re.split(r"\s+", source_paths_arg)
source_paths_stripped = [p.strip() for p in source_path_strs]
source_paths = [intermediate_docs_dir / p for p in source_paths_stripped if p]
else:
source_paths = intermediate_docs_dir.glob("**/*.ipynb")
with multiprocessing.Pool() as pool:
pool.map(
_process_path,
(
(notebook_path, intermediate_docs_dir, output_docs_dir)
for notebook_path in source_paths
),
)