#!/usr/bin/env bash
set -euo pipefail

# Fail fast on broken Space metadata, duplicate templates, or stale cache artifacts.
APP_ROOT="$(CDPATH= cd -- "$(dirname -- "$0")" && pwd)"
export APP_ROOT
python3 "${APP_ROOT}/scripts/preflight.py"

# ============================================================
# Required non-model settings
# ============================================================

: "${MARINE_API_URL:?Missing MARINE_API_URL variable}"

# ============================================================
# Model provider and key.
#
# This deployment is intentionally ZAI-only.  The official Codex CLI remains
# the runtime, while ZAI/GLM-5.3 is its OpenAI-compatible model endpoint.
# ============================================================

CODEX_PROVIDER="${CODEX_PROVIDER:-zai}"
case "${CODEX_PROVIDER,,}" in
  auto|glm|zhipu|zai)
    CODEX_PROVIDER="zai"
    ;;
  *)
    echo "[startup] ERROR: this deployment only supports CODEX_PROVIDER=zai"
    exit 1
    ;;
esac

MODEL_API_KEY="${ZAI_API_KEY:-${GLM_API_KEY:-${ZHIPU_API_KEY:-}}}"
export OPENAI_BASE_URL="${OPENAI_BASE_URL:-https://open.bigmodel.cn/api/v1}"
export CODEX_MODEL="${CODEX_MODEL:-glm-5.3}"
export CODEX_PROVIDER_ID="ZAI"
export CODEX_PROVIDER_NAME="ZAI"

echo "[startup] Codex provider=${CODEX_PROVIDER_NAME}; model=${CODEX_MODEL}; base_url=${OPENAI_BASE_URL}"

if [ -z "${MODEL_API_KEY}" ]; then
  echo "[startup] ERROR: no ${CODEX_PROVIDER_NAME} API key was injected."
  echo "[startup] Expected secret: ZAI_API_KEY (or GLM_API_KEY/ZHIPU_API_KEY)"
  echo "[startup] Available environment variable names containing KEY/API:"
  env | cut -d= -f1 | grep -E 'KEY|API' | sort || true
  exit 1
fi

# ============================================================
# Official OpenAI Codex CLI runtime
# ============================================================

export OPENAI_API_KEY="${MODEL_API_KEY}"
# Both deployments use the official native Codex CLI Harness.  Do not
# silently fall back to the legacy HTTP adapter.
export CODEX_HARNESS_RUNTIME="${CODEX_HARNESS_RUNTIME:-native}"
export REQUIRE_CODEX_HARNESS="${REQUIRE_CODEX_HARNESS:-1}"
if [ "${CODEX_HARNESS_RUNTIME}" != "native" ]; then
  echo "[startup] ERROR: CODEX_HARNESS_RUNTIME must be native"
  exit 1
fi
# Both providers use the official Codex Responses transport.  Disable the
# optional WebSocket transport because the compatible endpoints expose HTTPS
# Responses reliably and do not require a WebSocket session.
export CODEX_DISABLE_WEBSOCKETS="${CODEX_DISABLE_WEBSOCKETS:-1}"
# This service is a public data interface, not an operations shell.  Refuse a
# stale or accidental bypass setting before the official CLI is started.
case "${CODEX_ALLOW_MCP_BYPASS:-0}" in
  0|false|FALSE|no|NO|off|OFF|"") ;;
  *)
    echo "[startup] ERROR: CODEX_ALLOW_MCP_BYPASS is forbidden for this deployment"
    exit 1
    ;;
esac
export CODEX_ALLOW_MCP_BYPASS=0
export MARINE_EXPORT_RANGE_MAX_DAYS="${MARINE_EXPORT_RANGE_MAX_DAYS:-31}"

# ============================================================
# Web / Runtime
# ============================================================

export PORT="${PORT:-7860}"
export FISHERIES_EXPORT_ROOT="${FISHERIES_EXPORT_ROOT:-/tmp/squid_fisheries_exports}"
export HF_FISHERIES_CACHE_ROOT="${HF_FISHERIES_CACHE_ROOT:-/tmp/squid_hf_fisheries_cache}"
if [ -z "${PUBLIC_BASE_URL:-}" ] && [ -n "${SPACE_HOST:-}" ]; then
  export PUBLIC_BASE_URL="https://${SPACE_HOST}"
fi

# ============================================================
# Build private Marine MCP runtime configuration
# ============================================================

