#!/usr/bin/env python3
"""
instruction_generation unified entry script
Supports --mode summarize|parse|all
"""

import os
import sys
import asyncio
import argparse
from pathlib import Path
from dotenv import load_dotenv

# Load .env file (before importing logger)
env_file = Path(__file__).parent / ".env"
if env_file.exists():
    load_dotenv(env_file)
elif (Path(__file__).parent.parent / ".env").exists():
    # If not in current directory, try loading from project root
    load_dotenv(Path(__file__).parent.parent / ".env")

# Add current directory to path (for importing local modules)
sys.path.insert(0, str(Path(__file__).parent))
# Add domain_code/src to path for reusing util functions
sys.path.insert(0, str(Path(__file__).parent.parent / "domain_code" / "src"))
from util import init_logger, logger


# Import modules
from summarize_repo_readme import process_all_repos as process_summarize
from extract_repo_functions import process_all_repos as process_extract


async def main():
    """Main function"""
    parser = argparse.ArgumentParser(
        description="instruction_generation unified entry tool",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
  # Full pipeline: summarize README first, then parse functions
  python3 pipeline.py --mode all

  # Summarize README only
  python3 pipeline.py --mode summarize

  # Parse functions only (requires README_SUMMARY.md to exist)
  python3 pipeline.py --mode parse

  # Use local vLLM Qwen (default)
  python3 pipeline.py --mode all

  # Use OpenAI API
  export OPENAI_API_KEY="your-api-key"
  python3 pipeline.py --mode all --base_url https://api.openai.com/v1 --model gpt-4o-mini

  # Specify repository directory and other parameters
  python3 pipeline.py --mode all --repos_dir /path/to/repos_filtered --max_concurrency 16 --overwrite
        """,
    )
    
    # Common parameters
    parser.add_argument(
        "--repos_dir",
        type=str,
        default=os.getenv("REPOS_DIR", "/home/weifengsun/tangou1/domain_code/src/workdir/repos_filtered"),
        help="Repository root directory path (can be read from REPOS_DIR env var)",
    )
    parser.add_argument(
        "--mode",
        type=str,
        choices=["summarize", "parse", "all"],
        default="all",
        help="Execution mode: 'summarize' (README only), 'parse' (functions only), 'all' (full pipeline)",
    )
    
    # LLM parameters
    parser.add_argument(
        "--base_url",
        type=str,
        default=os.getenv("OPENAI_BASE_URL", "http://localhost:8000/v1"),
        help="LLM API base URL (can be read from OPENAI_BASE_URL env var, default: http://localhost:8000/v1)",
    )
    parser.add_argument(
        "--model",
        type=str,
        default=os.getenv("DEFAULT_MODEL", "Qwen3"),
        help="Model name (can be read from DEFAULT_MODEL env var, default: Qwen3)",
    )
    parser.add_argument(
        "--api_key_env",
        type=str,
        default="OPENAI_API_KEY",
        help="API key environment variable name (default: OPENAI_API_KEY)",
    )
    
    # Performance parameters
    parser.add_argument(
        "--max_concurrency",
        type=int,
        default=int(os.getenv("MAX_CONCURRENCY", "8")),
        help="Maximum concurrency (can be read from MAX_CONCURRENCY env var, default: 8)",
    )
    parser.add_argument(
        "--max_file_chars",
        type=int,
        default=int(os.getenv("MAX_FILE_CHARS", "200000")),
        help="Maximum file size (chars, for parse mode only, can be read from MAX_FILE_CHARS env var, default: 200000)",
    )
    
    # Other parameters
    parser.add_argument(
        "--overwrite",
        action="store_true",
        help="Overwrite existing files",
    )
    parser.add_argument(
        "--log_file",
        type=str,
        default="instruction_generation/workdir/logs/pipeline.log",
        help="Log file path",
    )
    
    args = parser.parse_args()
    
    # Initialize logger
    init_logger(args.log_file, level="INFO")
    
    # Get API key (with debug logging)
    # region agent log
    env_key_before = os.getenv(args.api_key_env)
    debug_log_path = Path(__file__).parent.parent / ".cursor" / "debug.log"
    try:
        with open(debug_log_path, "a", encoding="utf-8") as f:
            import json
            log_entry = {
                "sessionId": "debug-session",
                "runId": "api-key-debug",
                "hypothesisId": "A",
                "location": "pipeline.py:130",
                "message": "API key read from env",
                "data": {
                    "env_var_name": args.api_key_env,
                    "key_exists": env_key_before is not None,
                    "key_length": len(env_key_before) if env_key_before else 0,
                    "key_prefix": env_key_before[:20] + "..." if env_key_before and len(env_key_before) > 20 else env_key_before,
                },
                "timestamp": int(__import__("time").time() * 1000)
            }
            f.write(json.dumps(log_entry) + "\n")
    except Exception:
        pass
    # endregion
    
    api_key = os.getenv(args.api_key_env, "none")
    
