#!/usr/bin/env python3
"""
Multi-project manager for merging multiple knowledge-base projects.
"""

import os
import re
import shutil
import json
import logging
import re
from pathlib import Path
from typing import List, Dict, Optional
from datetime import datetime

# Configure logger
logger = logging.getLogger('app')

from utils.file_utils import get_document_preview
from utils import settings


def generate_robot_directory_tree(robot_dir: str, robot_id: str, max_depth: int = 3) -> str:
    """
    Generate the directory tree for a robot project.

    Args:
        robot_dir: Path to the robot project directory
        robot_id: Robot ID
        max_depth: Maximum depth

    Returns:
        str: Directory tree string
    """
    def _build_tree(path: str, prefix: str = "", is_last: bool = True, depth: int = 0) -> List[str]:
        if depth > max_depth:
            return []

        lines = []
        try:
            entries = sorted(os.listdir(path))
            # Separate directories and files
            dirs = [e for e in entries if os.path.isdir(os.path.join(path, e)) and not e.startswith('.')]
            files = [e for e in entries if os.path.isfile(os.path.join(path, e)) and not e.startswith('.')]

            entries = dirs + files

            for i, entry in enumerate(entries):
                entry_path = os.path.join(path, entry)
                is_dir = os.path.isdir(entry_path)
                is_last_entry = i == len(entries) - 1

                # Choose the appropriate tree connector
                if is_last_entry:
                    connector = "└── "
                    new_prefix = prefix + "    "
                else:
                    connector = "├── "
                    new_prefix = prefix + "│   "

                # Add the entry line
                line = prefix + connector + entry
                if is_dir:
                    line += "/"
                lines.append(line)

                # Recursively add subdirectories
                if is_dir and depth < max_depth:
                    sub_lines = _build_tree(entry_path, new_prefix, is_last_entry, depth + 1)
                    lines.extend(sub_lines)

        except PermissionError:
            lines.append(prefix + "└── [Permission Denied]")
        except Exception as e:
            lines.append(prefix + "└── [Error: " + str(e) + "]")

        return lines

    # Build the tree starting from the datasets directory
    dataset_dir = os.path.join(robot_dir, "datasets")
    tree_lines = []

    if not os.path.exists(dataset_dir):
        return "└── [No dataset directory found]"

    try:
        entries = sorted(os.listdir(dataset_dir))
        dirs = [e for e in entries if os.path.isdir(os.path.join(dataset_dir, e)) and not e.startswith('.')]
        files = [e for e in entries if os.path.isfile(os.path.join(dataset_dir, e)) and not e.startswith('.')]

        entries = dirs + files

        if not entries:
            tree_lines.append("└── [Empty dataset directory]")
        else:
            for i, entry in enumerate(entries):
                entry_path = os.path.join(dataset_dir, entry)
                is_dir = os.path.isdir(entry_path)
                is_last_entry = i == len(entries) - 1

                if is_last_entry:
                    connector = "└── "
                    prefix = "    "
                else:
                    connector = "├── "
                    prefix = "│   "

                line = connector + entry
                if is_dir:
                    line += "/"
                tree_lines.append(line)

                # Recursively add subdirectories
                if is_dir:
                    sub_lines = _build_tree(entry_path, prefix, is_last_entry, 1)
                    tree_lines.extend(sub_lines)

    except Exception as e:
        tree_lines.append(f"└── [Error generating tree: {str(e)}]")

    return "\n".join(tree_lines)


def get_unique_folder_name(target_dir: Path, original_name: str) -> str:
    """
    Get a unique folder name by appending a numeric suffix when needed.

    Args:
        target_dir: Target directory
        original_name: Original folder name

    Returns:
        str: Unique folder name
    """
    if not (target_dir / original_name).exists():
        return original_name

    # Add a numeric suffix when a name collision exists
    counter = 1
    while True:
        new_name = f"{original_name}_{counter}"
        if not (target_dir / new_name).exists():
            return new_name
        counter += 1


def copy_dataset_folder(source_project_id: str, target_dataset_dir: Path, folder_name: str, project_path: Path) -> Dict:
    """
    Copy a single project's dataset folder to the target directory.

