111 lines
4 KiB
Python
111 lines
4 KiB
Python
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"""
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Script to update documentation for a component using AI agent.
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"""
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import sys
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import argparse
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import subprocess
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from pathlib import Path
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from config import AgentConfig
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from cursor_cli_wrapper import CursorCLI, CursorResultStatus
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def main():
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"""Main entry point."""
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parser = argparse.ArgumentParser(description="Update documentation for a component")
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parser.add_argument("component", choices=["web_v2", "backend", "common"], help="Component to document")
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parser.add_argument("--model", default="claude-3-5-sonnet-20241022", help="LLM model to use")
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args = parser.parse_args()
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# Load configuration
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try:
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config = AgentConfig.from_env(args.component)
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# Override model if provided in args (though config loads from env, we want to support CLI override if needed,
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# but here we primarily rely on env vars set by workflow, so we'll stick to config or args)
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# Actually, AgentConfig.from_env reads CURSOR_MODEL.
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# If we pass it via args, we should update it.
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if args.model:
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config.cursor_model = args.model
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except ValueError as e:
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print(f"❌ Configuration error: {e}")
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sys.exit(1)
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print(f"🚀 Starting Documentation Update for: {args.component}")
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print(f"🤖 Model: {config.cursor_model}")
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# Initialize Cursor CLI
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cursor_cli = CursorCLI(
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project_root=config.project_root,
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api_key=config.cursor_api_key,
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model=config.cursor_model,
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verbose=True
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)
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# Define the task
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task_description = f"""
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You are an expert technical writer and software engineer.
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Your task is to update the documentation for the '{args.component}' component.
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1. Analyze the current codebase in '{config.component_root}'.
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2. Check existing documentation in 'ai_docs/{args.component}' and 'README.md' files.
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3. Identify missing or outdated documentation.
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4. Update or create documentation files to reflect the current state of the code.
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- Focus on architecture, API endpoints, setup instructions, and key features.
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- Ensure 'README.md' in the component root is up to date.
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- If there are significant changes, update 'ai_docs/{args.component}/architecture.md' or similar.
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Do NOT modify any code files. ONLY modify markdown documentation files.
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"""
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print("\n📝 Task Description:")
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print(task_description)
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print(f"\n{'='*80}\n")
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# Run agent
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result = cursor_cli.run_agent(
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task_description=task_description,
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force=True,
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max_iterations=5
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)
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if result.status != CursorResultStatus.SUCCESS:
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print(f"\n❌ Documentation update failed: {result.error}")
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sys.exit(1)
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print(f"\n✅ Agent completed successfully")
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print(f" - Files created: {len(result.files_created)}")
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print(f" - Files modified: {len(result.files_modified)}")
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if not result.files_created and not result.files_modified:
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print("\n⚠️ No changes made to documentation.")
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sys.exit(0)
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# Commit changes
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print("\n💾 Committing changes...")
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# Git config
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subprocess.run(["git", "config", "--global", "user.name", "AI Agent"], check=False)
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subprocess.run(["git", "config", "--global", "user.email", "ai-agent@mnemo-cards.com"], check=False)
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# Add changes
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subprocess.run(["git", "add", "."], cwd=config.project_root, check=True)
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# Commit
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commit_msg = f"docs({args.component}): Update documentation via AI Agent\n\nModel: {config.cursor_model}"
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subprocess.run(["git", "commit", "-m", commit_msg], cwd=config.project_root, check=False)
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# Push
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print("\n📤 Pushing changes...")
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# Pull first
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subprocess.run(["git", "pull", "--rebase"], cwd=config.project_root, check=False)
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push_result = subprocess.run(["git", "push"], cwd=config.project_root, check=False)
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if push_result.returncode == 0:
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print("✅ Changes pushed successfully")
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else:
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print("❌ Failed to push changes")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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