"""
Hermes Web UI -- Shared configuration, constants, and global state.
Imported by all other api/* modules and by server.py.

Discovery order for all paths:
  1. Explicit environment variable
  2. Filesystem heuristics (sibling checkout, parent dir, common install locations)
  3. Hardened defaults relative to $HOME
  4. Fail loudly with a human-readable fix-it message if required modules are missing
"""
import collections
import json
import os
import sys
import threading
import time
import traceback
import uuid
from pathlib import Path
from urllib.parse import parse_qs, urlparse

# ── Basic layout ──────────────────────────────────────────────────────────────
HOME    = Path.home()
# REPO_ROOT is the directory that contains this file's parent (api/ -> repo root)
REPO_ROOT = Path(__file__).parent.parent.resolve()

# ── Network config (env-overridable) ─────────────────────────────────────────
HOST = os.getenv('HERMES_WEBUI_HOST', '127.0.0.1')
PORT = int(os.getenv('HERMES_WEBUI_PORT', '8787'))

# ── State directory (env-overridable, never inside repo) ──────────────────────
STATE_DIR = Path(os.getenv(
    'HERMES_WEBUI_STATE_DIR',
    str(HOME / '.hermes' / 'webui')
)).expanduser().resolve()

SESSION_DIR           = STATE_DIR / 'sessions'
WORKSPACES_FILE       = STATE_DIR / 'workspaces.json'
SESSION_INDEX_FILE    = SESSION_DIR / '_index.json'
SETTINGS_FILE         = STATE_DIR / 'settings.json'
LAST_WORKSPACE_FILE   = STATE_DIR / 'last_workspace.txt'
PROJECTS_FILE         = STATE_DIR / 'projects.json'

# ── Hermes agent directory discovery ─────────────────────────────────────────
def _discover_agent_dir() -> Path:
    """
    Locate the hermes-agent checkout using a multi-strategy search.

    Priority:
      1. HERMES_WEBUI_AGENT_DIR env var  -- explicit override always wins
      2. HERMES_HOME / hermes-agent      -- e.g. ~/.hermes/hermes-agent
      3. Sibling of this repo            -- ../hermes-agent
      4. Parent of this repo             -- ../../hermes-agent (nested layout)
      5. Common install paths            -- ~/.hermes/hermes-agent (again as fallback)
      6. HOME / hermes-agent             -- ~/hermes-agent (simple flat layout)
    """
    candidates = []

    # 1. Explicit env var
    if os.getenv('HERMES_WEBUI_AGENT_DIR'):
        candidates.append(Path(os.getenv('HERMES_WEBUI_AGENT_DIR')).expanduser().resolve())

    # 2. HERMES_HOME / hermes-agent
    hermes_home = os.getenv('HERMES_HOME', str(HOME / '.hermes'))
    candidates.append(Path(hermes_home).expanduser() / 'hermes-agent')

    # 3. Sibling: <repo-root>/../hermes-agent
    candidates.append(REPO_ROOT.parent / 'hermes-agent')

    # 4. Parent is the agent repo itself (repo cloned inside hermes-agent/)
    if (REPO_ROOT.parent / 'run_agent.py').exists():
        candidates.append(REPO_ROOT.parent)

    # 5. ~/.hermes/hermes-agent (explicit common path)
    candidates.append(HOME / '.hermes' / 'hermes-agent')

    # 6. ~/hermes-agent
    candidates.append(HOME / 'hermes-agent')

    for path in candidates:
        if path.exists() and (path / 'run_agent.py').exists():
            return path.resolve()

    return None


def _discover_python(agent_dir: Path) -> str:
    """
    Locate a Python executable that has the Hermes agent dependencies installed.

    Priority:
      1. HERMES_WEBUI_PYTHON env var
      2. Agent venv at <agent_dir>/venv/bin/python
      3. Local .venv inside this repo
      4. System python3
    """
    if os.getenv('HERMES_WEBUI_PYTHON'):
        return os.getenv('HERMES_WEBUI_PYTHON')

    if agent_dir:
        venv_py = agent_dir / 'venv' / 'bin' / 'python'
        if venv_py.exists():
            return str(venv_py)

        # Windows layout
        venv_py_win = agent_dir / 'venv' / 'Scripts' / 'python.exe'
        if venv_py_win.exists():
            return str(venv_py_win)

    # Local .venv inside this repo
    local_venv = REPO_ROOT / '.venv' / 'bin' / 'python'
    if local_venv.exists():
        return str(local_venv)