    # region agent log
    try:
        with open(debug_log_path, "a", encoding="utf-8") as f:
            log_entry = {
                "sessionId": "debug-session",
                "runId": "api-key-debug",
                "hypothesisId": "A",
                "location": "pipeline.py:150",
                "message": "API key final value",
                "data": {
                    "api_key_length": len(api_key) if api_key else 0,
                    "api_key_prefix": api_key[:20] + "..." if api_key and len(api_key) > 20 else api_key,
                    "api_key_suffix": "..." + api_key[-10:] if api_key and len(api_key) > 10 else api_key,
                    "is_default_none": api_key == "none",
                },
                "timestamp": int(__import__("time").time() * 1000)
            }
            f.write(json.dumps(log_entry) + "\n")
    except Exception:
        pass
    # endregion
    
    # Check repository directory
    repos_dir = Path(args.repos_dir)
    if not repos_dir.exists():
        logger.error(f"Repository directory does not exist: {repos_dir}")
        sys.exit(1)
    
    # Create log directory
    log_file_path = Path(args.log_file)
    log_file_path.parent.mkdir(parents=True, exist_ok=True)
    
    logger.info("=" * 80)
    logger.info(f"instruction_generation tool started")
    logger.info("=" * 80)
    logger.info(f"Mode: {args.mode}")
    logger.info(f"Repository directory: {repos_dir}")
    logger.info(f"LLM API: {args.base_url}")
    logger.info(f"Model: {args.model}")
    logger.info(f"Max concurrency: {args.max_concurrency}")
    logger.info(f"Overwrite existing files: {args.overwrite}")
    logger.info("=" * 80)
    
    # Execute based on mode
    if args.mode == "summarize":
        # Summarize README only
        logger.info("Starting: README summarization")
        results = await process_summarize(
            repos_dir=repos_dir,
            base_url=args.base_url,
            model=args.model,
            api_key=api_key,
            log_file=str(log_file_path),
            max_concurrency=args.max_concurrency,
            overwrite=args.overwrite,
        )
        
        logger.info("\n" + "=" * 80)
        logger.info("README summarization complete!")
        logger.info("=" * 80)
        
    elif args.mode == "parse":
        # Parse functions only
        logger.info("Starting: Function parsing")
        results = await process_extract(
            repos_dir=repos_dir,
            base_url=args.base_url,
            model=args.model,
            api_key=api_key,
            log_file=str(log_file_path),
            max_file_chars=args.max_file_chars,
            max_concurrency=args.max_concurrency,
            overwrite=args.overwrite,
        )
        
        logger.info("\n" + "=" * 80)
        logger.info("Function parsing complete!")
        logger.info("=" * 80)
        
    elif args.mode == "all":
        # Full pipeline: summarize README first, then parse functions
        logger.info("Starting: Full pipeline")
        logger.info("\n" + "-" * 80)
        logger.info("Step 1/2: README summarization")
        logger.info("-" * 80)
        
        summarize_results = await process_summarize(
            repos_dir=repos_dir,
            base_url=args.base_url,
            model=args.model,
            api_key=api_key,
            log_file=str(log_file_path),
            max_concurrency=args.max_concurrency,
            overwrite=args.overwrite,
        )
        
        logger.info("\n" + "-" * 80)
        logger.info("Step 2/2: Function parsing")
        logger.info("-" * 80)
        
        # When parsing functions, if README_SUMMARY.md doesn't exist, overwrite=False will auto-skip
        # But if user requests overwrite, it will try to parse even without README_SUMMARY.md (will skip repos without summary)
        parse_results = await process_extract(
            repos_dir=repos_dir,
            base_url=args.base_url,
            model=args.model,
            api_key=api_key,
            log_file=str(log_file_path),
            max_file_chars=args.max_file_chars,
            max_concurrency=args.max_concurrency,
            overwrite=args.overwrite,
        )
        
        logger.info("\n" + "=" * 80)
        logger.info("Full pipeline complete!")
        logger.info("=" * 80)
        
        results = parse_results
    else:
        logger.error(f"Unknown mode: {args.mode}")
        sys.exit(1)
    
    logger.info("\n" + "=" * 80)
    logger.info("All tasks complete!")
    logger.info("=" * 80)


if __name__ == "__main__":
    asyncio.run(main())