4b45d33142
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API contract / OpenAPI type drift (push) Failing after 12m57s
관리자 /admin/ai 화면에서 provider 토큰(OAuth 액세스 토큰 또는 API 키)을 발급받아 붙여넣으면 DB에 암호화 저장되고, shared-secret으로 보호되는 게이트웨이 내부 엔드포인트로 push되어 실행 중인 엔진 컨테이너에 즉시 적용된다. NAS처럼 게이트웨이가 컨테이너로 도는 환경에서 CLI·로컬 PC 의존 없이 claude_api·openai·openrouter를 연결할 수 있다. - 게이트웨이: openrouter 어댑터 신설(chat/completions), OAuth 토큰이면 Anthropic Bearer 헤더, /internal/provider-credentials GET/POST와 boot_id 기반 재동기화 - API: app.admin_provider_credential 테이블(idempotent DDL), stdlib HMAC-CTR+MAC 암호화 서비스(PROVIDER_CREDENTIAL_SECRET, 폴백 SESSION_SECRET), /admin/providers CRUD·검증 라우트 - 웹: 제공자 연결 패널(저장·검증·해제, 토큰 힌트만 표시), 엔진 선택에 OpenRouter 추가, api.gen.ts 재생성 - compose: api 서비스에 PROVIDER_CREDENTIAL_SECRET 전달(로컬·NAS)
1337 lines
49 KiB
Python
1337 lines
49 KiB
Python
"""Provider 탐색과 Claude CLI 이외 실행 어댑터.
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Provider별 CLI/API 세부 구현은 게이트웨이가 소유한다. 애플리케이션과 맞닿는
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wire 계약은 ``app.contracts.engine_gateway``에 유지한다.
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"""
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from __future__ import annotations
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import asyncio
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import json
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import os
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import shutil
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import tempfile
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import time
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from dataclasses import dataclass
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any, AsyncIterator, Iterable, Literal, cast
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import httpx
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from app.contracts.engine_gateway import (
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ENGINE_PROVIDER_DEFAULTS,
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ENGINE_REASONING_EFFORTS,
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EngineCapabilitiesResponse,
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EngineModelOption,
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EngineProvider,
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GenerateRequest,
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ReasoningEffort,
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normalize_engine_gateway_model,
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)
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from app.services.llm_pricing import estimate_reference_cost
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CODEX_DEFAULT_MODEL, CODEX_DEFAULT_EFFORT = ENGINE_PROVIDER_DEFAULTS["codex_cli"]
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AGY_DEFAULT_MODEL, AGY_DEFAULT_EFFORT = ENGINE_PROVIDER_DEFAULTS["agy_cli"]
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CLAUDE_CLI_DEFAULT_MODEL, CLAUDE_DEFAULT_EFFORT = ENGINE_PROVIDER_DEFAULTS[
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"claude_cli"
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]
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CAPABILITY_CACHE_TTL_SECONDS = float(
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os.environ.get("ENGINE_CAPABILITY_CACHE_TTL_SECONDS", "60")
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)
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CLI_TIMEOUT_SECONDS = float(os.environ.get("ENGINE_CLI_TIMEOUT_SECONDS", "300"))
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ANTHROPIC_API_BASE = os.environ.get(
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"ANTHROPIC_API_BASE", "https://api.anthropic.com"
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).rstrip("/")
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OPENAI_API_BASE = os.environ.get(
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"OPENAI_BASE_URL", "https://api.openai.com/v1"
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).rstrip("/")
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OPENROUTER_API_BASE = os.environ.get(
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"OPENROUTER_API_BASE", "https://openrouter.ai/api/v1"
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).rstrip("/")
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_OPENAI_DEFAULT_ENGINE_MODELS = (
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"gpt-5.6-terra",
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"gpt-5.6-luna",
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"gpt-4.1",
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)
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class ProviderError(RuntimeError):
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"""자격 증명을 노출하지 않고 provider 탐색·생성 실패를 전달한다."""
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@dataclass(frozen=True, slots=True)
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class ProviderGenerateResult:
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text: str
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model: str
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provider: EngineProvider
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tokens_in: int = 0
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tokens_out: int = 0
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cost_usd: float = 0.0
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inference_geo: str | None = None
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structured: dict[str, Any] | None = None
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@dataclass(frozen=True, slots=True)
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class ProviderStreamEvent:
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type: Literal["delta", "done"]
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text: str = ""
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result: ProviderGenerateResult | None = None
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_CAPABILITY_CACHE: dict[EngineProvider, tuple[float, EngineCapabilitiesResponse]] = {}
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_CAPABILITY_LOCK = asyncio.Lock()
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# 관리자 연결 UI가 push한 자격증명의 종류(api_key | oauth_token). 토큰 값 자체는
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# os.environ으로만 들어가고 여기엔 어떤 헤더로 보낼지 판정하는 힌트만 둔다.
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_PROVIDER_AUTH_KINDS: dict[str, str] = {}
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def set_provider_auth_kind(provider: str, auth_kind: str) -> None:
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if auth_kind in {"api_key", "oauth_token"}:
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_PROVIDER_AUTH_KINDS[provider] = auth_kind
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else:
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_PROVIDER_AUTH_KINDS.pop(provider, None)
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def get_provider_auth_kind(provider: str) -> str:
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return _PROVIDER_AUTH_KINDS.get(provider, "api_key")
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def _anthropic_headers(api_key: str) -> dict[str, str]:
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"""Anthropic 인증 헤더. OAuth 액세스 토큰은 x-api-key 대신 Bearer를 쓴다."""