    # Fall back to system python3
    import shutil
    for name in ('python3', 'python'):
        found = shutil.which(name)
        if found:
            return found

    return 'python3'


# Run discovery
_AGENT_DIR = _discover_agent_dir()
PYTHON_EXE = _discover_python(_AGENT_DIR)

# ── Inject agent dir into sys.path so Hermes modules are importable ──────────

# When users (or CI builds) run `pip install --target .` or
# `pip install -t .` inside the hermes-agent checkout, third-party
# package directories (openai/, pydantic/, requests/, etc.) end up
# alongside real Hermes source files.  Putting _AGENT_DIR at the
# FRONT of sys.path means Python resolves `import pydantic` from that
# local directory — which breaks whenever the host platform differs
# from the container (e.g. macOS .so files inside a Linux image).
#
# Fix: insert _AGENT_DIR at the END of sys.path.  Python searches
# entries in order, so site-packages resolves pip packages correctly,
# and Hermes-specific modules (run_agent, hermes/, etc.) still
# resolve because they do not exist in site-packages.

if _AGENT_DIR is not None:
    if str(_AGENT_DIR) not in sys.path:
        sys.path.append(str(_AGENT_DIR))
    _HERMES_FOUND = True
else:
    _HERMES_FOUND = False

# ── Config file (reloadable -- supports profile switching) ──────────────────
_cfg_cache = {}
_cfg_lock = threading.Lock()

def _get_config_path() -> Path:
    """Return config.yaml path for the active profile."""
    env_override = os.getenv('HERMES_CONFIG_PATH')
    if env_override:
        return Path(env_override).expanduser()
    try:
        from api.profiles import get_active_hermes_home
        return get_active_hermes_home() / 'config.yaml'
    except ImportError:
        return HOME / '.hermes' / 'config.yaml'

def get_config() -> dict:
    """Return the cached config dict, loading from disk if needed."""
    if not _cfg_cache:
        reload_config()
    return _cfg_cache

def reload_config() -> None:
    """Reload config.yaml from the active profile's directory."""
    with _cfg_lock:
        _cfg_cache.clear()
        config_path = _get_config_path()
        try:
            import yaml as _yaml
            if config_path.exists():
                loaded = _yaml.safe_load(config_path.read_text())
                if isinstance(loaded, dict):
                    _cfg_cache.update(loaded)
        except Exception:
            pass

# Initial load
reload_config()
cfg = _cfg_cache  # alias for backward compat with existing references

# ── Default workspace discovery ───────────────────────────────────────────────
def _discover_default_workspace() -> Path:
    """
    Resolve the default workspace in order:
      1. HERMES_WEBUI_DEFAULT_WORKSPACE env var
      2. ~/workspace (common Hermes convention)
      3. STATE_DIR / workspace (isolated fallback)
    """
    if os.getenv('HERMES_WEBUI_DEFAULT_WORKSPACE'):
        return Path(os.getenv('HERMES_WEBUI_DEFAULT_WORKSPACE')).expanduser().resolve()

    common = HOME / 'workspace'
    if common.exists():
        return common.resolve()

    return (STATE_DIR / 'workspace').resolve()

DEFAULT_WORKSPACE = _discover_default_workspace()
DEFAULT_MODEL     = os.getenv('HERMES_WEBUI_DEFAULT_MODEL', 'openai/gpt-5.4-mini')

# ── Startup diagnostics ───────────────────────────────────────────────────────
def print_startup_config() -> None:
    """Print detected configuration at startup so the user can verify what was found."""
    ok   = '\033[32m[ok]\033[0m'
    warn = '\033[33m[!!]\033[0m'
    err  = '\033[31m[XX]\033[0m'

    lines = [
        '',
        '  Hermes Web UI -- startup config',
        '  --------------------------------',
        f'  repo root   : {REPO_ROOT}',
        f'  agent dir   : {_AGENT_DIR if _AGENT_DIR else "NOT FOUND"}  {ok if _AGENT_DIR else err}',
        f'  python      : {PYTHON_EXE}',
        f'  state dir   : {STATE_DIR}',
        f'  workspace   : {DEFAULT_WORKSPACE}',
        f'  host:port   : {HOST}:{PORT}',
        f'  config file : {_get_config_path()}  {"(found)" if _get_config_path().exists() else "(not found, using defaults)"}',
        '',
    ]
    print('\n'.join(lines), flush=True)