RUNTIME_MCP_CONFIG="/tmp/codex-marine-mcp.json"
export RUNTIME_MCP_CONFIG

python3 - <<'PY_MCP_CONFIG'
import json
import os
from pathlib import Path

env = {
    "MARINE_API_URL": os.environ["MARINE_API_URL"],
    "HF_SQUID_DATASET_REPO": (
        os.environ.get("HF_SQUID_DATASET_REPO")
        or os.environ.get("HF_DATASET_REPO")
        or "globalsquiddatabase/squid_dataset"
    ),
    "HF_TUNA_DATASET_REPO": (
        os.environ.get("HF_TUNA_DATASET_REPO")
        or "globalsquiddatabase/Tuna-Fisheries-Dataset"
    ),
    "FISHERIES_EXPORT_ROOT": os.environ.get(
        "FISHERIES_EXPORT_ROOT", "/tmp/squid_fisheries_exports"
    ),
    "HF_FISHERIES_CACHE_ROOT": os.environ.get(
        "HF_FISHERIES_CACHE_ROOT", "/tmp/squid_hf_fisheries_cache"
    ),
    "HF_SQUID_DATASET_REVISION": (
        os.environ.get("HF_SQUID_DATASET_REVISION")
        or os.environ.get("HF_DATASET_REVISION", "")
    ),
    "HF_TUNA_DATASET_REVISION": os.environ.get("HF_TUNA_DATASET_REVISION", ""),
    "PUBLIC_BASE_URL": os.environ.get("PUBLIC_BASE_URL", ""),
    "MARINE_PUBLIC_BASE_URL": os.environ.get("MARINE_PUBLIC_BASE_URL", ""),
    "MARINE_EXPORT_RANGE_MAX_DAYS": os.environ.get("MARINE_EXPORT_RANGE_MAX_DAYS", "31"),
}

hf_token = os.environ.get("HF_TOKEN", "").strip()
if hf_token:
    env["HF_TOKEN"] = hf_token
for name in ("LOCAL_SQUID_DATA_ROOT", "LOCAL_TUNA_DATA_ROOT"):
    if os.environ.get(name, "").strip():
        env[name] = os.environ[name]

cfg = {
    "timeouts": {
        "connect_timeout": 15,
        "execute_timeout": 900,
        "read_timeout": 900,
    },
    "servers": {
        "marine": {
            "command": "python3",
            "args": [os.path.join(os.environ["APP_ROOT"], "marine_mcp.py")],
            "disabled": False,
            "required": False,
            "env": env,
        }
    },
}

p = Path(os.environ["RUNTIME_MCP_CONFIG"])
p.write_text(
    json.dumps(cfg, ensure_ascii=False, indent=2) + "\n",
    encoding="utf-8",
)
p.chmod(0o600)

print("[startup] private Marine MCP runtime config ready")
PY_MCP_CONFIG

# Official Codex CLI configuration.  The JSON file above is retained for
# backwards compatibility with the adapter; native mode reads this TOML file.
export CODEX_HOME="${CODEX_HOME:-${HOME:-/tmp}/.codex-home}"
mkdir -p "${CODEX_HOME}"
python3 - <<'PY_CODEX_CONFIG'
import json
import os
from pathlib import Path

def q(value):
    return json.dumps(str(value), ensure_ascii=False)

home = Path(os.environ["CODEX_HOME"])
home.mkdir(parents=True, exist_ok=True)
marine_env = {
    "MARINE_API_URL": os.environ["MARINE_API_URL"],
    "HF_SQUID_DATASET_REPO": os.environ.get("HF_SQUID_DATASET_REPO", "globalsquiddatabase/squid_dataset"),
    "HF_TUNA_DATASET_REPO": os.environ.get("HF_TUNA_DATASET_REPO", "globalsquiddatabase/Tuna-Fisheries-Dataset"),
    "FISHERIES_EXPORT_ROOT": os.environ.get("FISHERIES_EXPORT_ROOT", "/tmp/squid_fisheries_exports"),
    "HF_FISHERIES_CACHE_ROOT": os.environ.get("HF_FISHERIES_CACHE_ROOT", "/tmp/squid_hf_fisheries_cache"),
    "PUBLIC_BASE_URL": os.environ.get("PUBLIC_BASE_URL", ""),
    "MARINE_PUBLIC_BASE_URL": os.environ.get("MARINE_PUBLIC_BASE_URL", ""),
    "MARINE_EXPORT_RANGE_MAX_DAYS": os.environ.get("MARINE_EXPORT_RANGE_MAX_DAYS", "31"),
}
for name in ("HF_TOKEN", "HF_SQUID_DATASET_REVISION", "HF_TUNA_DATASET_REVISION"):
    if os.environ.get(name, "").strip():
        marine_env[name] = os.environ[name]
for name in ("LOCAL_SQUID_DATA_ROOT", "LOCAL_TUNA_DATA_ROOT"):
    if os.environ.get(name, "").strip():
        marine_env[name] = os.environ[name]