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if get_provider_auth_kind("claude") == "oauth_token":
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return {
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"Authorization": f"Bearer {api_key}",
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"anthropic-version": "2023-06-01",
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}
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return {
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"x-api-key": api_key,
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"anthropic-version": "2023-06-01",
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}
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def clear_capability_cache() -> None:
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_CAPABILITY_CACHE.clear()
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def _now() -> float:
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return time.time()
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def _utcnow() -> datetime:
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return datetime.now(timezone.utc)
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def _efforts(values: Iterable[str]) -> list[ReasoningEffort]:
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allowed = set(ENGINE_REASONING_EFFORTS)
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return [cast(ReasoningEffort, value) for value in values if value in allowed]
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def _configured_openai_models() -> list[str]:
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"""운영 엔진에 노출할 OpenAI 텍스트 모델을 명시 allowlist로 제한한다."""
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raw = os.environ.get("OPENAI_ENGINE_MODELS", "").strip()
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candidates = (
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[item.strip() for item in raw.split(",")]
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if raw
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else list(_OPENAI_DEFAULT_ENGINE_MODELS)
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)
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configured_default = os.environ.get("OPENAI_ENGINE_MODEL", "").strip()
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if configured_default:
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candidates.insert(0, configured_default)
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result: list[str] = []
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for model in candidates:
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if not model or model in result:
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continue
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if any(character.isspace() for character in model) or "/" in model:
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raise ProviderError("OPENAI_ENGINE_MODELS에 유효하지 않은 모델 식별자가 있습니다.")
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result.append(model)
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if not result:
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raise ProviderError("OPENAI_ENGINE_MODELS가 비어 있습니다.")
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return result
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def _openai_reasoning_efforts(model: str) -> list[ReasoningEffort]:
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# API 모델 목록은 추론 강도 메타데이터를 제공하지 않는다. 운영 기본값으로 쓰는
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# GPT-5 계열에는 여러 세대가 공통 지원하는 보수적 교집합만 노출한다.
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if model.startswith("gpt-5"):
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return ["low", "medium", "high"]
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return []
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def _binary(env_name: str, fallback: str) -> str | None:
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configured = os.environ.get(env_name, "").strip()
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if configured:
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path = Path(configured)
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return str(path) if path.exists() else shutil.which(configured)
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if os.name == "nt":
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shim = shutil.which(fallback)
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if fallback == "codex" and shim:
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npm_vendor_root = (
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Path(shim).parent
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/ "node_modules"
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/ "@openai"
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/ "codex"
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/ "node_modules"
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/ "@openai"
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)
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native_candidates = sorted(
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npm_vendor_root.glob("codex-win32-*/vendor/*/bin/codex.exe")
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)
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if native_candidates:
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return str(native_candidates[0])
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executable = shutil.which(f"{fallback}.exe")
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if executable:
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return executable
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if fallback == "agy":
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# agy 인스톨러의 Windows 표준 위치(%LOCALAPPDATA%\agy\bin). PATH에
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# 올라 있지 않은 머신에서도 게이트웨이가 공급자를 잃지 않게 한다.
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local_app_data = os.environ.get("LOCALAPPDATA", "")
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if local_app_data:
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well_known = Path(local_app_data) / "agy" / "bin" / "agy.exe"
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if well_known.exists():
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return str(well_known)
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return shim
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return shutil.which(fallback)
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def _safe_process_error(stderr: bytes, fallback: str) -> str:
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detail = stderr.decode("utf-8", errors="replace").strip()
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if not detail:
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return fallback
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return detail[-1200:]
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# Windows 필수 변수의 표준 기본값 — 승격 체인의 psutil 환경 이식에서 유실될 수 있다.
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_WINDOWS_ESSENTIAL_ENV_DEFAULTS = {
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"SystemRoot": r"C:\Windows",
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"SystemDrive": "C:",
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"ComSpec": r"C:\Windows\system32\cmd.exe",
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}
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def _cli_subprocess_env() -> dict[str, str]:
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"""CLI 자식 프로세스에 물려줄 환경.
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공개 런타임 승격은 이전 프로세스 환경을 psutil로 통째로 이식하는데, 이 캡처에서
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SystemRoot 같은 Windows 필수 변수가 유실되면 Go 계열 CLI(agy)가 시스템 인증서
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풀·홈 디렉터리 해석에 실패하고 빈 모델 목록을 조용히 내놓는다(2026-08-18 실측).
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상속 환경에서 빠진 필수 키만 기본값으로 채운다.
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"""
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env = dict(os.environ)
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if os.name == "nt":
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# os.environ은 Windows에서 키를 대문자로 정규화하므로 대소문자 무시 조회한다.