    Args:
        source_project_id: Source project ID
        target_dataset_dir: Target datasets directory
        folder_name: Folder name to copy
        project_path: Project path

    Returns:
        Dict: Copy result
    """
    result = {
        "success": False,
        "source_path": "",
        "target_path": "",
        "original_folder_name": folder_name,
        "final_folder_name": folder_name,
        "error": None
    }

    try:
        source_folder = project_path / "data" / source_project_id / "datasets" / folder_name
        result["source_path"] = str(source_folder)

        if not source_folder.exists():
            result["error"] = f"Source folder does not exist: {source_folder}"
            return result

        # Handle name collisions
        unique_folder_name = get_unique_folder_name(target_dataset_dir, folder_name)
        result["final_folder_name"] = unique_folder_name

        target_folder = target_dataset_dir / unique_folder_name
        result["target_path"] = str(target_folder)

        # Copy the folder
        shutil.copytree(source_folder, target_folder)
        result["success"] = True

        logger.info(f"  Copied: {source_folder} -> {target_folder}")

    except Exception as e:
        result["error"] = str(e)
        logger.error(f"  Error copying {folder_name}: {str(e)}")

    return result


def generate_robot_readme(robot_id: str, dataset_ids: List[str], copy_results: List[Dict], project_path: Path) -> str:
    """
    Generate the README.md file for a robot project.

    Args:
        robot_id: Robot ID
        dataset_ids: List of source project IDs
        copy_results: List of copy results

    Returns:
        str: Path to the README.md file
    """
    readme_path = project_path / "robot" / robot_id / "README.md"
    readme_path.parent.mkdir(parents=True, exist_ok=True)

    robot_dir = project_path / "robot" / robot_id

    # Statistics
    total_folders = len(copy_results)
    successful_copies = sum(1 for r in copy_results if r["success"])
    failed_copies = total_folders - successful_copies

    # Group by source project
    project_groups = {}
    for result in copy_results:
        if result["success"]:
            source_project = result["source_path"].split("/")[2]  # projects/data/{project_id}/dataset/...
            if source_project not in project_groups:
                project_groups[source_project] = []
            project_groups[source_project].append(result)

    readme_content = "\n## Directory Structure\n\n"
    # Generate the actual directory tree
    readme_content += "```\n"
    readme_content += generate_robot_directory_tree(str(robot_dir), robot_id)
    readme_content += "\n```\n\n"

    readme_content += "## Dataset Details\n\n"

    dataset_dir = robot_dir / "datasets"
    if not dataset_dir.exists():
        readme_content += "No dataset files available.\n"
    else:
        # Get all document directories
        doc_dirs = []
        try:
            for item in sorted(os.listdir(dataset_dir)):
                item_path = dataset_dir / item
                if item_path.is_dir():
                    doc_dirs.append(item)
        except Exception as e:
            logger.error(f"Error listing dataset directories: {str(e)}")

        if not doc_dirs:
            readme_content += "No document directories found.\n"
        else:
            # Display documents grouped by source project
            for project_id, folders in project_groups.items():
                for folder in folders:
                    folder_name = folder["final_folder_name"]
                    doc_path = dataset_dir / folder_name

                    readme_content += f"#### {folder_name}\n\n"
                    readme_content += f"**Files:**\n"

                    # Check file existence
                    document_file = doc_path / "document.txt"
                    pagination_file = doc_path / "pagination.txt"
                    embeddings_file = doc_path / "embedding.pkl"

                    readme_content += f"- `{folder_name}/document.txt`"
                    if document_file.exists():
                        readme_content += " ✓"
                    readme_content += "\n"

                    readme_content += f"- `{folder_name}/pagination.txt`"
                    if pagination_file.exists():
                        readme_content += " ✓"
                    readme_content += "\n"

                    readme_content += f"- `{folder_name}/embedding.pkl`"
                    if embeddings_file.exists():
                        readme_content += " ✓"
                    readme_content += "\n\n"

                    # Add document preview
                    if document_file.exists():
                        readme_content += f"**Content Preview (first 10 lines):**\n\n```\n"
                        preview = get_document_preview(str(document_file), 10)
                        readme_content += preview
                        readme_content += "\n```\n\n"
                    else:
                        readme_content += f"**Content Preview:** Not available\n\n"

                    # Show rename information
                    original_name = folder["original_folder_name"]
                    if original_name != folder_name:
                        readme_content += f"**Original Name:** `{original_name}` → `{folder_name}`\n\n"

                    readme_content += "---\n\n"

    # Write the README file
    with open(readme_path, 'w', encoding='utf-8') as f:
        f.write(readme_content)

    logger.info(f"Generated README: {readme_path}")
    return str(readme_path)


def _get_robot_dir(project_path: Path, bot_id: str) -> Path:
    return project_path / "robot" / bot_id


def create_robot_project(dataset_ids: List[str], bot_id: str, force_rebuild: bool = False, project_path: Path = Path("projects"), skills: Optional[List[str]] = None) -> str:
    """
    Ensure the robot project directory exists without rebuilding it.

