feat(agent-client): Claude 및 Pi 에이전트 클라이언트를 위한 설치 스크립트와 README를 추가한다
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30
agent-client/claude/README.md
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agent-client/claude/README.md
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# Claude Agent Client
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기존 Seulgivibe Claude 설정이 되어 있는 macOS 환경에서 Claude TUI `/model`에 아래 모델을 함께 노출한다.
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```text
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claude-seulgivibe-sonnet-4-5
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claude-seulgivibe-opus-4-8
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claude-seulgivibe-mythos-5
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claude-dev-corp-gemma4-26b
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```
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## 설치
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```bash
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cd agent-client/claude
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./install.sh
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```
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설치 후 Claude TUI를 새로 열고 `/model`에서 모델을 선택한다.
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## 전제
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- `~/.claude/anthropic_key.sh`가 이미 설정되어 있어야 한다.
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- dev-corp 토큰은 있으면 아래 순서로 사용한다.
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- `~/.claude/dev-corp-openai-key.sh`
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- `~/.claude/dev-corp-openai-api-key`
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- `~/.pi/agent/dev-corp-openai-api-key`
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- 없으면 `~/.claude/anthropic_key.sh` 출력값을 fallback으로 사용한다.
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JWT/API key 원문은 이 폴더에 포함하지 않는다.
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183
agent-client/claude/install.sh
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183
agent-client/claude/install.sh
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#!/usr/bin/env bash
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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CLAUDE_DIR="$HOME/.claude"
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SETTINGS="$CLAUDE_DIR/settings.json"
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GATEWAY="$CLAUDE_DIR/iop-claude-gateway.py"
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DEV_CORP_KEY_HELPER="$CLAUDE_DIR/dev-corp-openai-key.sh"
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LABEL="com.iop.agent-client.claude"
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PLIST="$HOME/Library/LaunchAgents/$LABEL.plist"
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PYTHON_BIN="/usr/bin/python3"
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UID_VALUE="$(id -u)"
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if [[ ! -x "$PYTHON_BIN" ]]; then
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PYTHON_BIN="$(command -v python3 || true)"
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fi
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if [[ -z "$PYTHON_BIN" || ! -x "$PYTHON_BIN" ]]; then
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echo "python3 를 찾을 수 없습니다."
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exit 1
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fi
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if [[ ! -x "$CLAUDE_DIR/anthropic_key.sh" ]]; then
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echo "~/.claude/anthropic_key.sh 설정이 먼저 필요합니다."
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exit 1
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fi
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mkdir -p "$CLAUDE_DIR/cache" "$HOME/Library/LaunchAgents"
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OLD_LABELS=(
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"$LABEL"
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"com.seulgivibe.claude.models"
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"com.seulgivibe.claude.anthropic-proxy"
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"com.leedongmyung.claude.seulgivibe-anthropic-proxy"
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)
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for old_label in "${OLD_LABELS[@]}"; do
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launchctl bootout "gui/$UID_VALUE/$old_label" >/dev/null 2>&1 || true
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done
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OLD_PLISTS=(
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"$PLIST"
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"$HOME/Library/LaunchAgents/com.seulgivibe.claude.models.plist"
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"$HOME/Library/LaunchAgents/com.seulgivibe.claude.anthropic-proxy.plist"
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"$HOME/Library/LaunchAgents/com.leedongmyung.claude.seulgivibe-anthropic-proxy.plist"
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)
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for old_plist in "${OLD_PLISTS[@]}"; do
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rm -f "$old_plist"
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done
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for old_process in \
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"$CLAUDE_DIR/iop-claude-gateway.py" \
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"$CLAUDE_DIR/seulgivibe-claude-gateway.py" \
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"$CLAUDE_DIR/dev-corp-claude-gateway.py" \
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"$CLAUDE_DIR/seulgivibe-anthropic-proxy.mjs"
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do
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pids="$(pgrep -f "$old_process" || true)"
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if [[ -n "$pids" ]]; then
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while IFS= read -r pid; do
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[[ -n "$pid" && "$pid" != "$$" ]] && kill "$pid" >/dev/null 2>&1 || true
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done <<< "$pids"
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fi
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done
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rm -f "$CLAUDE_DIR/seulgivibe-anthropic-proxy.mjs"
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install -m 755 "$SCRIPT_DIR/iop-claude-gateway.py" "$GATEWAY"
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if [[ ! -x "$DEV_CORP_KEY_HELPER" ]]; then
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cat > "$DEV_CORP_KEY_HELPER" <<'EOF'
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#!/bin/sh
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set -eu
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if [ -f "$HOME/.claude/dev-corp-openai-api-key" ]; then
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tr -d '\n' < "$HOME/.claude/dev-corp-openai-api-key"
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exit 0
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fi
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if [ -f "$HOME/.pi/agent/dev-corp-openai-api-key" ]; then
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tr -d '\n' < "$HOME/.pi/agent/dev-corp-openai-api-key"