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upper_names = {key.upper(): key for key in env}
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for name, default in _WINDOWS_ESSENTIAL_ENV_DEFAULTS.items():
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existing = upper_names.get(name.upper())
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if existing is None or not env[existing]:
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env[name] = default
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return env
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async def _run_process(
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args: list[str],
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*,
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input_text: str | None = None,
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cwd: str | None = None,
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timeout: float = CLI_TIMEOUT_SECONDS,
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) -> tuple[str, str]:
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proc = await asyncio.create_subprocess_exec(
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*args,
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stdin=asyncio.subprocess.PIPE if input_text is not None else asyncio.subprocess.DEVNULL,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE,
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cwd=cwd,
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env=_cli_subprocess_env(),
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)
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try:
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stdout, stderr = await asyncio.wait_for(
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proc.communicate(
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input_text.encode("utf-8") if input_text is not None else None
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),
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timeout=timeout,
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)
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except TimeoutError as exc:
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proc.kill()
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await proc.wait()
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raise ProviderError(f"provider 명령이 {timeout:.0f}초 안에 끝나지 않았습니다.") from exc
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if proc.returncode != 0:
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raise ProviderError(
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_safe_process_error(stderr, f"provider 명령 실패: 종료 코드 {proc.returncode}")
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)
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return (
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stdout.decode("utf-8", errors="replace"),
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stderr.decode("utf-8", errors="replace"),
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)
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def _unavailable(provider: EngineProvider, detail: str) -> EngineCapabilitiesResponse:
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return EngineCapabilitiesResponse(
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provider=provider,
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available=False,
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source="unavailable",
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detail=detail,
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fetched_at=_now(),
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)
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def _display_model_name(model_id: str) -> str:
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parts = model_id.split("-")
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effort = parts[-1] if parts and parts[-1] in {"low", "medium", "high"} else None
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if effort:
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parts = parts[:-1]
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words: list[str] = []
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for part in parts:
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if part.lower() in {"gpt", "oss"}:
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words.append(part.upper())
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elif any(char.isdigit() for char in part):
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words.append(part)
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else:
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words.append(part.capitalize())
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label = " ".join(words)
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return f"{label} ({effort.capitalize()})" if effort else label
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async def _discover_claude_cli() -> EngineCapabilitiesResponse:
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if _binary("CLAUDE_BIN", "claude") is None:
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return _unavailable("claude_cli", "Claude CLI를 찾을 수 없습니다.")
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efforts = _efforts(("low", "medium", "high", "xhigh", "max"))
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models = [
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EngineModelOption(
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id=CLAUDE_CLI_DEFAULT_MODEL,
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label="Claude CLI 기본 모델",
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description="로그인된 Claude CLI가 권장하는 기본 모델을 사용합니다.",
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reasoning_efforts=efforts,
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default_reasoning_effort=CLAUDE_DEFAULT_EFFORT,
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is_default=True,
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),
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*[
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EngineModelOption(
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id=model,
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label=f"Claude {model.capitalize()} 최신",
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description="Claude CLI가 제공하는 안정 alias입니다.",
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reasoning_efforts=efforts,
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default_reasoning_effort=CLAUDE_DEFAULT_EFFORT,
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)
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for model in ("opus", "sonnet", "fable")
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],
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]
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return EngineCapabilitiesResponse(
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provider="claude_cli",
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available=True,
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source="static_cli",
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models=models,
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default_model=CLAUDE_CLI_DEFAULT_MODEL,
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default_reasoning_effort=CLAUDE_DEFAULT_EFFORT,
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detail="Claude CLI는 모델 목록 명령이 없어 공식 alias를 사용합니다.",
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fetched_at=_now(),
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)
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async def _codex_model_list(binary: str) -> dict[str, Any]:
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proc = await asyncio.create_subprocess_exec(
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binary,
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"app-server",
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stdin=asyncio.subprocess.PIPE,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE,
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env=_cli_subprocess_env(),
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)
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if proc.stdin is None or proc.stdout is None:
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proc.kill()
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await proc.wait()
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raise ProviderError("Codex app-server stdio를 열 수 없습니다.")
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messages = (
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{
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"method": "initialize",
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"id": 0,
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"params": {
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"clientInfo": {
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"name": "vignette_engine_gateway",
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"title": "Vignette Engine Gateway",
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"version": "1.0.0",
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}
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},
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},
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{"method": "initialized", "params": {}},
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{
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"method": "model/list",
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"id": 6,
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"params": {"limit": 100, "includeHidden": False},
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},
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)
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for message in messages:
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proc.stdin.write((json.dumps(message) + "\n").encode("utf-8"))
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await proc.stdin.drain()
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try:
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while True:
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raw = await asyncio.wait_for(proc.stdout.readline(), timeout=20)
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if not raw:
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raise ProviderError("Codex model/list 응답이 비어 있습니다.")
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try:
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message = json.loads(raw)
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except json.JSONDecodeError:
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continue
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if message.get("id") == 6:
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if message.get("error"):
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raise ProviderError(str(message["error"].get("message") or message["error"]))
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return cast(dict[str, Any], message.get("result") or {})
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except TimeoutError as exc:
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raise ProviderError("Codex model/list 응답 시간이 초과됐습니다.") from exc
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finally:
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if proc.stdin is not None and not proc.stdin.is_closing():
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proc.stdin.close()
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if proc.returncode is None:
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try:
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await asyncio.wait_for(proc.wait(), timeout=2)
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except TimeoutError:
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proc.kill()
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await proc.wait()
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async def _discover_codex_cli() -> EngineCapabilitiesResponse:
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binary = _binary("CODEX_BIN", "codex")
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if binary is None:
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return _unavailable("codex_cli", "Codex CLI를 찾을 수 없습니다.")