    Args:
        dataset_ids: List of source project IDs, deprecated and kept for compatibility
        bot_id: Robot ID
        force_rebuild: Ignored and kept for compatibility
        skills: List of skill filenames

    Returns:
        str: Robot project directory path
    """

    def _skill_matches_autoload(skill: str, autoload_skill_name: str) -> bool:
        normalized_skill = Path(skill.lstrip("@")).name.lower()
        normalized_autoload_skill_name = autoload_skill_name.lower()
        if re.search(re.escape(normalized_autoload_skill_name), normalized_skill):
            return True
        autoload_prefix = normalized_autoload_skill_name.split("-")[0]
        return bool(autoload_prefix and re.search(re.escape(autoload_prefix), normalized_skill))

    skills = list(skills or [])
    if os.path.isabs(settings.SKILLS_DIR):
        autoload_skills_dir = Path(settings.SKILLS_DIR) / "autoload" / settings.PROJECT_NAME
    else:
        autoload_skills_dir = project_path.parent / settings.SKILLS_DIR / "autoload" / settings.PROJECT_NAME

    if autoload_skills_dir.exists():
        for item in sorted(autoload_skills_dir.iterdir()):
            if not item.is_dir() or any(_skill_matches_autoload(skill, item.name) for skill in skills):
                continue
            skill_path = f"@skills/autoload/{settings.PROJECT_NAME}/{item.name}"
            skills.append(skill_path)
            logger.info(f"Auto loaded skill '{skill_path}' from {autoload_skills_dir}")
    else:
        logger.warning(f"Autoload skills directory does not exist: {autoload_skills_dir}")


    logger.info(f"Ensuring robot project exists: {bot_id}, skills: {skills}")

    # Create the robot directory structure if it does not exist
    robot_dir = _get_robot_dir(project_path, bot_id)
    dataset_dir = robot_dir / "datasets"
    scripts_dir = robot_dir / "scripts"
    download_dir = robot_dir / "download"

    # Create directories without deleting existing content
    robot_dir.mkdir(parents=True, exist_ok=True)
    dataset_dir.mkdir(parents=True, exist_ok=True)
    scripts_dir.mkdir(parents=True, exist_ok=True)
    download_dir.mkdir(parents=True, exist_ok=True)

    # Remove all symlinks under dataset_dir
    for item in dataset_dir.iterdir():
        if item.is_symlink():
            item.unlink()
            logger.info(f"Removed from dataset_dir: {item}")

    # Create symlinks for dataset_ids
    docs_datasets_dir = project_path / "docs" / "datasets"
    for dataset_id in dataset_ids:
        source = docs_datasets_dir / dataset_id
        target = dataset_dir / dataset_id
        if source.exists():
            os.symlink(source.resolve(), target)
            logger.info(f"Created symlink: {target} -> {source.resolve()}")
        else:
            logger.warning(f"Dataset source not found, skipping symlink: {source}")

    # Process skills and keep them updated each time
    if skills:
        _extract_skills_to_robot(bot_id, skills, project_path)

    logger.info(f"Robot project ready: {robot_dir}")
    return str(robot_dir)


if __name__ == "__main__":
    # Test code
    test_dataset_ids = ["test-project-1", "test-project-2"]
    test_bot_id = "test-robot-001"

    robot_dir = create_robot_project(test_dataset_ids, test_bot_id)
    logger.info(f"Created robot project at: {robot_dir}")


def _extract_skills_to_robot(bot_id: str, skills: List[str], project_path: Path) -> None:
    """
    Copy skills into the robot project's skills directory.
    - If a full path is provided (for example "projects/uploads/xxx/skills/rag-retrieve_2.zip"), use it directly
    - If a simple name is provided (for example "rag-retrieve"), search in this priority order:
      1. projects/uploads/{bot_id}/skills/
      2. skills/{PROJECT_NAME}/
    - If a repository-relative path starting with @ is provided
      (for example "@skills/autoload/support/rag-retrieve"), resolve it directly from the repo root

    Search priority for skill directories: first projects/uploads/{bot_id}/skills/, then skills/common,
    and finally skills/{PROJECT_NAME}