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exit 0
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fi
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exec "$HOME/.claude/anthropic_key.sh"
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EOF
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chmod 755 "$DEV_CORP_KEY_HELPER"
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fi
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"$PYTHON_BIN" - "$SETTINGS" "$CLAUDE_DIR/cache/gateway-models.json" <<'PY'
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import json
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import pathlib
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import sys
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import time
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settings_path = pathlib.Path(sys.argv[1])
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cache_path = pathlib.Path(sys.argv[2])
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settings_path.parent.mkdir(parents=True, exist_ok=True)
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cache_path.parent.mkdir(parents=True, exist_ok=True)
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settings = {}
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if settings_path.exists():
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backup = settings_path.with_name(f"{settings_path.name}.bak-{time.strftime('%Y%m%d%H%M%S')}")
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backup.write_bytes(settings_path.read_bytes())
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settings = json.loads(settings_path.read_text() or "{}")
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models = [
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"claude-seulgivibe-sonnet-4-5",
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"claude-seulgivibe-opus-4-8",
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"claude-seulgivibe-mythos-5",
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"claude-dev-corp-gemma4-26b",
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]
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settings["apiKeyHelper"] = settings.get("apiKeyHelper") or "~/.claude/anthropic_key.sh"
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env = settings.setdefault("env", {})
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env["ANTHROPIC_BASE_URL"] = "http://127.0.0.1:18443/anthropic"
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env["NODE_TLS_REJECT_UNAUTHORIZED"] = "0"
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env["CLAUDE_CODE_ENABLE_GATEWAY_MODEL_DISCOVERY"] = "1"
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for key in [
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"ANTHROPIC_CUSTOM_MODEL_OPTION",
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"ANTHROPIC_CUSTOM_MODEL_OPTION_NAME",
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"ANTHROPIC_CUSTOM_MODEL_OPTION_DESCRIPTION",
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"ANTHROPIC_DEFAULT_FABLE_MODEL",
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"ANTHROPIC_DEFAULT_FABLE_MODEL_NAME",
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"ANTHROPIC_DEFAULT_FABLE_MODEL_DESCRIPTION",
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]:
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env.pop(key, None)
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if settings.get("model") not in models:
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settings["model"] = "claude-seulgivibe-mythos-5"
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settings["availableModels"] = models
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settings["enforceAvailableModels"] = True
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settings.setdefault("effortLevel", "xhigh")
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settings.setdefault("alwaysThinkingEnabled", True)
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settings_path.write_text(json.dumps(settings, indent=2, ensure_ascii=False) + "\n")
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cache = {
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"baseUrl": "http://127.0.0.1:18443/anthropic",
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"fetchedAt": int(time.time() * 1000),
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"models": [
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{"id": "claude-seulgivibe-sonnet-4-5", "display_name": "Seulgivibe Sonnet 4.5"},
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{"id": "claude-seulgivibe-opus-4-8", "display_name": "Seulgivibe Opus 4.8"},
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{"id": "claude-seulgivibe-mythos-5", "display_name": "Seulgivibe Fable 5"},
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{"id": "claude-dev-corp-gemma4-26b", "display_name": "dev-corp gemma4:26b"},
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],
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}
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cache_path.write_text(json.dumps(cache, ensure_ascii=False, separators=(",", ":")) + "\n")
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PY
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cat > "$PLIST" <<EOF
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
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<plist version="1.0">
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<dict>
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<key>Label</key>
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<string>$LABEL</string>
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<key>ProgramArguments</key>
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<array>
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<string>$PYTHON_BIN</string>
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<string>$GATEWAY</string>
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</array>
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<key>RunAtLoad</key>
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<true/>
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<key>KeepAlive</key>
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<true/>
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<key>StandardOutPath</key>
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<string>$CLAUDE_DIR/iop-claude-gateway.out.log</string>
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<key>StandardErrorPath</key>
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<string>$CLAUDE_DIR/iop-claude-gateway.err.log</string>
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</dict>
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</plist>
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EOF
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launchctl bootstrap "gui/$UID_VALUE" "$PLIST"
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launchctl kickstart -k "gui/$UID_VALUE/$LABEL"
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for _ in 1 2 3 4 5; do
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curl -fsS "http://127.0.0.1:18443/health" >/dev/null 2>&1 && break
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sleep 1
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done
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curl -fsS "http://127.0.0.1:18443/anthropic/v1/models" >/dev/null
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echo "완료: Claude TUI를 새로 열고 /model 에서 모델을 선택하세요."