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try:
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payload = await _codex_model_list(binary)
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except (OSError, ProviderError) as exc:
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return _unavailable("codex_cli", f"Codex 모델 조회 실패: {exc}")
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raw_models = payload.get("data") if isinstance(payload, dict) else []
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models: list[EngineModelOption] = []
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for item in raw_models if isinstance(raw_models, list) else []:
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if not isinstance(item, dict) or item.get("hidden"):
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continue
|
|
model_id = str(item.get("model") or item.get("id") or "").strip()
|
|
if not model_id:
|
|
continue
|
|
supported = item.get("supportedReasoningEfforts") or []
|
|
efforts = _efforts(
|
|
str(entry.get("reasoningEffort") or "")
|
|
for entry in supported
|
|
if isinstance(entry, dict)
|
|
)
|
|
raw_default = str(item.get("defaultReasoningEffort") or "")
|
|
default_effort = (
|
|
cast(ReasoningEffort, raw_default)
|
|
if raw_default in efforts
|
|
else (efforts[0] if efforts else None)
|
|
)
|
|
models.append(
|
|
EngineModelOption(
|
|
id=model_id,
|
|
label=str(item.get("displayName") or model_id),
|
|
description=str(item.get("description") or ""),
|
|
reasoning_efforts=efforts,
|
|
default_reasoning_effort=default_effort,
|
|
is_default=model_id == CODEX_DEFAULT_MODEL,
|
|
)
|
|
)
|
|
if not models:
|
|
return _unavailable("codex_cli", "Codex가 선택 가능한 모델을 반환하지 않았습니다.")
|
|
|
|
default_model = (
|
|
CODEX_DEFAULT_MODEL
|
|
if any(model.id == CODEX_DEFAULT_MODEL for model in models)
|
|
else next((model.id for model in models if model.is_default), models[0].id)
|
|
)
|
|
selected = next(model for model in models if model.id == default_model)
|
|
default_effort = (
|
|
CODEX_DEFAULT_EFFORT
|
|
if CODEX_DEFAULT_EFFORT in selected.reasoning_efforts
|
|
else selected.default_reasoning_effort
|
|
)
|
|
return EngineCapabilitiesResponse(
|
|
provider="codex_cli",
|
|
available=True,
|
|
source="live_cli",
|
|
models=models,
|
|
default_model=default_model,
|
|
default_reasoning_effort=default_effort,
|
|
detail="Codex app-server model/list에서 실시간 조회했습니다.",
|
|
fetched_at=_now(),
|
|
)
|
|
|
|
|
|
async def _discover_agy_cli() -> EngineCapabilitiesResponse:
|
|
binary = _binary("AGY_BIN", "agy")
|
|
if binary is None:
|
|
return _unavailable("agy_cli", "Agy CLI를 찾을 수 없습니다.")
|
|
try:
|
|
stdout, _ = await _run_process([binary, "models"], timeout=30)
|
|
except (OSError, ProviderError) as exc:
|
|
return _unavailable("agy_cli", f"Agy 모델 조회 실패: {exc}")
|
|
|
|
models: list[EngineModelOption] = []
|
|
for line in stdout.splitlines():
|
|
# agy CLI는 2026-08부터 "model_id\t표시 라벨" 형태로 출력한다. 탭 왼쪽 토큰이
|
|
# 모델 id고 라벨은 CLI가 준 값을 우선한다. 탭 없이 공백이 섞인 줄은 상태/안내
|
|
# 문구이므로 건너뛴다(구형 베어 id 출력 계약은 그대로 유지).
|
|
label: str | None = None
|
|
if "\t" in line:
|
|
model_id, _, rest = line.partition("\t")
|
|
model_id = model_id.strip()
|
|
label = rest.strip() or None
|
|
if not model_id:
|
|
continue
|
|
else:
|
|
model_id = line.strip()
|
|
if not model_id or any(char.isspace() for char in model_id):
|
|
continue
|
|
suffix = model_id.rsplit("-", 1)[-1]
|
|
if suffix in {"low", "medium", "high"}:
|
|
efforts = _efforts((suffix,))
|
|
default_effort = cast(ReasoningEffort, suffix)
|
|
else:
|
|
efforts = _efforts(("low", "medium", "high"))
|
|
default_effort = AGY_DEFAULT_EFFORT if model_id == AGY_DEFAULT_MODEL else "medium"
|
|
models.append(
|
|
EngineModelOption(
|
|
id=model_id,
|
|
label=label or _display_model_name(model_id),
|
|
description="Agy CLI가 현재 계정에 노출한 모델입니다.",
|
|
reasoning_efforts=efforts,
|
|
default_reasoning_effort=default_effort,
|
|
is_default=model_id == AGY_DEFAULT_MODEL,
|
|
)
|
|
)
|
|
if not models:
|
|
return _unavailable("agy_cli", "Agy가 선택 가능한 모델을 반환하지 않았습니다.")