    if not _HERMES_FOUND:
        print(
            f'{err}  Could not find the Hermes agent directory.\n'
            '      The server will start but agent features will not work.\n'
            '\n'
            '      To fix, set one of:\n'
            '        export HERMES_WEBUI_AGENT_DIR=/path/to/hermes-agent\n'
            '        export HERMES_HOME=/path/to/.hermes\n'
            '\n'
            '      Or clone hermes-agent as a sibling of this repo:\n'
            '        git clone <hermes-agent-repo> ../hermes-agent\n',
            flush=True
        )

def verify_hermes_imports() -> tuple:
    """
    Attempt to import the key Hermes modules.
    Returns (ok: bool, missing: list[str], errors: dict[str, str]).
    """
    required = ['run_agent']
    missing  = []
    errors   = {}
    for mod in required:
        try:
            __import__(mod)
        except Exception as e:
            missing.append(mod)
            # Capture the full error message so startup logs show WHY
            # (e.g. pydantic_core .so mismatch) instead of just the name.
            errors[mod] = f"{type(e).__name__}: {e}"
    return (len(missing) == 0), missing, errors

# ── Limits ───────────────────────────────────────────────────────────────────
MAX_FILE_BYTES   = 200_000
MAX_UPLOAD_BYTES = 20 * 1024 * 1024

# ── File type maps ───────────────────────────────────────────────────────────
IMAGE_EXTS = {'.png', '.jpg', '.jpeg', '.gif', '.svg', '.webp', '.ico', '.bmp'}
MD_EXTS    = {'.md', '.markdown', '.mdown'}
CODE_EXTS  = {'.py', '.js', '.ts', '.jsx', '.tsx', '.css', '.html', '.json',
              '.yaml', '.yml', '.toml', '.sh', '.bash', '.txt', '.log', '.env',
              '.csv', '.xml', '.sql', '.rs', '.go', '.java', '.c', '.cpp', '.h'}
MIME_MAP = {
    '.png':'image/png', '.jpg':'image/jpeg', '.jpeg':'image/jpeg',
    '.gif':'image/gif', '.svg':'image/svg+xml', '.webp':'image/webp',
    '.ico':'image/x-icon', '.bmp':'image/bmp',
    '.pdf':'application/pdf', '.json':'application/json',
}

# ── Toolsets (from config.yaml or hardcoded default) ─────────────────────────
_DEFAULT_TOOLSETS = [
    'browser', 'clarify', 'code_execution', 'cronjob', 'delegation', 'file',
    'image_gen', 'memory', 'session_search', 'skills', 'terminal', 'todo',
    'web', 'webhook',
]
CLI_TOOLSETS = get_config().get('platform_toolsets', {}).get('cli', _DEFAULT_TOOLSETS)

# ── Model / provider discovery ───────────────────────────────────────────────

# Hardcoded fallback models (used when no config.yaml or agent is available)
_FALLBACK_MODELS = [
    {'provider': 'OpenAI',    'id': 'openai/gpt-5.4-mini',              'label': 'GPT-5.4 Mini'},
    {'provider': 'OpenAI',    'id': 'openai/gpt-4o',                    'label': 'GPT-4o'},
    {'provider': 'OpenAI',    'id': 'openai/o3',                        'label': 'o3'},
    {'provider': 'OpenAI',    'id': 'openai/o4-mini',                   'label': 'o4-mini'},
    {'provider': 'Anthropic', 'id': 'anthropic/claude-sonnet-4.6',      'label': 'Claude Sonnet 4.6'},
    {'provider': 'Anthropic', 'id': 'anthropic/claude-sonnet-4-5',      'label': 'Claude Sonnet 4.5'},
    {'provider': 'Anthropic', 'id': 'anthropic/claude-haiku-4-5',       'label': 'Claude Haiku 4.5'},
    {'provider': 'Other',     'id': 'google/gemini-2.5-pro',            'label': 'Gemini 2.5 Pro'},
    {'provider': 'Other',     'id': 'deepseek/deepseek-chat-v3-0324',   'label': 'DeepSeek V3'},
    {'provider': 'Other',     'id': 'meta-llama/llama-4-scout',         'label': 'Llama 4 Scout'},
]

# Provider display names for known Hermes provider IDs
_PROVIDER_DISPLAY = {
    'nous': 'Nous Portal', 'openrouter': 'OpenRouter', 'anthropic': 'Anthropic',
    'openai': 'OpenAI', 'openai-codex': 'OpenAI Codex', 'copilot': 'GitHub Copilot',
    'zai': 'Z.AI / GLM', 'kimi-coding': 'Kimi / Moonshot', 'deepseek': 'DeepSeek',
    'minimax': 'MiniMax', 'google': 'Google', 'meta-llama': 'Meta Llama',
    'huggingface': 'HuggingFace', 'alibaba': 'Alibaba',
    'ollama': 'Ollama', 'lmstudio': 'LM Studio',
}

