mirror of
https://github.com/arc53/DocsGPT
synced 2024-11-03 23:15:37 +00:00
124 lines
5.5 KiB
Python
124 lines
5.5 KiB
Python
import os
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import sys
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import nltk
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import dotenv
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import typer
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from collections import defaultdict
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from typing import List, Optional
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from parser.file.bulk import SimpleDirectoryReader
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from parser.schema.base import Document
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from parser.open_ai_func import call_openai_api, get_user_permission
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from parser.py2doc import transform_to_docs
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from parser.py2doc import extract_functions_and_classes as extract_py
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from parser.js2doc import extract_functions_and_classes as extract_js
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from parser.java2doc import extract_functions_and_classes as extract_java
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from parser.token_func import group_split
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dotenv.load_dotenv()
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app = typer.Typer(add_completion=False)
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nltk.download('punkt', quiet=True)
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nltk.download('averaged_perceptron_tagger', quiet=True)
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#Splits all files in specified folder to documents
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@app.command()
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def ingest(yes: bool = typer.Option(False, "-y", "--yes", prompt=False,
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help="Whether to skip price confirmation"),
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dir: Optional[List[str]] = typer.Option(["inputs"],
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help="""List of paths to directory for index creation.
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E.g. --dir inputs --dir inputs2"""),
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file: Optional[List[str]] = typer.Option(None,
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help="""File paths to use (Optional; overrides dir).
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E.g. --file inputs/1.md --file inputs/2.md"""),
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recursive: Optional[bool] = typer.Option(True, help="Whether to recursively search in subdirectories."),
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limit: Optional[int] = typer.Option(None, help="Maximum number of files to read."),
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formats: Optional[List[str]] = typer.Option([".rst", ".md"],
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help="""List of required extensions (list with .)
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Currently supported: .rst, .md, .pdf, .docx, .csv, .epub, .html, .mdx"""),
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exclude: Optional[bool] = typer.Option(True, help="Whether to exclude hidden files (dotfiles)."),
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sample: Optional[bool] = typer.Option(False, help="Whether to output sample of the first 5 split documents."),
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token_check: Optional[bool] = typer.Option(True, help="Whether to group small documents and split large."),
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min_tokens: Optional[int] = typer.Option(150, help="Minimum number of tokens to not group."),
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max_tokens: Optional[int] = typer.Option(2000, help="Maximum number of tokens to not split."),
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):
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"""
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Creates index from specified location or files.
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By default /inputs folder is used, .rst and .md are parsed.
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"""
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def process_one_docs(directory, folder_name):
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raw_docs = SimpleDirectoryReader(input_dir=directory, input_files=file, recursive=recursive,
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required_exts=formats, num_files_limit=limit,
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exclude_hidden=exclude).load_data()
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# Here we split the documents, as needed, into smaller chunks.
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# We do this due to the context limits of the LLMs.
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raw_docs = group_split(documents=raw_docs, min_tokens=min_tokens, max_tokens=max_tokens, token_check=token_check)
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#Old method
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# text_splitter = RecursiveCharacterTextSplitter()
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# docs = text_splitter.split_documents(raw_docs)
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#Sample feature
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if sample == True:
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for i in range(min(5, len(raw_docs))):
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print(raw_docs[i].text)
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docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
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# Here we check for command line arguments for bot calls.
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# If no argument exists or the yes is not True, then the
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# user permission is requested to call the API.
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if len(sys.argv) > 1:
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if yes:
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call_openai_api(docs, folder_name)
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else:
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get_user_permission(docs, folder_name)
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else:
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get_user_permission(docs, folder_name)
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folder_counts = defaultdict(int)
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folder_names = []
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for dir_path in dir:
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folder_name = os.path.basename(os.path.normpath(dir_path))
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folder_counts[folder_name] += 1
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if folder_counts[folder_name] > 1:
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folder_name = f"{folder_name}_{folder_counts[folder_name]}"
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folder_names.append(folder_name)
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for directory, folder_name in zip(dir, folder_names):
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process_one_docs(directory, folder_name)
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@app.command()
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def convert(dir: Optional[str] = typer.Option("inputs",
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help="""Path to directory to make documentation for.
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E.g. --dir inputs """),
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formats: Optional[str] = typer.Option("py",
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help="""Required language.
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py, js, java supported for now""")):
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"""
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Creates documentation linked to original functions from specified location.
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By default /inputs folder is used, .py is parsed.
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"""
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if formats == 'py':
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functions_dict, classes_dict = extract_py(dir)
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elif formats == 'js':
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functions_dict, classes_dict = extract_js(dir)
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elif formats == 'java':
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functions_dict, classes_dict = extract_java(dir)
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else:
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raise Exception("Sorry, language not supported yet")
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transform_to_docs(functions_dict, classes_dict, formats, dir)
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if __name__ == "__main__":
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app()
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