|
|
default_model = (
|
|
AGY_DEFAULT_MODEL
|
|
if any(model.id == AGY_DEFAULT_MODEL for model in models)
|
|
else models[0].id
|
|
)
|
|
selected = next(model for model in models if model.id == default_model)
|
|
return EngineCapabilitiesResponse(
|
|
provider="agy_cli",
|
|
available=True,
|
|
source="live_cli",
|
|
models=models,
|
|
default_model=default_model,
|
|
default_reasoning_effort=selected.default_reasoning_effort,
|
|
detail="agy models에서 실시간 조회했습니다.",
|
|
fetched_at=_now(),
|
|
)
|
|
|
|
|
|
async def _discover_claude_api() -> EngineCapabilitiesResponse:
|
|
api_key = os.environ.get("ANTHROPIC_API_KEY", "").strip() or os.environ.get(
|
|
"ANTHROPIC_AUTH_TOKEN", ""
|
|
).strip()
|
|
if not api_key:
|
|
return _unavailable("claude_api", "ANTHROPIC_API_KEY가 설정되지 않았습니다.")
|
|
try:
|
|
async with httpx.AsyncClient(timeout=20) as client:
|
|
response = await client.get(
|
|
f"{ANTHROPIC_API_BASE}/v1/models",
|
|
params={"limit": 100},
|
|
headers={**_anthropic_headers(api_key)},
|
|
)
|
|
response.raise_for_status()
|
|
payload = response.json()
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
return _unavailable("claude_api", f"Anthropic 모델 조회 실패: {exc}")
|
|
|
|
models: list[EngineModelOption] = []
|
|
for item in payload.get("data", []) if isinstance(payload, dict) else []:
|
|
if not isinstance(item, dict):
|
|
continue
|
|
model_id = str(item.get("id") or "").strip()
|
|
if not model_id:
|
|
continue
|
|
effort_capability = (item.get("capabilities") or {}).get("effort") or {}
|
|
efforts = _efforts(
|
|
effort
|
|
for effort in ENGINE_REASONING_EFFORTS
|
|
if isinstance(effort_capability.get(effort), dict)
|
|
and effort_capability[effort].get("supported")
|
|
)
|
|
default_effort: ReasoningEffort | None = (
|
|
CLAUDE_DEFAULT_EFFORT
|
|
if CLAUDE_DEFAULT_EFFORT in efforts
|
|
else (efforts[0] if efforts else None)
|
|
)
|
|
models.append(
|
|
EngineModelOption(
|
|
id=model_id,
|
|
label=str(item.get("display_name") or model_id),
|
|
description="Anthropic Models API가 현재 키에 노출한 모델입니다.",
|
|
reasoning_efforts=efforts,
|
|
default_reasoning_effort=default_effort,
|
|
)
|
|
)
|
|
if not models:
|
|
return _unavailable("claude_api", "Anthropic이 선택 가능한 모델을 반환하지 않았습니다.")
|
|
configured_default = os.environ.get("ANTHROPIC_MODEL", "").strip()
|
|
default_model = (
|
|
configured_default
|
|
if configured_default and any(model.id == configured_default for model in models)
|
|
else models[0].id
|
|
)
|
|
selected = next(model for model in models if model.id == default_model)
|
|
selected.is_default = True
|
|
return EngineCapabilitiesResponse(
|
|
provider="claude_api",
|
|
available=True,
|
|
source="live_api",
|
|
models=models,
|
|
default_model=default_model,
|
|
default_reasoning_effort=selected.default_reasoning_effort,
|
|
detail="Anthropic /v1/models에서 실시간 조회했습니다.",
|
|
fetched_at=_now(),
|
|
)
|
|
|
|
|
|
async def _discover_openai() -> EngineCapabilitiesResponse:
|
|
api_key = os.environ.get("OPENAI_API_KEY", "").strip()
|
|
if not api_key:
|
|
return _unavailable("openai", "OPENAI_API_KEY가 설정되지 않았습니다.")
|
|
try:
|
|
allowed_models = _configured_openai_models()
|
|
async with httpx.AsyncClient(timeout=20) as client:
|
|
response = await client.get(
|
|
f"{OPENAI_API_BASE}/models",
|
|
headers={"Authorization": f"Bearer {api_key}"},
|
|
)
|
|
response.raise_for_status()
|
|
payload = response.json()
|
|
except ProviderError as exc:
|
|
return _unavailable("openai", str(exc))
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
return _unavailable("openai", f"OpenAI 모델 조회 실패: {exc}")
|
|
|
|
live_ids = {
|
|
str(item.get("id") or "").strip()
|
|
for item in payload.get("data", [])
|
|
if isinstance(item, dict)
|
|
} if isinstance(payload, dict) else set()
|
|
available_ids = [model for model in allowed_models if model in live_ids]
|
|
if not available_ids:
|
|
return _unavailable(
|
|
"openai",
|
|
"OpenAI가 allowlist의 텍스트 모델을 반환하지 않았습니다.",
|
|
)
|
|
|
|
configured_default = os.environ.get("OPENAI_ENGINE_MODEL", "").strip()
|
|
default_model = (
|
|
configured_default
|
|
if configured_default in available_ids
|
|
else available_ids[0]
|
|
)
|
|
models: list[EngineModelOption] = []
|
|
for model_id in available_ids:
|
|
efforts = _openai_reasoning_efforts(model_id)
|
|
default_effort: ReasoningEffort | None = (
|
|
"medium" if "medium" in efforts else None
|
|
)
|
|
models.append(
|
|
EngineModelOption(
|
|
id=model_id,
|
|
label=model_id,
|
|
description="OpenAI Models API와 운영 allowlist가 함께 허용한 모델입니다.",
|
|
reasoning_efforts=efforts,
|
|
default_reasoning_effort=default_effort,
|
|
is_default=model_id == default_model,
|
|
)
|
|
)
|
|
selected = next(model for model in models if model.id == default_model)
|
|
return EngineCapabilitiesResponse(
|
|
provider="openai",
|
|
available=True,
|
|
source="live_api",
|
|
models=models,
|
|
default_model=default_model,
|
|
default_reasoning_effort=selected.default_reasoning_effort,
|
|
detail="OpenAI /v1/models와 운영 allowlist를 교차 확인했습니다.",
|
|
fetched_at=_now(),
|
|
)
|
|
|
|
|
|
def _configured_openrouter_models() -> list[str]:
|
|
"""OpenRouter allowlist. 미설정이면 계정이 노출한 전체 모델을 그대로 쓴다."""