# Well-known models per provider (used to populate dropdown for direct API providers)
_PROVIDER_MODELS = {
    'anthropic': [
        {'id': 'claude-opus-4.6',    'label': 'Claude Opus 4.6'},
        {'id': 'claude-sonnet-4.6',  'label': 'Claude Sonnet 4.6'},
        {'id': 'claude-sonnet-4-5',  'label': 'Claude Sonnet 4.5'},
        {'id': 'claude-haiku-4-5',   'label': 'Claude Haiku 4.5'},
    ],
    'openai': [
        {'id': 'gpt-5.4-mini', 'label': 'GPT-5.4 Mini'},
        {'id': 'gpt-4o',       'label': 'GPT-4o'},
        {'id': 'o3',           'label': 'o3'},
        {'id': 'o4-mini',      'label': 'o4-mini'},
    ],
    'openai-codex': [
        {'id': 'codex-mini-latest', 'label': 'Codex Mini'},
    ],
    'google': [
        {'id': 'gemini-2.5-pro', 'label': 'Gemini 2.5 Pro'},
    ],
    'deepseek': [
        {'id': 'deepseek-chat-v3-0324', 'label': 'DeepSeek V3'},
        {'id': 'deepseek-reasoner',     'label': 'DeepSeek Reasoner'},
    ],
    'nous': [
        {'id': 'claude-opus-4.6',    'label': 'Claude Opus 4.6 (via Nous)'},
        {'id': 'claude-sonnet-4.6',  'label': 'Claude Sonnet 4.6 (via Nous)'},
        {'id': 'gpt-5.4-mini',      'label': 'GPT-5.4 Mini (via Nous)'},
        {'id': 'gemini-2.5-pro',    'label': 'Gemini 2.5 Pro (via Nous)'},
    ],
    'zai': [
        {'id': 'glm-5.1',            'label': 'GLM-5.1'},
        {'id': 'glm-5',              'label': 'GLM-5'},
        {'id': 'glm-5-turbo',        'label': 'GLM-5 Turbo'},
        {'id': 'glm-4.7',            'label': 'GLM-4.7'},
        {'id': 'glm-4.5',            'label': 'GLM-4.5'},
        {'id': 'glm-4.5-flash',      'label': 'GLM-4.5 Flash'},
    ],
    'kimi-coding': [
        {'id': 'moonshot-v1-8k',     'label': 'Moonshot v1 8k'},
        {'id': 'moonshot-v1-32k',    'label': 'Moonshot v1 32k'},
        {'id': 'moonshot-v1-128k',   'label': 'Moonshot v1 128k'},
        {'id': 'kimi-latest',        'label': 'Kimi Latest'},
    ],
    'minimax': [
        {'id': 'MiniMax-M2.7',           'label': 'MiniMax M2.7'},
        {'id': 'MiniMax-M2.7-highspeed', 'label': 'MiniMax M2.7 Highspeed'},
        {'id': 'MiniMax-M2.5',           'label': 'MiniMax M2.5'},
        {'id': 'MiniMax-M2.5-highspeed', 'label': 'MiniMax M2.5 Highspeed'},
        {'id': 'MiniMax-M2.1',           'label': 'MiniMax M2.1'},
    ],
    # GitHub Copilot — model IDs served via the Copilot API
    'copilot': [
        {'id': 'gpt-5.4',           'label': 'GPT-5.4'},
        {'id': 'gpt-5.4-mini',      'label': 'GPT-5.4 Mini'},
        {'id': 'gpt-4o',            'label': 'GPT-4o'},
        {'id': 'claude-opus-4.6',   'label': 'Claude Opus 4.6'},
        {'id': 'claude-sonnet-4.6', 'label': 'Claude Sonnet 4.6'},
        {'id': 'gemini-2.5-pro',    'label': 'Gemini 2.5 Pro'},
    ],
    # 'gemini' is the hermes_cli provider ID for Google AI Studio
    'gemini': [
        {'id': 'gemini-2.5-pro',   'label': 'Gemini 2.5 Pro'},
        {'id': 'gemini-2.0-flash', 'label': 'Gemini 2.0 Flash'},
    ],
}


def resolve_model_provider(model_id: str) -> tuple:
    """Resolve model name, provider, and base_url for AIAgent.