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635
agent-client/claude/iop-claude-gateway.py
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635
agent-client/claude/iop-claude-gateway.py
Executable file
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#!/usr/bin/env python3
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import http.client
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import json
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import os
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import ssl
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import subprocess
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import time
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import uuid
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from urllib.parse import urlsplit
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HOST = "127.0.0.1"
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PORT = int(os.environ.get("IOP_CLAUDE_GATEWAY_PORT", "18443"))
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SEULGIVIBE_HOST = os.environ.get("SEULGIVIBE_HOST", "seulgivibe.lgudax.cool")
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SEULGIVIBE_PREFIX = os.environ.get("SEULGIVIBE_ANTHROPIC_PREFIX", "/anthropic")
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SEULGIVIBE_KEY_HELPER = os.path.expanduser("~/.claude/anthropic_key.sh")
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DEV_CORP_OPENAI_BASE_URL = os.environ.get(
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"DEV_CORP_OPENAI_BASE_URL",
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"http://digitalplatform-iop.cloud:18086/v1",
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).rstrip("/")
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DEV_CORP_KEY_HELPER = os.path.expanduser("~/.claude/dev-corp-openai-key.sh")
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DEV_CORP_TOKEN_FILES = [
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os.path.expanduser("~/.claude/dev-corp-openai-api-key"),
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os.path.expanduser("~/.pi/agent/dev-corp-openai-api-key"),
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]
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DEV_CORP_MODEL = "claude-dev-corp-gemma4-26b"
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DEV_CORP_UPSTREAM_MODEL = "gemma4:26b"
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DEV_CORP_MIN_MAX_TOKENS = int(os.environ.get("DEV_CORP_UPSTREAM_MIN_MAX_TOKENS", "1024"))
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SEULGIVIBE_ALIASES = {
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"claude-seulgivibe-sonnet-4-5": "claude-sonnet-4-5-20250929",
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"claude-seulgivibe-opus-4-8": "claude-opus-4-8",
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"claude-seulgivibe-mythos-5": "claude-fable-5",
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}
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MODELS = [
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{
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"id": "claude-seulgivibe-sonnet-4-5",
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"type": "model",
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"display_name": "Seulgivibe Sonnet 4.5",
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"description": "Seulgivibe Sonnet 4.5",
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"created_at": "2026-05-13T00:00:00Z",
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},
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{
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"id": "claude-seulgivibe-opus-4-8",
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"type": "model",
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"display_name": "Seulgivibe Opus 4.8",
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"description": "Seulgivibe Opus 4.8",
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"created_at": "2026-05-13T00:00:00Z",
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},
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{
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"id": "claude-seulgivibe-mythos-5",
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"type": "model",
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"display_name": "Seulgivibe Fable 5",
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"description": "Fable 5 · Most capable for your hardest and longest-running tasks · $10/$50 per Mtok",
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"created_at": "2026-05-13T00:00:00Z",
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},
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{
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"id": DEV_CORP_MODEL,