|
|
raw = os.environ.get("OPENROUTER_ENGINE_MODELS", "").strip()
|
|
if not raw:
|
|
return []
|
|
result: list[str] = []
|
|
for model in (item.strip() for item in raw.split(",")):
|
|
if not model or model in result:
|
|
continue
|
|
if any(character.isspace() for character in model) or "/" not in model:
|
|
raise ProviderError(
|
|
"OPENROUTER_ENGINE_MODELS의 모델 식별자는 vendor/model 형태여야 합니다."
|
|
)
|
|
result.append(model)
|
|
return result
|
|
|
|
|
|
async def _discover_openrouter() -> EngineCapabilitiesResponse:
|
|
api_key = os.environ.get("OPENROUTER_API_KEY", "").strip()
|
|
if not api_key:
|
|
return _unavailable("openrouter", "OPENROUTER_API_KEY가 설정되지 않았습니다.")
|
|
try:
|
|
allowed_models = _configured_openrouter_models()
|
|
async with httpx.AsyncClient(timeout=20) as client:
|
|
response = await client.get(
|
|
f"{OPENROUTER_API_BASE}/models",
|
|
headers={"Authorization": f"Bearer {api_key}"},
|
|
)
|
|
response.raise_for_status()
|
|
payload = response.json()
|
|
except ProviderError as exc:
|
|
return _unavailable("openrouter", str(exc))
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
return _unavailable("openrouter", f"OpenRouter 모델 조회 실패: {exc}")
|
|
|
|
data = payload.get("data", []) if isinstance(payload, dict) else []
|
|
live: dict[str, dict[str, Any]] = {}
|
|
for item in data if isinstance(data, list) else []:
|
|
if not isinstance(item, dict):
|
|
continue
|
|
model_id = str(item.get("id") or "").strip()
|
|
if model_id:
|
|
live[model_id] = item
|
|
if allowed_models:
|
|
selected_ids = [model for model in allowed_models if model in live]
|
|
else:
|
|
selected_ids = list(live)
|
|
if not selected_ids:
|
|
return _unavailable(
|
|
"openrouter",
|
|
"OpenRouter가 사용 가능한 모델을 반환하지 않았습니다.",
|
|
)
|
|
configured_default = os.environ.get("OPENROUTER_ENGINE_MODEL", "").strip()
|
|
default_model = (
|
|
configured_default
|
|
if configured_default in selected_ids
|
|
else selected_ids[0]
|
|
)
|
|
models: list[EngineModelOption] = []
|
|
for model_id in selected_ids:
|
|
entry = live[model_id]
|
|
pricing = entry.get("pricing") or {}
|
|
is_free = str(pricing.get("prompt") or "") == "0" and str(
|
|
pricing.get("completion") or ""
|
|
) == "0"
|
|
models.append(
|
|
EngineModelOption(
|
|
id=model_id,
|
|
label=str(entry.get("name") or model_id),
|
|
description=(
|
|
"OpenRouter 무료 모델입니다."
|
|
if is_free
|
|
else "OpenRouter 계정에서 현재 사용할 수 있는 모델입니다."
|
|
),
|
|
reasoning_efforts=[],
|
|
default_reasoning_effort=None,
|
|
is_default=model_id == default_model,
|
|
)
|
|
)
|
|
return EngineCapabilitiesResponse(
|
|
provider="openrouter",
|
|
available=True,
|
|
source="live_api",
|
|
models=models,
|
|
default_model=default_model,
|
|
default_reasoning_effort=None,
|
|
detail="OpenRouter /models에서 실시간 조회했습니다.",
|
|
fetched_at=_now(),
|
|
)
|
|
|
|
|
|
async def _generate_openrouter(
|
|
req: GenerateRequest,
|
|
system_prompt: str,
|
|
user_payload: str,
|
|
) -> ProviderGenerateResult:
|
|
pricing_started_at = _utcnow()
|
|
api_key = os.environ.get("OPENROUTER_API_KEY", "").strip()
|
|
if not api_key:
|
|
raise ProviderError("OPENROUTER_API_KEY가 설정되지 않았습니다.")