    Model IDs from the dropdown can be in several formats:
      - 'claude-sonnet-4.6'          (bare name, uses config default provider)
      - 'anthropic/claude-sonnet-4.6' (OpenRouter format, provider/model)
      - '@minimax:MiniMax-M2.7'       (explicit provider hint from dropdown)

    The @provider:model format is used for models from non-default provider
    groups in the dropdown, so we can route them through the correct provider
    via resolve_runtime_provider(requested=provider) instead of the default.

    Returns (model, provider, base_url) where provider and base_url may be None.
    """
    config_provider = None
    config_base_url = None
    model_cfg = cfg.get('model', {})
    if isinstance(model_cfg, dict):
        config_provider = model_cfg.get('provider')
        config_base_url = model_cfg.get('base_url')

    model_id = (model_id or '').strip()
    if not model_id:
        return model_id, config_provider, config_base_url

    # @provider:model format — explicit provider hint from the dropdown.
    # Route through that provider directly (resolve_runtime_provider will
    # resolve credentials in streaming.py).
    if model_id.startswith('@') and ':' in model_id:
        provider_hint, bare_model = model_id[1:].split(':', 1)
        return bare_model, provider_hint, None

    if '/' in model_id:
        prefix, bare = model_id.split('/', 1)
        # OpenRouter always needs the full provider/model path (e.g. openrouter/free,
        # anthropic/claude-sonnet-4.6). Never strip the prefix for OpenRouter.
        if config_provider == 'openrouter':
            return model_id, 'openrouter', config_base_url
        # If prefix matches config provider exactly, strip it and use that provider directly.
        # e.g. config=anthropic, model=anthropic/claude-... → bare name to anthropic API
        if config_provider and prefix == config_provider:
            return bare, config_provider, config_base_url
        # If prefix does NOT match config provider, the user picked a cross-provider model
        # from the OpenRouter dropdown (e.g. config=anthropic but picked openai/gpt-5.4-mini).
        # In this case always route through openrouter with the full provider/model string.
        if prefix in _PROVIDER_MODELS and prefix != config_provider:
            return model_id, 'openrouter', None

    return model_id, config_provider, config_base_url


def get_available_models() -> dict:
    """
    Return available models grouped by provider.

    Discovery order:
      1. Read config.yaml 'model' section for active provider info
      2. Check for known API keys in env or ~/.hermes/.env
      3. Fetch models from custom endpoint if base_url is configured
      4. Fall back to hardcoded model list (OpenRouter-style)

    Returns: {
        'active_provider': str|None,
        'default_model': str,
        'groups': [{'provider': str, 'models': [{'id': str, 'label': str}]}]
    }
    """
    active_provider = None
    default_model = DEFAULT_MODEL
    groups = []

    # 1. Read config.yaml model section
    cfg_base_url = ''  # must be defined before conditional blocks (#117)
    model_cfg = cfg.get('model', {})
    cfg_base_url = ''
    if isinstance(model_cfg, str):
        default_model = model_cfg
    elif isinstance(model_cfg, dict):
        active_provider = model_cfg.get('provider')
        cfg_default = model_cfg.get('default', '')
        cfg_base_url = model_cfg.get('base_url', '')
        if cfg_default:
            default_model = cfg_default

    # 2. Also check env vars for model override
    env_model = os.getenv('HERMES_MODEL') or os.getenv('OPENAI_MODEL') or os.getenv('LLM_MODEL')
    if env_model:
        default_model = env_model.strip()

    # 3. Try to read auth store for active provider (if hermes is installed)
    if not active_provider:
        try:
            from api.profiles import get_active_hermes_home as _gah
            auth_store_path = _gah() / 'auth.json'
        except ImportError:
            auth_store_path = HOME / '.hermes' / 'auth.json'
        if auth_store_path.exists():
            try:
                import json as _j
                auth_store = _j.loads(auth_store_path.read_text())
                active_provider = auth_store.get('active_provider')
            except Exception:
                pass

    # 4. Detect available providers.
    # Primary: ask hermes-agent's auth layer — the authoritative source. It checks
    # auth.json, credential pools, and env vars the same way the agent does at runtime,
    # so the dropdown reflects exactly what the user has configured.
    # Fallback: scan raw API key env vars (matches old behaviour if hermes not available).
    detected_providers = set()
    if active_provider:
        detected_providers.add(active_provider)

