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

PI_DIR="$HOME/.pi/agent"
SETTINGS="$PI_DIR/settings.json"
MODELS="$PI_DIR/models.json"
PYTHON_BIN="/usr/bin/python3"

if [[ ! -x "$PYTHON_BIN" ]]; then
  PYTHON_BIN="$(command -v python3 || true)"
fi

if [[ -z "$PYTHON_BIN" || ! -x "$PYTHON_BIN" ]]; then
  echo "python3 를 찾을 수 없습니다."
  exit 1
fi

mkdir -p "$PI_DIR"

"$PYTHON_BIN" - "$SETTINGS" "$MODELS" <<'PY'
import json
import pathlib
import subprocess
import sys
import time

settings_path = pathlib.Path(sys.argv[1]).expanduser()
models_path = pathlib.Path(sys.argv[2]).expanduser()


def read_json(path):
    if not path.exists():
        return {}
    return json.loads(path.read_text() or "{}")


def write_json(path, value):
    if path.exists():
        backup = path.with_name(f"{path.name}.bak-{time.strftime('%Y%m%d%H%M%S')}")
        backup.write_bytes(path.read_bytes())
    path.write_text(json.dumps(value, indent=2, ensure_ascii=False) + "\n")


def run_helper(path):
    expanded = pathlib.Path(path).expanduser()
    if not expanded.exists():
        return ""
    try:
        result = subprocess.run(
            [str(expanded)],
            check=True,
            stdout=subprocess.PIPE,
            stderr=subprocess.DEVNULL,
            text=True,
            timeout=10,
        )
    except Exception:
        return ""
    return result.stdout.strip()


def merge_desired_models(existing_models, desired_models):
    existing_by_id = {}
    for existing in existing_models:
        if isinstance(existing, dict) and isinstance(existing.get("id"), str):
            existing_by_id.setdefault(existing["id"], existing)

    merged_models = []
    for desired in desired_models:
        merged = dict(existing_by_id.get(desired["id"], {}))
        merged.update(desired)
        merged_models.append(merged)
    return merged_models


def zero_cost():
    return {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0}


settings = read_json(settings_path)
models_doc = read_json(models_path)

providers = models_doc.setdefault("providers", {})

seulgivibe_provider = providers.setdefault("seulgivibe-claude", {})
seulgivibe_api_key = seulgivibe_provider.get("apiKey") or run_helper("~/.claude/anthropic_key.sh")
seulgivibe_provider.update(
    {
        "baseUrl": "https://seulgivibe.lgudax.cool/anthropic",
        "api": "anthropic-messages",
        "authHeader": True,
        "compat": {"supportsEagerToolInputStreaming": False},
    }
)
if seulgivibe_api_key:
    seulgivibe_provider["apiKey"] = seulgivibe_api_key
seulgivibe_provider["models"] = merge_desired_models(
    seulgivibe_provider.get("models", []),
    [
    {
        "id": "claude-sonnet-4-5",
        "name": "Seulgivibe Claude Sonnet 4.5",
        "reasoning": True,
        "input": ["text"],
        "contextWindow": 200000,
        "maxTokens": 64000,
        "cost": zero_cost(),
    },
    {
        "id": "claude-opus-4-8",
        "name": "Seulgivibe Claude Opus 4.8",
        "reasoning": True,
        "thinkingLevelMap": {"xhigh": "xhigh"},
        "input": ["text"],
        "contextWindow": 1000000,
        "maxTokens": 128000,
        "compat": {"forceAdaptiveThinking": True, "supportsTemperature": False},
        "cost": zero_cost(),
    },
    {
        "id": "claude-fable-5",
        "name": "Seulgivibe Claude Fable 5",
        "reasoning": True,
        "thinkingLevelMap": {"xhigh": "xhigh"},
        "input": ["text"],
        "contextWindow": 1000000,
        "maxTokens": 128000,
        "compat": {"forceAdaptiveThinking": True, "supportsTemperature": False},
        "cost": zero_cost(),
    },
    ],
)

legacy_openai_provider = providers.get("seulgivibe-openai")
if not isinstance(legacy_openai_provider, dict):
    legacy_openai_provider = {}

seulgivibe_codex_provider = providers.setdefault("seulgivibe-codex", {})
seulgivibe_codex_api_key = (
    seulgivibe_codex_provider.get("apiKey")
    or legacy_openai_provider.get("apiKey")
    or run_helper("~/.claude/anthropic_key.sh")
)
seulgivibe_codex_provider.update(
    {
        "baseUrl": "https://seulgivibe.lgudax.cool/openai/v1",
        "api": "openai-responses",
    }
)
if seulgivibe_codex_api_key:
    seulgivibe_codex_provider["apiKey"] = seulgivibe_codex_api_key
seulgivibe_codex_provider["models"] = merge_desired_models(
    seulgivibe_codex_provider.get("models", []),
    [
    {
        "id": "gpt-5.1",
        "name": "Seulgivibe Codex GPT-5.1",
        "reasoning": True,
        "thinkingLevelMap": {"off": "none"},
        "input": ["text"],
        "contextWindow": 400000,
        "maxTokens": 128000,
        "cost": zero_cost(),
    },
    {
        "id": "gpt-5.5",
        "name": "Seulgivibe Codex GPT-5.5",
        "reasoning": True,
        "thinkingLevelMap": {"off": "none", "xhigh": "xhigh", "minimal": None},
        "input": ["text"],
        "contextWindow": 272000,
        "maxTokens": 128000,
        "cost": zero_cost(),
    },
    ],
)
providers.pop("seulgivibe-openai", None)

settings.setdefault("defaultProvider", "seulgivibe-codex")
settings.setdefault("defaultModel", "gpt-5.5")
settings.setdefault("defaultThinkingLevel", "high")
settings.setdefault("hideThinkingBlock", False)
settings["httpIdleTimeoutMs"] = 300000
retry = settings.setdefault("retry", {})
provider_retry = retry.setdefault("provider", {})
provider_retry["timeoutMs"] = 300000
provider_retry["maxRetries"] = 0
provider_retry["maxRetryDelayMs"] = 60000

enabled = settings.setdefault("enabledModels", [])
if not isinstance(enabled, list):
    enabled = []
desired_enabled = [
    "seulgivibe-codex/gpt-5.1:medium",
    "seulgivibe-codex/gpt-5.5:xhigh",
    "seulgivibe-claude/claude-sonnet-4-5",
    "seulgivibe-claude/claude-opus-4-8",
    "seulgivibe-claude/claude-fable-5",
]
normalized_enabled = []
seen_enabled = set()
for item in enabled:
    if not isinstance(item, str):
        continue
    if item.startswith("seulgivibe-openai/"):
        continue
    if item.startswith("seulgivibe-codex/") or item.startswith("seulgivibe-claude/"):
        continue
    if item not in seen_enabled:
        normalized_enabled.append(item)
        seen_enabled.add(item)
for item in desired_enabled:
    if item not in seen_enabled:
        normalized_enabled.append(item)
        seen_enabled.add(item)
settings["enabledModels"] = normalized_enabled

write_json(settings_path, settings)
write_json(models_path, models_doc)
PY

echo "완료: Pi session에서 /reload 하거나 Pi를 재시작하세요."