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"type": "model",
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"display_name": "dev-corp gemma4:26b",
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"description": "dev-corp gemma4:26b via OpenAI-compatible gateway",
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"created_at": "2026-07-10T00:00:00Z",
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},
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]
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def is_record(value):
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return isinstance(value, dict)
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def content_to_text(content):
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts = []
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for item in content:
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if isinstance(item, str):
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parts.append(item)
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elif is_record(item):
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item_type = item.get("type")
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if item_type in ("text", "input_text", "output_text"):
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text = item.get("text")
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if isinstance(text, str):
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parts.append(text)
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elif item_type == "tool_result":
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text = content_to_text(item.get("content"))
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if text:
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parts.append(text)
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return "\n".join(parts)
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return ""
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def normalize_system(system_value):
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if isinstance(system_value, str):
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return system_value
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if isinstance(system_value, list):
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return content_to_text(system_value)
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return ""
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def normalize_system_messages(payload):
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messages = payload.get("messages")
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if not isinstance(messages, list):
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return
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system_parts = []
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regular_messages = []
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for message in messages:
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if is_record(message) and message.get("role") == "system":
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text = content_to_text(message.get("content"))
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if text:
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system_parts.append(text)
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else:
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regular_messages.append(message)
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if not system_parts:
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return
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existing = normalize_system(payload.get("system"))
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payload["system"] = "\n\n".join(part for part in [existing, *system_parts] if part)
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payload["messages"] = regular_messages
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def read_helper(path):
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if not os.path.exists(path):
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return ""
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try:
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result = subprocess.run(
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[path],
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check=True,
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stdout=subprocess.PIPE,
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stderr=subprocess.DEVNULL,
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text=True,
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timeout=10,
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)
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except Exception:
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return ""