    _hermes_auth_used = False
    try:
        from hermes_cli.models import list_available_providers as _lap
        from hermes_cli.auth import get_auth_status as _gas
        for _p in _lap():
            if not _p.get('authenticated'):
                continue
            # Exclude providers whose credential came from an ambient token
            # (e.g. 'gh auth token' for Copilot on a machine with gh CLI auth).
            # Only include providers with an explicit, dedicated credential.
            try:
                _src = _gas(_p['id']).get('key_source', '')
                if _src == 'gh auth token':
                    continue
            except Exception:
                pass
            detected_providers.add(_p['id'])
        _hermes_auth_used = True
    except Exception:
        pass

    if not _hermes_auth_used:
        # Fallback: scan .env and os.environ for known API key variables
        try:
            from api.profiles import get_active_hermes_home as _gah2
            hermes_env_path = _gah2() / '.env'
        except ImportError:
            hermes_env_path = HOME / '.hermes' / '.env'
        env_keys = {}
        if hermes_env_path.exists():
            try:
                for line in hermes_env_path.read_text().splitlines():
                    line = line.strip()
                    if line and not line.startswith('#') and '=' in line:
                        k, v = line.split('=', 1)
                        env_keys[k.strip()] = v.strip().strip('"').strip("'")
            except Exception:
                pass
        all_env = {**env_keys}
        for k in ('ANTHROPIC_API_KEY', 'OPENAI_API_KEY', 'OPENROUTER_API_KEY',
                  'GOOGLE_API_KEY', 'GLM_API_KEY', 'KIMI_API_KEY', 'DEEPSEEK_API_KEY'):
            val = os.getenv(k)
            if val:
                all_env[k] = val
        if all_env.get('ANTHROPIC_API_KEY'):
            detected_providers.add('anthropic')
        if all_env.get('OPENAI_API_KEY'):
            detected_providers.add('openai')
        if all_env.get('OPENROUTER_API_KEY'):
            detected_providers.add('openrouter')
        if all_env.get('GOOGLE_API_KEY'):
            detected_providers.add('google')
        if all_env.get('GLM_API_KEY'):
            detected_providers.add('zai')
        if all_env.get('KIMI_API_KEY'):
            detected_providers.add('kimi-coding')
        if all_env.get('MINIMAX_API_KEY') or all_env.get('MINIMAX_CN_API_KEY'):
            detected_providers.add('minimax')
        if all_env.get('DEEPSEEK_API_KEY'):
            detected_providers.add('deepseek')

    # 3. Fetch models from custom endpoint if base_url is configured
    auto_detected_models = []
    if cfg_base_url:
        try:
            import ipaddress
            import urllib.request

            # Normalize the base_url and build models endpoint
            base_url = cfg_base_url.strip()
            if base_url.endswith('/v1'):
                endpoint_url = base_url[:-3] + '/models'
            else:
                endpoint_url = base_url + '/v1/models'

            # Detect provider from base_url
            provider = 'custom'
            parsed = urlparse(base_url if '://' in base_url else f'http://{base_url}')
            host = (parsed.netloc or parsed.path).lower()

            if parsed.hostname:
                try:
                    addr = ipaddress.ip_address(parsed.hostname)
                    if addr.is_private or addr.is_loopback or addr.is_link_local:
                        if 'ollama' in host or '127.0.0.1' in host or 'localhost' in host:
                            provider = 'ollama'
                        elif 'lmstudio' in host or 'lm-studio' in host:
                            provider = 'lmstudio'
                        else:
                            provider = 'local'
                except ValueError:
                    pass

            # Resolve API key from environment
            headers = {}
            api_key_vars = ('HERMES_API_KEY', 'HERMES_OPENAI_API_KEY', 'OPENAI_API_KEY',
                            'LOCAL_API_KEY', 'OPENROUTER_API_KEY', 'API_KEY')
            for key in api_key_vars:
                api_key = os.getenv(key)
                if api_key:
                    headers['Authorization'] = f'Bearer {api_key}'
                    break

            # Fetch model list from endpoint
            req = urllib.request.Request(endpoint_url, method='GET')
            for k, v in headers.items():
                req.add_header(k, v)
            with urllib.request.urlopen(req, timeout=10) as response:
                data = json.loads(response.read().decode('utf-8'))

