"""
Command handling module for Clover - A terminal assistant for AI-powered project management
"""

import os
import sys
from pathlib import Path

# Add the current directory to Python path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from config.settings import load_config
from tools.file_tools import read_file, create_file, update_file, delete_file
from tools.project_tools import summarize_file, get_project_structure, aggregate_summaries
from tools.commandline_tool import commandline, safe_execute
from tools.git_tools import git_status, git_commit, git_push, git_diff
from tools.lint_format_tools import lint_code, format_code

def handle_command(args):
    """
    Handle the parsed CLI arguments and execute corresponding commands
    """
    # Load configuration
    config = load_config()

    try:
        # Check if this is an interactive prompt (not a special command)
        if args.prompt and not args.init and not args.list and not args.timeout and not args.threads:
            # Handle regular prompts - this would invoke the AI assistant
            print("Processing prompt with AI assistant...")
            # In a full implementation, this would connect to an LLM API
            print("Prompt: ", args.prompt)
            print("This is where an AI assistant would process:")
            print("- Creating files")
            print("- Modifying code")
            print("- Running commands")
            print("- Managing project structure")
            print("\n[Note: This is a command line tool, not the full AI interface yet]")

        elif args.init:
            # Handle /init command
            init_project()

        elif args.list:
            # Handle /list command
            list_models()

        elif args.timeout is not None:
            # Handle /timeout command
            set_timeout(args.timeout)

        elif args.threads is not None:
            # Handle /threads command
            set_threads(args.threads)

        elif args.prompt and args.prompt == "/git_status":
            # Handle git status command from interactive mode
            print("Repository Status:")
            result = git_status()
            if "error" in result:
                print(f"Error: {result['error']}")
            else:
                print(f"Staged files: {len(result['staged'])}")
                print(f"Unstaged files: {len(result['unstaged'])}")
                print(f"Untracked files: {len(result['untracked'])}")

        elif args.prompt and args.prompt.startswith("/lint_file "):
            # Handle linting command
            try:
                file_path = args.prompt.split(" ", 2)[2]
                result = lint_code([file_path])
                print(f"Linting results for {file_path}:")
                if "error" in result:
                    print(f"Error: {result['error']}")
                else:
                    print("Return code:", result.get('return_code'))
                    print("Success:", result.get('success'))
            except Exception as e:
                print(f"Error linting file: {e}")

        else:
            # No specific command, just show help for now
            from cli.parser import print_help
            print_help()

    except Exception as e:
        print(f"Error executing command: {e}")
        sys.exit(1)

def init_project():
    """Initialize project with a summary file"""
    try:
        # Create or update clover.md file
        project_summary = """
# Project Summary

This is the project summary file for the Clover CLI tool.
All project information and progress will be tracked here.

## Current Status
- Project initialized
- Basic structure created
- Configuration loaded

## Next Steps
1. Review existing files
2. Define project goals
3. Begin implementation tasks
"""

        with open('clover.md', 'w') as f:
            f.write(project_summary)

        print("Project initialized! Created clover.md file.")

        # Create structure.md if it doesn't exist
        if not os.path.exists('structure.md'):
            # In a real implementation, this would call the LLM to generate structure
            with open('structure.md', 'w') as f:
                f.write("# Project Structure\n\nThis is a placeholder for the project structure generated by LLM.\n")
            print("Created structure.md file.")

    except Exception as e:
        print(f"Error initializing project: {e}")

def list_models():
    """List available models on the server"""
    try:
        # In a real implementation, this would query an OpenAI-compatible API
        print("Available models:")
        print("- gpt-4")
        print("- gpt-3.5-turbo")
        print("- claude-3-opus")
        print("- claude-3-sonnet")
        print("- llama2-70b")
        # Add more mock models as examples
        print("\n[Note: In real implementation, this would query the actual server]")

    except Exception as e:
        print(f"Error listing models: {e}")

def set_timeout(seconds):
    """Set timeout duration for AI operations"""
    try:
        config = load_config()
        config['timeout'] = seconds
        # In a full implementation, save to config file
        print(f"Timeout set to {seconds} seconds")

    except Exception as e:
        print(f"Error setting timeout: {e}")

def set_threads(count):
    """Set maximum number of threads for concurrent operations"""
    try:
        config = load_config()
        config['threads'] = count
        # In a full implementation, save to config file
        print(f"Thread limit set to {count}")

    except Exception as e:
        print(f"Error setting thread limit: {e}")

def execute_command(cmd):
    """Execute a system command with permission prompt"""
    try:
        response = commandline(cmd)
        print(response)
    except Exception as e:
        print(f"Error executing command: {e}")