auth_line = (
    "experimental_bearer_token = " + q(os.environ["OPENAI_API_KEY"])
    if os.environ.get("CODEX_PROVIDER") == "zai"
    else "env_key = \"OPENAI_API_KEY\""
)

lines = [
    "model_provider = " + q(os.environ["CODEX_PROVIDER_ID"]),
    "model = " + q(os.environ.get("CODEX_MODEL", "glm-5.3")),
    "model_reasoning_effort = " + q(os.environ.get("CODEX_REASONING_EFFORT", "max")),
    "cli_auth_credentials_store = \"file\"",
    "",
    "[model_providers." + os.environ["CODEX_PROVIDER_ID"] + "]",
    "name = " + q(os.environ["CODEX_PROVIDER_NAME"]),
    "base_url = " + q(os.environ.get("OPENAI_BASE_URL", "https://open.bigmodel.cn/api/v1")),
    auth_line,
    "requires_openai_auth = false",
    "wire_api = \"responses\"",
    "supports_websockets = false",
    "",
    "[mcp_servers.marine]",
    "command = \"python3\"",
    "args = [" + q(os.path.join(os.environ["APP_ROOT"], "marine_mcp.py")) + "]",
    "required = false",
    # Native/headless Codex runs cannot display an interactive MCP approval
    # prompt.  Marine is the deployment's explicitly configured, read-only
    # data server, so approve its tool calls in the CLI config instead of
    # leaving requests pending until the harness timeout.
    "default_tools_approval_mode = \"approve\"",
    "startup_timeout_sec = 30",
    "tool_timeout_sec = 900",
    "env = { " + ", ".join(f"{k} = {q(v)}" for k, v in marine_env.items()) + " }",
]
# Publish metadata for whichever OpenAI-compatible provider/model is active.
if os.environ.get("CODEX_MODEL", "").strip():
    catalog = {
        "models": [{
            "slug": os.environ.get("CODEX_MODEL", "glm-5.3"),
            "display_name": os.environ.get("CODEX_MODEL", "glm-5.3"),
            "description": (
                os.environ.get("CODEX_PROVIDER_NAME", "OpenAI-compatible")
                + " model"
            ),
            "base_instructions": "You are a helpful coding assistant. Use the configured Marine MCP tools when the user asks for marine data.",
            "model_messages": {
                "instructions_template": "You are a helpful coding assistant. Follow the user's request and use available tools when needed."
            },
            "default_reasoning_level": os.environ.get("CODEX_REASONING_EFFORT", "max"),
            "supported_reasoning_levels": [
                {"effort": "low", "description": "Light reasoning"},
                {"effort": "medium", "description": "Balanced reasoning"},
                {"effort": "high", "description": "Deep reasoning"},
                {"effort": "max", "description": "Maximum reasoning"},
            ],
            # These fields are required by the official Codex model catalog
            # parser.  Keep the legacy shell_command spelling accepted by
            # Codex 0.147.x while preserving the standard tool capability.
            "shell_type": "shell_command",
            "visibility": "list",
            "supported_in_api": True,
            "priority": 1,
            "truncation_policy": {"mode": "tokens", "limit": 204800},
            "supports_reasoning_summaries": True,
            "default_reasoning_summary": "none",
            "support_verbosity": False,
            "default_verbosity": None,
            "context_window": 204800,
            "max_context_window": 204800,
            "effective_context_window_percent": 95,
            "supports_parallel_tool_calls": True,
            "experimental_supported_tools": [],
            "input_modalities": ["text"],
        }]
    }
    (home / "models.json").write_text(
        json.dumps(catalog, ensure_ascii=False, indent=2) + "\n",
        encoding="utf-8",
    )
    lines.insert(3, "model_catalog_json = " + q(str(home / "models.json")))
path = home / "config.toml"
path.write_text("\n".join(lines) + "\n", encoding="utf-8")
path.chmod(0o600)
print(f"[startup] official Codex config ready: {path}")
PY_CODEX_CONFIG

# ============================================================
# Marine API health check
# ============================================================

if ! curl -fsS --max-time 12 "${MARINE_API_URL%/}/health"; then
  echo "[startup] WARNING: Marine API health check failed. Chat remains available; Ocean tools will be unavailable until MARINE_API_URL is corrected."
fi
echo

# ============================================================
# Start Squid Agent Web UI
# ============================================================

exec uvicorn ui_server:app \
  --host 0.0.0.0 \
  --port "${PORT}" \
  --proxy-headers