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return result.stdout.strip()
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def read_token_file(path):
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try:
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with open(path, "r", encoding="utf-8") as handle:
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return handle.read().strip()
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except Exception:
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return ""
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|
||||
|
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def inbound_token(headers):
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for key in ("authorization", "x-api-key", "api-key"):
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value = headers.get(key)
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if not value:
|
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continue
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value = value.strip()
|
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if value.lower().startswith("bearer "):
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return value[7:].strip()
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return value
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return ""
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|
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def seulgivibe_token(headers):
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return inbound_token(headers) or read_helper(SEULGIVIBE_KEY_HELPER)
|
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|
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|
||||
def dev_corp_token(headers):
|
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token = read_helper(DEV_CORP_KEY_HELPER)
|
||||
if token:
|
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return token
|
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for path in DEV_CORP_TOKEN_FILES:
|
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token = read_token_file(path)
|
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if token:
|
||||
return token
|
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return inbound_token(headers) or read_helper(SEULGIVIBE_KEY_HELPER)
|
||||
|
||||
|
||||
def seulgivibe_path(raw_path):
|
||||
if raw_path.startswith(f"{SEULGIVIBE_PREFIX}/"):
|
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return raw_path
|
||||
if raw_path.startswith("/v1/"):
|
||||
return f"{SEULGIVIBE_PREFIX}{raw_path}"
|
||||
return raw_path
|
||||
|
||||
|
||||
def call_seulgivibe(method, raw_path, payload, inbound_headers):
|
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outbound_payload = dict(payload)
|
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model = outbound_payload.get("model")
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if model in SEULGIVIBE_ALIASES:
|
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normalize_system_messages(outbound_payload)
|
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outbound_payload["model"] = SEULGIVIBE_ALIASES[model]
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||||
|
||||
body = json.dumps(outbound_payload, ensure_ascii=False, separators=(",", ":")).encode("utf-8")
|
||||
headers = {
|
||||
"content-type": "application/json",
|
||||
"accept": inbound_headers.get("accept", "application/json, text/event-stream"),
|
||||
"content-length": str(len(body)),
|
||||
}
|
||||
for key in ("anthropic-version", "anthropic-beta"):
|
||||
if inbound_headers.get(key):
|
||||
headers[key] = inbound_headers[key]
|
||||
token = seulgivibe_token(inbound_headers)
|
||||
if token:
|
||||
headers["authorization"] = f"Bearer {token}"
|
||||
|
||||
context = ssl._create_unverified_context()
|
||||
conn = http.client.HTTPSConnection(SEULGIVIBE_HOST, 443, context=context, timeout=300)
|
||||
try:
|
||||
conn.request(method, seulgivibe_path(raw_path), body=body, headers=headers)
|
||||
response = conn.getresponse()
|
||||
return response.status, dict(response.getheaders()), response.read()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def unwrap_json_string_body(body):
|
||||
try:
|
||||
value = json.loads(body.decode("utf-8"))
|
||||
except Exception:
|
||||
return body
|
||||
if not isinstance(value, str):
|
||||
return body
|
||||
stripped = value.strip()
|
||||
if not stripped.startswith(("{", "[")):
|
||||
return body
|
||||
return stripped.encode("utf-8")
|
||||
|
||||
|
||||
def anthropic_messages_to_openai(payload):
|
||||
messages = []
|
||||
system_text = normalize_system(payload.get("system"))
|
||||
if system_text:
|
||||
messages.append({"role": "system", "content": system_text})
|
||||
|
||||
tool_names = {}
|
||||
for message in payload.get("messages") or []:
|
||||
if not is_record(message):
|
||||
continue
|
||||
role = message.get("role")
