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import dotenv

import os

import argparse

# Import the function that creates the flow

from flow import create_tutorial_flow

dotenv.load_dotenv()

# Default file patterns

DEFAULT_INCLUDE_PATTERNS = {

"*.py", "*.js", "*.jsx", "*.ts", "*.tsx", "*.go", "*.java", "*.pyi", "*.pyx",

"*.c", "*.cc", "*.cpp", "*.h", "*.md", "*.rst", "Dockerfile",

"Makefile", "*.yaml", "*.yml",

}

DEFAULT_EXCLUDE_PATTERNS = {

"assets/*", "data/*", "examples/*", "images/*", "public/*", "static/*", "temp/*",

"docs/*",

"venv/*", ".venv/*", "*test*", "tests/*", "docs/*", "examples/*", "v1/*",

"dist/*", "build/*", "experimental/*", "deprecated/*", "misc/*",

"legacy/*", ".git/*", ".github/*", ".next/*", ".vscode/*", "obj/*", "bin/*", "node_modules/*", "*.log"

}

# --- Main Function ---

def main():

parser = argparse.ArgumentParser(description="Generate a tutorial for a GitHub codebase or local directory.")

# Create mutually exclusive group for source

source_group = parser.add_mutually_exclusive_group(required=True)

source_group.add_argument("--repo", help="URL of the public GitHub repository.")

source_group.add_argument("--dir", help="Path to local directory.")

parser.add_argument("-n", "--name", help="Project name (optional, derived from repo/directory if omitted).")

parser.add_argument("-t", "--token", help="GitHub personal access token (optional, reads from GITHUB_TOKEN env var if not provided).")

parser.add_argument("-o", "--output", default="output", help="Base directory for output (default: ./output).")

parser.add_argument("-i", "--include", nargs="+", help="Include file patterns (e.g. '*.py' '*.js'). Defaults to common code files if not specified.")

parser.add_argument("-e", "--exclude", nargs="+", help="Exclude file patterns (e.g. 'tests/*' 'docs/*'). Defaults to test/build directories if not specified.")

parser.add_argument("-s", "--max-size", type=int, default=100000, help="Maximum file size in bytes (default: 100000, about 100KB).")

# Add language parameter for multi-language support

parser.add_argument("--language", default="english", help="Language for the generated tutorial (default: english)")

# Add use_cache parameter to control LLM caching

parser.add_argument("--no-cache", action="store_true", help="Disable LLM response caching (default: caching enabled)")

# Add max_abstraction_num parameter to control the number of abstractions

parser.add_argument("--max-abstractions", type=int, default=10, help="Maximum number of abstractions to identify (default: 10)")

args = parser.parse_args()

# Get GitHub token from argument or environment variable if using repo

github_token = None

if args.repo:

github_token = args.token or os.environ.get('GITHUB_TOKEN')

if not github_token:

print("Warning: No GitHub token provided. You might hit rate limits for public repositories.")

# Initialize the shared dictionary with inputs

shared = {

"repo_url": args.repo,

"local_dir": args.dir,

"project_name": args.name, # Can be None, FetchRepo will derive it

"github_token": github_token,

"output_dir": args.output, # Base directory for CombineTutorial output

# Add include/exclude patterns and max file size

"include_patterns": set(args.include) if args.include else DEFAULT_INCLUDE_PATTERNS,

"exclude_patterns": set(args.exclude) if args.exclude else DEFAULT_EXCLUDE_PATTERNS,

"max_file_size": args.max_size,

# Add language for multi-language support

"language": args.language,

# Add use_cache flag (inverse of no-cache flag)

"use_cache": not args.no_cache,

# Add max_abstraction_num parameter

"max_abstraction_num": args.max_abstractions,

# Outputs will be populated by the nodes

"files": [],

"abstractions": [],

"relationships": {},

"chapter_order": [],

"chapters": [],

"final_output_dir": None

}

# Display starting message with repository/directory and language

print(f"Starting tutorial generation for: {args.repo or args.dir} in {args.language.capitalize()} language")

print(f"LLM caching: {'Disabled' if args.no_cache else 'Enabled'}")

# Create the flow instance

tutorial_flow = create_tutorial_flow()

# Run the flow

tutorial_flow.run(shared)

if __name__ == "__main__":

main()