            # Handle both OpenAI-compatible and llama.cpp response formats
            models_list = []
            if 'data' in data and isinstance(data['data'], list):
                models_list = data['data']
            elif 'models' in data and isinstance(data['models'], list):
                models_list = data['models']

            for model in models_list:
                if not isinstance(model, dict):
                    continue
                model_id = model.get('id', '') or model.get('name', '') or model.get('model', '')
                model_name = model.get('name', '') or model.get('model', '') or model_id
                if model_id and model_name:
                    auto_detected_models.append({'id': model_id, 'label': model_name})
                    detected_providers.add(provider.lower())
        except Exception:
            pass  # custom endpoint unreachable or misconfigured -- fail silently

    # 5. Build model groups
    if detected_providers:
        for pid in sorted(detected_providers):
            provider_name = _PROVIDER_DISPLAY.get(pid, pid.title())
            if pid == 'openrouter':
                # OpenRouter uses provider/model format -- show the fallback list
                groups.append({
                    'provider': 'OpenRouter',
                    'models': [{'id': m['id'], 'label': m['label']} for m in _FALLBACK_MODELS],
                })
            elif pid in _PROVIDER_MODELS:
                # For non-default providers, prefix model IDs with @provider:model
                # so resolve_model_provider() routes through that specific provider
                # via resolve_runtime_provider(requested=provider).
                # The default provider's models keep bare names for direct API routing.
                raw_models = _PROVIDER_MODELS[pid]
                _active = (active_provider or '').lower()
                if _active and pid != _active:
                    models = []
                    for m in raw_models:
                        mid = m['id']
                        # Don't double-prefix; use @provider: hint for bare names
                        if mid.startswith('@') or '/' in mid:
                            models.append({'id': mid, 'label': m['label']})
                        else:
                            models.append({'id': f'@{pid}:{mid}', 'label': m['label']})
                else:
                    models = list(raw_models)
                groups.append({
                    'provider': provider_name,
                    'models': models,
                })
            else:
                # Unknown provider -- use auto-detected models if available,
                # otherwise fall back to default model placeholder
                if auto_detected_models:
                    groups.append({
                        'provider': provider_name,
                        'models': auto_detected_models,
                    })
                else:
                    groups.append({
                        'provider': provider_name,
                        'models': [{'id': default_model, 'label': default_model.split('/')[-1]}],
                    })
    else:
        # No providers detected. Show only the configured default model so the user
        # can at least send messages with their current setting. Avoid showing a
        # generic multi-provider list — those models wouldn't be routable anyway.
        label = default_model.split('/')[-1] if '/' in default_model else default_model
        groups.append({'provider': 'Default', 'models': [{'id': default_model, 'label': label}]})

    # Ensure the user's configured default_model always appears in the dropdown.
    # It may be missing if the model isn't in any hardcoded list (e.g. openrouter/free,
    # a custom local model, or any model.default not in _FALLBACK_MODELS).
    # Normalize before comparing: strip provider prefix so 'anthropic/claude-opus-4.6'
    # matches 'claude-opus-4.6' already in the list and avoids a duplicate entry.
    if default_model:
        _norm = lambda mid: mid.split('/', 1)[-1] if '/' in mid else mid
        all_ids_norm = {_norm(m['id']) for g in groups for m in g.get('models', [])}
        if _norm(default_model) not in all_ids_norm:
            # Determine which group to inject into
            label = default_model.split('/')[-1] if '/' in default_model else default_model
            injected = False
            for g in groups:
                if active_provider and active_provider.lower() in g.get('provider', '').lower():
                    g['models'].insert(0, {'id': default_model, 'label': label})
                    injected = True
                    break
            if not injected and groups:
                groups[0]['models'].insert(0, {'id': default_model, 'label': label})
            elif not groups:
                groups.append({'provider': active_provider or 'Default', 'models': [{'id': default_model, 'label': label}]})

    return {
        'active_provider': active_provider,
        'default_model': default_model,
        'groups': groups,
    }


# ── Static file path ─────────────────────────────────────────────────────────
_INDEX_HTML_PATH = REPO_ROOT / 'static' / 'index.html'

# ── Thread synchronisation ───────────────────────────────────────────────────
LOCK              = threading.Lock()
SESSIONS_MAX      = 100
CHAT_LOCK         = threading.Lock()
STREAMS: dict     = {}
STREAMS_LOCK      = threading.Lock()
CANCEL_FLAGS: dict = {}
SERVER_START_TIME = time.time()