|
||||
content = message.get("content")
|
||||
|
||||
if role == "assistant":
|
||||
text_parts = []
|
||||
tool_calls = []
|
||||
blocks = content if isinstance(content, list) else [{"type": "text", "text": content_to_text(content)}]
|
||||
for block in blocks:
|
||||
if not is_record(block):
|
||||
continue
|
||||
block_type = block.get("type")
|
||||
if block_type == "text":
|
||||
text = block.get("text")
|
||||
if isinstance(text, str) and text:
|
||||
text_parts.append(text)
|
||||
elif block_type == "tool_use":
|
||||
tool_id = str(block.get("id") or f"call_{uuid.uuid4().hex[:16]}")
|
||||
name = str(block.get("name") or "")
|
||||
tool_names[tool_id] = name
|
||||
tool_calls.append(
|
||||
{
|
||||
"id": tool_id,
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": name,
|
||||
"arguments": json.dumps(block.get("input") or {}, ensure_ascii=False),
|
||||
},
|
||||
}
|
||||
)
|
||||
openai_message = {"role": "assistant", "content": "\n".join(text_parts) or None}
|
||||
if tool_calls:
|
||||
openai_message["tool_calls"] = tool_calls
|
||||
messages.append(openai_message)
|
||||
continue
|
||||
|
||||
if role == "user":
|
||||
text_parts = []
|
||||
blocks = content if isinstance(content, list) else [{"type": "text", "text": content_to_text(content)}]
|
||||
for block in blocks:
|
||||
if is_record(block) and block.get("type") == "tool_result":
|
||||
tool_call_id = str(block.get("tool_use_id") or "")
|
||||
tool_message = {
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call_id,
|
||||
"content": content_to_text(block.get("content")),
|
||||
}
|
||||
name = tool_names.get(tool_call_id)
|
||||
if name:
|
||||
tool_message["name"] = name
|
||||
messages.append(tool_message)
|
||||
else:
|
||||
text = content_to_text([block])
|
||||
if text:
|
||||
text_parts.append(text)
|
||||
if text_parts:
|
||||
messages.append({"role": "user", "content": "\n".join(text_parts)})
|
||||
continue
|
||||
|
||||
if role in ("system", "developer"):
|
||||
text = content_to_text(content)
|
||||
if text:
|
||||
messages.append({"role": "system", "content": text})
|
||||
|
||||
return messages
|
||||
|
||||
|
||||
def anthropic_tools_to_openai(payload):
|
||||
tools = []
|
||||
for tool in payload.get("tools") or []:
|
||||
if not is_record(tool):
|
||||
continue
|
||||
name = tool.get("name")
|
||||
if not isinstance(name, str) or not name:
|
||||
continue
|
||||
parameters = tool.get("input_schema")
|
||||
if not is_record(parameters):
|
||||
parameters = {"type": "object", "properties": {}}
|
||||
tools.append(
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": name,
|
||||
"description": tool.get("description") or "",
|
||||
"parameters": parameters,
|
||||
},
|
||||
}
|
||||
)
|
||||
return tools
|
||||
|
||||
|
||||
def build_openai_payload(payload):
|
||||
body = {
|
||||
"model": DEV_CORP_UPSTREAM_MODEL,
|
||||
"messages": anthropic_messages_to_openai(payload),
|
||||
"temperature": payload.get("temperature", 0.2),
|
||||
"top_p": payload.get("top_p", 0.95),
|
||||
"stream": False,
|
||||
}
|
||||
max_tokens = payload.get("max_tokens")
|
||||
if isinstance(max_tokens, int) and max_tokens > 0:
|
||||
body["max_tokens"] = max(max_tokens, DEV_CORP_MIN_MAX_TOKENS)
|
||||
else:
|
||||
body["max_tokens"] = DEV_CORP_MIN_MAX_TOKENS
|
||||
tools = anthropic_tools_to_openai(payload)
|
||||
if tools:
|
||||
body["tools"] = tools
|
||||
return body
|
||||
|
||||
|
||||
def parse_openai_url(path):
|
||||
parsed = urlsplit(DEV_CORP_OPENAI_BASE_URL)
|
||||
scheme = parsed.scheme or "http"
|
||||
host = parsed.hostname or ""
|
||||
port = parsed.port
|
||||
prefix = parsed.path.rstrip("/")
|
||||
return scheme, host, port, f"{prefix}{path}"
|
||||
|
||||
|
||||
def call_dev_corp(openai_payload, inbound_headers):
|
||||
scheme, host, port, path = parse_openai_url("/chat/completions")
|
||||
body = json.dumps(openai_payload, ensure_ascii=False, separators=(",", ":")).encode("utf-8")
|
||||
headers = {
|
||||
"content-type": "application/json",
|
||||
"accept": "application/json",
|
||||
"content-length": str(len(body)),
|
||||
}
|
||||
token = dev_corp_token(inbound_headers)
|
||||
if token:
|
||||
headers["authorization"] = f"Bearer {token}"
|
||||
|
||||
if scheme == "https":
|
||||
context = ssl._create_unverified_context()
|
||||
conn = http.client.HTTPSConnection(host, port or 443, context=context, timeout=300)
|
||||
else:
|
||||
conn = http.client.HTTPConnection(host, port or 80, timeout=300)
|
||||
try:
|
||||
conn.request("POST", path, body=body, headers=headers)
|
||||
response = conn.getresponse()
|
||||
return response.status, dict(response.getheaders()), response.read()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def parse_tool_arguments(raw):
|
||||
if not isinstance(raw, str) or raw == "":
|
||||
return {}
|
||||
try:
|
||||
value = json.loads(raw)
|
||||
except Exception:
|
||||
return {"raw": raw}
|
||||
return value if is_record(value) else {"value": value}
