mirror of
https://github.com/arc53/DocsGPT
synced 2024-11-17 21:26:26 +00:00
112 lines
4.9 KiB
Python
112 lines
4.9 KiB
Python
import os
|
|
import sys
|
|
import nltk
|
|
import dotenv
|
|
import typer
|
|
import ast
|
|
|
|
from collections import defaultdict
|
|
from pathlib import Path
|
|
from typing import List, Optional
|
|
|
|
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
|
|
|
from parser.file.bulk import SimpleDirectoryReader
|
|
from parser.schema.base import Document
|
|
from parser.open_ai_func import call_openai_api, get_user_permission
|
|
from parser.py2doc import transform_to_docs
|
|
from parser.py2doc import extract_functions_and_classes as extract_py
|
|
from parser.js2doc import extract_functions_and_classes as extract_js
|
|
from parser.java2doc import extract_functions_and_classes as extract_java
|
|
|
|
|
|
dotenv.load_dotenv()
|
|
|
|
app = typer.Typer(add_completion=False)
|
|
|
|
nltk.download('punkt', quiet=True)
|
|
nltk.download('averaged_perceptron_tagger', quiet=True)
|
|
|
|
|
|
#Splits all files in specified folder to documents
|
|
@app.command()
|
|
def ingest(yes: bool = typer.Option(False, "-y", "--yes", prompt=False,
|
|
help="Whether to skip price confirmation"),
|
|
dir: Optional[List[str]] = typer.Option(["inputs"],
|
|
help="""List of paths to directory for index creation.
|
|
E.g. --dir inputs --dir inputs2"""),
|
|
file: Optional[List[str]] = typer.Option(None,
|
|
help="""File paths to use (Optional; overrides dir).
|
|
E.g. --file inputs/1.md --file inputs/2.md"""),
|
|
recursive: Optional[bool] = typer.Option(True,
|
|
help="Whether to recursively search in subdirectories."),
|
|
limit: Optional[int] = typer.Option(None,
|
|
help="Maximum number of files to read."),
|
|
formats: Optional[List[str]] = typer.Option([".rst", ".md"],
|
|
help="""List of required extensions (list with .)
|
|
Currently supported: .rst, .md, .pdf, .docx, .csv, .epub, .html"""),
|
|
exclude: Optional[bool] = typer.Option(True, help="Whether to exclude hidden files (dotfiles).")):
|
|
|
|
"""
|
|
Creates index from specified location or files.
|
|
By default /inputs folder is used, .rst and .md are parsed.
|
|
"""
|
|
|
|
def process_one_docs(directory, folder_name):
|
|
raw_docs = SimpleDirectoryReader(input_dir=directory, input_files=file, recursive=recursive,
|
|
required_exts=formats, num_files_limit=limit,
|
|
exclude_hidden=exclude).load_data()
|
|
raw_docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
|
|
# Here we split the documents, as needed, into smaller chunks.
|
|
# We do this due to the context limits of the LLMs.
|
|
text_splitter = RecursiveCharacterTextSplitter()
|
|
docs = text_splitter.split_documents(raw_docs)
|
|
|
|
# Here we check for command line arguments for bot calls.
|
|
# If no argument exists or the yes is not True, then the
|
|
# user permission is requested to call the API.
|
|
if len(sys.argv) > 1:
|
|
if yes:
|
|
call_openai_api(docs, folder_name)
|
|
else:
|
|
get_user_permission(docs, folder_name)
|
|
else:
|
|
get_user_permission(docs, folder_name)
|
|
|
|
folder_counts = defaultdict(int)
|
|
folder_names = []
|
|
for dir_path in dir:
|
|
folder_name = os.path.basename(os.path.normpath(dir_path))
|
|
folder_counts[folder_name] += 1
|
|
if folder_counts[folder_name] > 1:
|
|
folder_name = f"{folder_name}_{folder_counts[folder_name]}"
|
|
folder_names.append(folder_name)
|
|
|
|
for directory, folder_name in zip(dir, folder_names):
|
|
process_one_docs(directory, folder_name)
|
|
|
|
|
|
@app.command()
|
|
def convert(dir: Optional[str] = typer.Option("inputs",
|
|
help="""Path to directory to make documentation for.
|
|
E.g. --dir inputs """),
|
|
formats: Optional[str] = typer.Option("py",
|
|
help="""Required language.
|
|
py, js, java supported for now""")):
|
|
|
|
"""
|
|
Creates documentation linked to original functions from specified location.
|
|
By default /inputs folder is used, .py is parsed.
|
|
"""
|
|
if formats == 'py':
|
|
functions_dict, classes_dict = extract_py(dir)
|
|
elif formats == 'js':
|
|
functions_dict, classes_dict = extract_js(dir)
|
|
elif formats == 'java':
|
|
functions_dict, classes_dict = extract_java(dir)
|
|
else:
|
|
raise Exception("Sorry, language not supported yet")
|
|
transform_to_docs(functions_dict, classes_dict, formats, dir)
|
|
if __name__ == "__main__":
|
|
app()
|