|
|
model, effort = await _resolve_selection(req, "openrouter")
|
|
if req.ai_role == "client":
|
|
messages: list[dict[str, str]] = [
|
|
{"role": "user", "content": user_payload}
|
|
]
|
|
else:
|
|
messages = [
|
|
{"role": message.role, "content": message.content}
|
|
for message in req.messages
|
|
if message.role != "system"
|
|
]
|
|
if system_prompt:
|
|
messages = [{"role": "system", "content": system_prompt}, *messages]
|
|
payload: dict[str, Any] = {
|
|
"model": model,
|
|
"messages": messages,
|
|
"max_tokens": req.max_tokens,
|
|
"temperature": req.temperature,
|
|
}
|
|
if effort:
|
|
payload["reasoning"] = {"effort": effort}
|
|
try:
|
|
async with httpx.AsyncClient(timeout=CLI_TIMEOUT_SECONDS) as client:
|
|
response = await client.post(
|
|
f"{OPENROUTER_API_BASE}/chat/completions",
|
|
headers={
|
|
"Authorization": f"Bearer {api_key}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
json=payload,
|
|
)
|
|
response.raise_for_status()
|
|
body = response.json()
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
raise ProviderError(f"OpenRouter Chat Completions 호출 실패: {exc}") from exc
|
|
choices = body.get("choices", []) if isinstance(body, dict) else []
|
|
text = ""
|
|
if isinstance(choices, list) and choices and isinstance(choices[0], dict):
|
|
message = choices[0].get("message") or {}
|
|
if isinstance(message, dict):
|
|
text = str(message.get("content") or "").strip()
|
|
if not text:
|
|
raise ProviderError("OpenRouter가 텍스트 응답을 반환하지 않았습니다.")
|
|
usage = body.get("usage") or {}
|
|
detail = usage.get("prompt_tokens_details") or {}
|
|
estimate = estimate_reference_cost(
|
|
provider="openrouter",
|
|
model=str(body.get("model") or model),
|
|
tokens_in=int(usage.get("prompt_tokens") or 0),
|
|
tokens_out=int(usage.get("completion_tokens") or 0),
|
|
priced_at=pricing_started_at,
|
|
cached_input_tokens=int(detail.get("cached_tokens") or 0),
|
|
)
|
|
return ProviderGenerateResult(
|
|
text=text,
|
|
model=str(body.get("model") or model),
|
|
provider="openrouter",
|
|
tokens_in=int(usage.get("prompt_tokens") or 0),
|
|
tokens_out=int(usage.get("completion_tokens") or 0),
|
|
cost_usd=estimate.cost_usd if estimate is not None else 0.0,
|
|
structured=_structured_or_none(text, req),
|
|
)
|
|
|
|
|
|
async def _discover(provider: EngineProvider) -> EngineCapabilitiesResponse:
|
|
if provider == "claude_cli":
|
|
return await _discover_claude_cli()
|
|
if provider == "claude_api":
|
|
return await _discover_claude_api()
|
|
if provider == "openai":
|
|
return await _discover_openai()
|
|
if provider == "openrouter":
|
|
return await _discover_openrouter()
|
|
if provider == "codex_cli":
|
|
return await _discover_codex_cli()
|
|
if provider == "agy_cli":
|
|
return await _discover_agy_cli()
|
|
return _unavailable(provider, f"{provider} 어댑터는 아직 모델 탐색을 지원하지 않습니다.")
|
|
|
|
|
|
async def discover_capabilities(
|
|
provider: EngineProvider, *, force: bool = False
|
|
) -> EngineCapabilitiesResponse:
|
|
cached = _CAPABILITY_CACHE.get(provider)
|
|
if (
|
|
not force
|
|
and cached is not None
|
|
and time.monotonic() - cached[0] < CAPABILITY_CACHE_TTL_SECONDS
|
|
):
|
|
return cached[1].model_copy(deep=True)
|
|
async with _CAPABILITY_LOCK:
|
|
cached = _CAPABILITY_CACHE.get(provider)
|
|
if (
|
|
not force
|
|
and cached is not None
|
|
and time.monotonic() - cached[0] < CAPABILITY_CACHE_TTL_SECONDS
|
|
):
|
|
return cached[1].model_copy(deep=True)
|
|
result = await _discover(provider)
|
|
_CAPABILITY_CACHE[provider] = (time.monotonic(), result)
|
|
return result.model_copy(deep=True)
|
|
|
|
|
|
def _cli_prompt(system_prompt: str, user_payload: str) -> str:
|
|
parts = []
|
|
if system_prompt.strip():
|
|
parts.append("[시스템 지침]\n" + system_prompt.strip())
|
|
parts.append("[응답할 입력]\n" + user_payload.strip())
|
|
return "\n\n".join(parts)
|
|
|
|
|
|
def _cli_runtime_cwd() -> Path:
|
|
path = Path(
|
|
os.environ.get(
|
|
"ENGINE_CLI_CWD",
|
|
str(Path(tempfile.gettempdir()) / "vignette-engine-runtime"),
|
|
)
|
|
)
|
|
path.mkdir(parents=True, exist_ok=True)
|
|
return path
|
|
|
|
|
|
async def _resolve_selection(
|
|
req: GenerateRequest, provider: EngineProvider
|
|
) -> tuple[str, ReasoningEffort | None]:
|
|
capabilities = await discover_capabilities(provider)
|
|
if not capabilities.available:
|
|
raise ProviderError(capabilities.detail or f"{provider}를 사용할 수 없습니다.")