# ── Thread-local env context ─────────────────────────────────────────────────
_thread_ctx = threading.local()

def _set_thread_env(**kwargs):
    _thread_ctx.env = kwargs

def _clear_thread_env():
    _thread_ctx.env = {}

# ── Per-session agent locks ───────────────────────────────────────────────────
SESSION_AGENT_LOCKS: dict = {}
SESSION_AGENT_LOCKS_LOCK  = threading.Lock()

def _get_session_agent_lock(session_id: str) -> threading.Lock:
    with SESSION_AGENT_LOCKS_LOCK:
        if session_id not in SESSION_AGENT_LOCKS:
            SESSION_AGENT_LOCKS[session_id] = threading.Lock()
        return SESSION_AGENT_LOCKS[session_id]

# ── Settings persistence ─────────────────────────────────────────────────────

_SETTINGS_DEFAULTS = {
    'default_model': DEFAULT_MODEL,
    'default_workspace': str(DEFAULT_WORKSPACE),
    'send_key': 'enter',  # 'enter' or 'ctrl+enter'
    'show_token_usage': False,  # show input/output token badge below assistant messages
    'show_cli_sessions': False,  # merge CLI sessions from state.db into the sidebar
    'sync_to_insights': False,  # mirror WebUI token usage to state.db for /insights
    'check_for_updates': True,  # check if webui/agent repos are behind upstream
    'theme': 'dark',  # active UI theme name (no enum gate -- allows custom themes)
    'bot_name': os.getenv('HERMES_WEBUI_BOT_NAME', 'Hermes'),  # display name for the assistant
    'password_hash': None,  # SHA-256 hash; None = auth disabled
}

def load_settings() -> dict:
    """Load settings from disk, merging with defaults for any missing keys."""
    settings = dict(_SETTINGS_DEFAULTS)
    if SETTINGS_FILE.exists():
        try:
            stored = json.loads(SETTINGS_FILE.read_text(encoding='utf-8'))
            if isinstance(stored, dict):
                settings.update(stored)
        except Exception:
            pass
    return settings

_SETTINGS_ALLOWED_KEYS = set(_SETTINGS_DEFAULTS.keys()) - {'password_hash'}
_SETTINGS_ENUM_VALUES = {
    'send_key': {'enter', 'ctrl+enter'},
}
_SETTINGS_BOOL_KEYS = {'show_token_usage', 'show_cli_sessions', 'sync_to_insights', 'check_for_updates'}

def save_settings(settings: dict) -> dict:
    """Save settings to disk. Returns the merged settings. Ignores unknown keys."""
    import hashlib as _hl
    current = load_settings()
    # Handle _set_password: hash and store as password_hash
    raw_pw = settings.pop('_set_password', None)
    if raw_pw and isinstance(raw_pw, str) and raw_pw.strip():
        salt = str(STATE_DIR).encode()
        current['password_hash'] = _hl.sha256(salt + raw_pw.strip().encode()).hexdigest()
    # Handle _clear_password: explicitly disable auth
    if settings.pop('_clear_password', False):
        current['password_hash'] = None
    for k, v in settings.items():
        if k in _SETTINGS_ALLOWED_KEYS:
            # Validate enum-constrained keys
            if k in _SETTINGS_ENUM_VALUES and v not in _SETTINGS_ENUM_VALUES[k]:
                continue
            # Coerce bool keys
            if k in _SETTINGS_BOOL_KEYS:
                v = bool(v)
            current[k] = v
    SETTINGS_FILE.write_text(
        json.dumps(current, ensure_ascii=False, indent=2),
        encoding='utf-8',
    )
    # Update runtime defaults so new sessions use them immediately
    global DEFAULT_MODEL, DEFAULT_WORKSPACE
    if 'default_model' in current:
        DEFAULT_MODEL = current['default_model']
    if 'default_workspace' in current:
        DEFAULT_WORKSPACE = Path(current['default_workspace']).expanduser().resolve()
    return current

# Apply saved settings on startup (override env-derived defaults)
_startup_settings = load_settings()
if SETTINGS_FILE.exists():
    if _startup_settings.get('default_model'):
        DEFAULT_MODEL = _startup_settings['default_model']
    if _startup_settings.get('default_workspace'):
        DEFAULT_WORKSPACE = Path(_startup_settings['default_workspace']).expanduser().resolve()

# ── SESSIONS in-memory cache (LRU OrderedDict) ───────────────────────────────
SESSIONS: collections.OrderedDict = collections.OrderedDict()

# ── Profile state initialisation ────────────────────────────────────────────
# Must run after all imports are resolved to correctly patch module-level caches
try:
    from api.profiles import init_profile_state
    init_profile_state()
except ImportError:
    pass  # hermes_cli not available -- default profile only