|
||||
|
||||
|
||||
def openai_to_anthropic(openai_payload, requested_model):
|
||||
choice = (openai_payload.get("choices") or [{}])[0]
|
||||
message = choice.get("message") or {}
|
||||
finish_reason = choice.get("finish_reason")
|
||||
content = []
|
||||
|
||||
text = message.get("content")
|
||||
if isinstance(text, str) and text:
|
||||
content.append({"type": "text", "text": text})
|
||||
|
||||
tool_calls = message.get("tool_calls") or []
|
||||
for tool_call in tool_calls:
|
||||
if not is_record(tool_call):
|
||||
continue
|
||||
function = tool_call.get("function") or {}
|
||||
content.append(
|
||||
{
|
||||
"type": "tool_use",
|
||||
"id": str(tool_call.get("id") or f"call_{uuid.uuid4().hex[:16]}"),
|
||||
"name": str(function.get("name") or ""),
|
||||
"input": parse_tool_arguments(function.get("arguments")),
|
||||
}
|
||||
)
|
||||
|
||||
usage = openai_payload.get("usage") or {}
|
||||
if tool_calls:
|
||||
stop_reason = "tool_use"
|
||||
elif finish_reason == "length":
|
||||
stop_reason = "max_tokens"
|
||||
else:
|
||||
stop_reason = "end_turn"
|
||||
|
||||
return {
|
||||
"id": openai_payload.get("id") or f"msg_{uuid.uuid4().hex}",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": requested_model or DEV_CORP_MODEL,
|
||||
"content": content or [{"type": "text", "text": ""}],
|
||||
"stop_reason": stop_reason,
|
||||
"stop_sequence": None,
|
||||
"usage": {
|
||||
"input_tokens": int(usage.get("prompt_tokens") or 0),
|
||||
"output_tokens": int(usage.get("completion_tokens") or 0),
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def estimate_tokens(payload):
|
||||
text = normalize_system(payload.get("system"))
|
||||
for message in payload.get("messages") or []:
|
||||
if is_record(message):
|
||||
text += "\n" + content_to_text(message.get("content"))
|
||||
return max(1, len(text) // 4)
|
||||
|
||||
|
||||
class Handler(BaseHTTPRequestHandler):
|
||||
protocol_version = "HTTP/1.1"
|
||||
|
||||
def log_message(self, *_):
|
||||
return
|
||||
|
||||
def read_json(self):
|
||||
length = int(self.headers.get("content-length", "0") or "0")
|
||||
body = self.rfile.read(length) if length > 0 else b"{}"
|
||||
return json.loads(body.decode("utf-8") or "{}")
|
||||
|
||||
def write_json(self, status, payload):
|
||||
body = json.dumps(payload, ensure_ascii=False, separators=(",", ":")).encode("utf-8")
|
||||
self.send_response(status)
|
||||
self.send_header("content-type", "application/json")
|
||||
self.send_header("content-length", str(len(body)))
|
||||
self.send_header("connection", "close")
|
||||
self.end_headers()
|
||||
self.wfile.write(body)
|
||||
self.close_connection = True
|
||||
|
||||
def write_raw(self, status, headers, body):
|
||||
self.send_response(status)
|
||||
for key, value in headers.items():
|
||||
lower_key = key.lower()
|
||||
if lower_key in ("connection", "transfer-encoding", "content-length"):
|
||||
continue
|
||||
self.send_header(key, value)
|
||||
self.send_header("content-length", str(len(body)))
|
||||
self.send_header("connection", "close")
|
||||
self.end_headers()
|
||||
self.wfile.write(body)
|
||||
self.close_connection = True
|
||||
|
||||
def write_sse(self, event, payload):
|
||||
self.wfile.write(f"event: {event}\n".encode("utf-8"))
|
||||
self.wfile.write(b"data: ")
|
||||
self.wfile.write(json.dumps(payload, ensure_ascii=False, separators=(",", ":")).encode("utf-8"))
|
||||
self.wfile.write(b"\n\n")
|
||||
self.wfile.flush()
|
||||
|
||||
def write_anthropic_stream(self, message):
|
||||
self.send_response(200)
|
||||
self.send_header("content-type", "text/event-stream")
|
||||
self.send_header("cache-control", "no-cache")
|
||||
self.send_header("connection", "close")
|
||||
self.end_headers()
|
||||
|
||||
self.write_sse(
|
||||
"message_start",
|
||||
{
|
||||
"type": "message_start",
|
||||
"message": {
|
||||
"id": message["id"],
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": message["model"],
|
||||
"content": [],
|
||||
"stop_reason": None,
|
||||
"stop_sequence": None,
|
||||
"usage": {"input_tokens": message["usage"]["input_tokens"], "output_tokens": 0},
|
||||
},
|
||||
},
|
||||
)
|
||||
for index, block in enumerate(message["content"]):
|
||||
if block.get("type") == "tool_use":
|
||||
start_block = {
|
||||
"type": "tool_use",
|
||||
"id": block.get("id"),
|
||||
"name": block.get("name"),
|
||||
"input": {},
|
||||
}
|
||||
self.write_sse(
|
||||
"content_block_start",
|
||||
{"type": "content_block_start", "index": index, "content_block": start_block},
|
||||
)
|
||||
partial_json = json.dumps(block.get("input") or {}, ensure_ascii=False, separators=(",", ":"))
|
||||
if partial_json:
|
||||
self.write_sse(
|
||||
"content_block_delta",
|
||||
{
|
||||
"type": "content_block_delta",
|
||||
"index": index,
|
||||
"delta": {"type": "input_json_delta", "partial_json": partial_json},
|
||||
},
|
||||
)
|
||||
else:
|
||||