    Args:
        bot_id: Robot ID
        skills: List of skill filenames (for example ["rag-retrieve", "@skills/autoload/support/rag-retrieve", "projects/uploads/{bot_id}/skills/rag-retrieve"])
        project_path: Project path
    """
    # Skill source directories in priority order
    repo_root = Path(__file__).resolve().parent.parent
    official_skills_dir = repo_root / "skills" / settings.PROJECT_NAME
    autoload_skills_dir = repo_root / "skills" / "autoload" / settings.PROJECT_NAME
    if not official_skills_dir.exists():
        logger.warning(f"Official skills directory does not exist: {official_skills_dir}")
    skills_source_dirs = [
        project_path / "uploads" / bot_id / "skills",
        repo_root / "skills" / "common",
        official_skills_dir,
    ]
    managed_skill_dirs = [*skills_source_dirs, autoload_skills_dir]
    skills_target_dir = project_path / "robot" / bot_id / "skills"
    skills_target_dir.mkdir(parents=True, exist_ok=True)
    logger.info(f"Copying skills to {skills_target_dir}")

    managed_skill_names = set()
    for base_dir in managed_skill_dirs:
        if not base_dir.exists():
            continue
        for item in base_dir.iterdir():
            if item.is_dir():
                managed_skill_names.add(item.name)

    # Remove extra managed skill directories that are no longer expected
    expected_skill_names = {Path(skill.lstrip("@")).name for skill in skills}
    if skills_target_dir.exists():
        for item in skills_target_dir.iterdir():
            if not item.is_dir() or item.name in expected_skill_names:
                continue
            if item.name in managed_skill_names:
                logger.info(f"  Removing managed stale skill directory: {item}")
                shutil.rmtree(item)
            else:
                logger.info(f"  Keeping unmanaged skill directory: {item}")

    for skill in skills:
        skill_name = Path(skill.lstrip("@")).name
        target_dir = skills_target_dir / skill_name

        source_dir = None

        if skill.startswith("@"):
            candidate_dir = repo_root / skill.lstrip("@")
            if candidate_dir.exists():
                source_dir = candidate_dir
                logger.info(f"  Found skill '{skill}' at {candidate_dir}")

        # For simple names, search multiple directories in priority order
        if source_dir is None:
            for base_dir in skills_source_dirs:
                candidate_dir = base_dir / skill
                if candidate_dir.exists():
                    source_dir = candidate_dir
                    logger.info(f"  Found skill '{skill}' in {base_dir}")
                    break

        if source_dir is None:
            logger.warning(f"  Skill directory '{skill}' not found in any source directory: {[str(d) for d in skills_source_dirs]}")
            continue

        try:
            shutil.copytree(source_dir, target_dir, dirs_exist_ok=True)
            logger.info(f"  Synced: {source_dir} -> {target_dir}")
        except Exception as e:
            logger.error(f"  Failed to copy {source_dir}: {e}")


_COMMON_ENV_KEYS = frozenset({
    'TMPDIR', 'PATH', 'HOME', 'USER', 'SHELL', 'LANG', 'TERM',
    'PWD', 'OLDPWD', 'NODE_ENV', 'MASTERKEY', 'ASSISTANT_ID', 'USER_IDENTIFIER' , 'TRACE_ID'
})

_ENV_PATTERNS = [
    re.compile(r'process\.env\.(\w+)'),
    re.compile(r'os\.getenv\([\'"](\w+)'),
    re.compile(r'os\.environ\.get\([\'"](\w+)'),
    re.compile(r'os\.environ\[[\'"](\w+)'),
]

_SCAN_EXTENSIONS = {'.js', '.py', '.ts', '.sh', '.md', '.jsx', '.tsx', '.mjs', '.cjs'}


def scan_skill_env_keys(bot_id: str, skills: List[str], project_path: Path) -> set:
    """
    扫描 skills 目录下所有文件，提取引用的环境变量 KEY。

    Args:
        bot_id: 机器人 ID
        skills: 技能名称列表
        project_path: 项目路径（如 Path("projects")）

    Returns:
        set: 环境变量 KEY 集合（排除通用变量）
    """
    skills_source_dirs = [
        project_path / "uploads" / bot_id / "skills",
        Path("skills"),
    ]

    env_keys = set()

    for skill in skills:
        source_dir = None
        for base_dir in skills_source_dirs:
            candidate = base_dir / skill
            if candidate.exists():
                source_dir = candidate
                break

        if source_dir is None or not source_dir.exists():
            continue

        for file_path in source_dir.rglob('*'):
            if not file_path.is_file():
                continue
            if file_path.suffix.lower() not in _SCAN_EXTENSIONS:
                continue
            try:
                content = file_path.read_text(encoding='utf-8', errors='ignore')
            except Exception:
                continue
            for pattern in _ENV_PATTERNS:
                env_keys.update(pattern.findall(content))

    env_keys -= _COMMON_ENV_KEYS
    return env_keys