self.write_sse(
|
||||
"content_block_start",
|
||||
{"type": "content_block_start", "index": index, "content_block": {"type": "text", "text": ""}},
|
||||
)
|
||||
text = block.get("text") or ""
|
||||
if text:
|
||||
self.write_sse(
|
||||
"content_block_delta",
|
||||
{
|
||||
"type": "content_block_delta",
|
||||
"index": index,
|
||||
"delta": {"type": "text_delta", "text": text},
|
||||
},
|
||||
)
|
||||
self.write_sse("content_block_stop", {"type": "content_block_stop", "index": index})
|
||||
|
||||
self.write_sse(
|
||||
"message_delta",
|
||||
{
|
||||
"type": "message_delta",
|
||||
"delta": {"stop_reason": message["stop_reason"], "stop_sequence": None},
|
||||
"usage": {"output_tokens": message["usage"]["output_tokens"]},
|
||||
},
|
||||
)
|
||||
self.write_sse("message_stop", {"type": "message_stop"})
|
||||
self.close_connection = True
|
||||
|
||||
def do_GET(self):
|
||||
path = urlsplit(self.path).path
|
||||
if path == "/health":
|
||||
self.write_json(200, {"ok": True, "models": [model["id"] for model in MODELS]})
|
||||
return
|
||||
if path in ("/v1/models", "/anthropic/v1/models"):
|
||||
self.write_json(200, {"data": MODELS, "first_id": MODELS[0]["id"], "last_id": MODELS[-1]["id"], "has_more": False})
|
||||
return
|
||||
self.write_json(404, {"type": "error", "error": {"type": "not_found_error", "message": path}})
|
||||
|
||||
def do_POST(self):
|
||||
path = urlsplit(self.path).path
|
||||
is_count_tokens = path in ("/v1/messages/count_tokens", "/anthropic/v1/messages/count_tokens")
|
||||
is_messages = path in ("/v1/messages", "/anthropic/v1/messages")
|
||||
if not is_count_tokens and not is_messages:
|
||||
self.write_json(404, {"type": "error", "error": {"type": "not_found_error", "message": path}})
|
||||
return
|
||||
|
||||
try:
|
||||
payload = self.read_json()
|
||||
except Exception as exc:
|
||||
self.write_json(400, {"type": "error", "error": {"type": "invalid_request_error", "message": str(exc)}})
|
||||
return
|
||||
|
||||
headers = {key.lower(): value for key, value in self.headers.items()}
|
||||
if payload.get("model") == DEV_CORP_MODEL:
|
||||
if is_count_tokens:
|
||||
self.write_json(200, {"input_tokens": estimate_tokens(payload)})
|
||||
return
|
||||
openai_payload = build_openai_payload(payload)
|
||||
status, _, body = call_dev_corp(openai_payload, headers)
|
||||
if status < 200 or status >= 300:
|
||||
try:
|
||||
detail = json.loads(body.decode("utf-8"))
|
||||
except Exception:
|
||||
detail = body.decode("utf-8", "replace")
|
||||
self.write_json(
|
||||
502,
|
||||
{
|
||||
"type": "error",
|
||||
"error": {
|
||||
"type": "upstream_error",
|
||||
"message": f"dev-corp upstream returned HTTP {status}",
|
||||
"detail": detail,
|
||||
},
|
||||
},
|
||||
)
|
||||
return
|
||||
try:
|
||||
openai_response = json.loads(body.decode("utf-8"))
|
||||
except Exception as exc:
|
||||
self.write_json(502, {"type": "error", "error": {"type": "upstream_parse_error", "message": str(exc)}})
|
||||
return
|
||||
message = openai_to_anthropic(openai_response, payload.get("model"))
|
||||
if payload.get("stream") is True:
|
||||
self.write_anthropic_stream(message)
|
||||
else:
|
||||
self.write_json(200, message)
|
||||
return
|
||||
|
||||
status, response_headers, body = call_seulgivibe(self.command, path, payload, headers)
|
||||
if 200 <= status < 300:
|
||||
body = unwrap_json_string_body(body)
|
||||
self.write_raw(status, response_headers, body)
|
||||
|
||||
|
||||
class Server(ThreadingHTTPServer):
|
||||
allow_reuse_address = True
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"iop claude gateway listening on http://{HOST}:{PORT} at {time.strftime('%Y-%m-%d %H:%M:%S')}", flush=True)
|
||||
Server((HOST, PORT), Handler).serve_forever()
|
||||
34
agent-client/pi/README.md
Normal file
34
agent-client/pi/README.md
Normal file
|
|
@ -0,0 +1,34 @@
|
|||
# Pi Agent Client
|
||||
|
||||
Pi Coding Agent에 Seulgivibe Codex/OpenAI 모델과 Claude 모델을 함께 등록한다.
|
||||
|
||||
등록 대상:
|
||||
|
||||
```text
|
||||
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
|
||||
```
|
||||
|
||||
## 설치
|
||||
|
||||
```bash
|
||||
cd agent-client/pi
|
||||
./install.sh
|
||||
```
|
||||
|
||||
설치 후 이미 실행 중인 Pi session은 `/reload` 하거나 재시작한다.
|
||||
|
||||
새 설정 파일을 만드는 환경에서는 기본 모델을 `seulgivibe-codex/gpt-5.5`로 둔다. 기존 기본값이 있으면 보존한다.
|
||||
|
||||
## 전제
|
||||
|
||||
- Pi는 이미 설치되어 있어야 한다.
|
||||
- 기존 `~/.pi/agent/settings.json`, `~/.pi/agent/models.json`의 개인 설정과 API key는 보존한다.
|
||||
- Seulgivibe key가 없으면 `~/.claude/anthropic_key.sh`에서 읽어 넣는다.
|
||||
- 기존 `seulgivibe-openai` 설정은 `seulgivibe-codex`로 이관한 뒤 제거한다.
|
||||
- 기존 dev-corp 설정이 있으면 지우지 않고 보존한다.
|
||||
|
||||
JWT/API key 원문은 이 폴더에 포함하지 않는다.
|
||||
222
agent-client/pi/install.sh
Executable file
222
agent-client/pi/install.sh
Executable file
|
|
@ -0,0 +1,222 @@
|
|||
#!/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."
|
||||
Loading…
Reference in a new issue