|
|
requested_model = normalize_engine_gateway_model(req.model)
|
|
model = requested_model or capabilities.default_model
|
|
option = next((item for item in capabilities.models if item.id == model), None)
|
|
if option is None:
|
|
raise ProviderError(f"{provider}에서 사용할 수 없는 모델입니다: {model}")
|
|
effort = req.reasoning_effort or option.default_reasoning_effort
|
|
if effort is not None and effort not in option.reasoning_efforts:
|
|
raise ProviderError(f"{model}에서 사용할 수 없는 추론 강도입니다: {effort}")
|
|
return option.id, effort
|
|
|
|
|
|
def _structured_or_none(text: str, req: GenerateRequest) -> dict[str, Any] | None:
|
|
if not req.structured_schema:
|
|
return None
|
|
try:
|
|
parsed = json.loads(text)
|
|
except (json.JSONDecodeError, TypeError):
|
|
return None
|
|
return parsed if isinstance(parsed, dict) else None
|
|
|
|
|
|
async def _generate_codex(
|
|
req: GenerateRequest, system_prompt: str, user_payload: str
|
|
) -> ProviderGenerateResult:
|
|
pricing_started_at = _utcnow()
|
|
binary = _binary("CODEX_BIN", "codex")
|
|
if binary is None:
|
|
raise ProviderError("Codex CLI를 찾을 수 없습니다.")
|
|
model, effort = await _resolve_selection(req, "codex_cli")
|
|
cli_cwd = _cli_runtime_cwd()
|
|
args = [
|
|
binary,
|
|
"exec",
|
|
"--json",
|
|
"--ephemeral",
|
|
"--skip-git-repo-check",
|
|
"--ignore-user-config",
|
|
"--ignore-rules",
|
|
"--sandbox",
|
|
"read-only",
|
|
"-C",
|
|
str(cli_cwd),
|
|
"-m",
|
|
model,
|
|
]
|
|
if effort:
|
|
args += ["-c", f'model_reasoning_effort="{effort}"']
|
|
args.append("-")
|
|
stdout, _ = await _run_process(
|
|
args,
|
|
input_text=_cli_prompt(system_prompt, user_payload),
|
|
cwd=str(cli_cwd),
|
|
)
|
|
text = ""
|
|
tokens_in = 0
|
|
tokens_out = 0
|
|
cached_input_tokens = 0
|
|
for line in stdout.splitlines():
|
|
try:
|
|
event = json.loads(line)
|
|
except json.JSONDecodeError:
|
|
continue
|
|
if event.get("type") == "item.completed":
|
|
item = event.get("item") or {}
|
|
if item.get("type") == "agent_message":
|
|
text = str(item.get("text") or text)
|
|
elif event.get("type") == "turn.completed":
|
|
usage = event.get("usage") or {}
|
|
tokens_in = int(usage.get("input_tokens") or 0)
|
|
tokens_out = int(usage.get("output_tokens") or 0)
|
|
cached_input_tokens = int(usage.get("cached_input_tokens") or 0)
|
|
elif event.get("type") in {"turn.failed", "error"}:
|
|
raise ProviderError(str(event.get("message") or event))
|
|
if not text.strip():
|
|
raise ProviderError("Codex CLI가 최종 응답을 반환하지 않았습니다.")
|
|
estimate = estimate_reference_cost(
|
|
provider="codex_cli",
|
|
model=model,
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
priced_at=pricing_started_at,
|
|
cached_input_tokens=cached_input_tokens,
|
|
)
|
|
return ProviderGenerateResult(
|
|
text=text,
|
|
model=model,
|
|
provider="codex_cli",
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
cost_usd=estimate.cost_usd if estimate is not None else 0.0,
|
|
structured=_structured_or_none(text, req),
|
|
)
|
|
|
|
|
|
async def _generate_agy(
|
|
req: GenerateRequest, system_prompt: str, user_payload: str
|
|
) -> ProviderGenerateResult:
|
|
# text 출력은 토큰 사용량을 주지 않는다. stream-json의 terminal result를
|
|
# 동일하게 소비해 generate와 stream 모두 같은 token/cost 계약을 유지한다.
|
|
async for event in _stream_agy(req, system_prompt, user_payload):
|
|
if event.type == "done" and event.result is not None:
|
|
return event.result
|
|
raise ProviderError("Agy CLI가 최종 응답을 반환하지 않았습니다.")
|
|
|
|
|
|
async def _stream_agy(
|
|
req: GenerateRequest, system_prompt: str, user_payload: str
|
|
) -> AsyncIterator[ProviderStreamEvent]:
|
|
"""Agy stream-json의 agent_response delta를 게이트웨이 토큰으로 전달한다.
|
|
|
|
Agy print 모드는 대화 내용을 로컬 conversation 저장소에 남길 수 있으므로 여기서는
|
|
--continue/--conversation을 쓰지 않는다. 회기 메모리는 매 요청의 마스킹된 prompt가
|
|
소유하고, 프로세스는 응답 뒤 종료한다.
|
|
"""
|
|
pricing_started_at = _utcnow()
|
|
binary = _binary("AGY_BIN", "agy")
|
|
if binary is None:
|
|
raise ProviderError("Agy CLI를 찾을 수 없습니다.")
|
|
model, effort = await _resolve_selection(req, "agy_cli")
|
|
prompt = _cli_prompt(system_prompt, user_payload)
|
|
args = [binary, "--model", model, "--sandbox"]
|
|
if effort:
|
|
args += ["--effort", effort]
|
|
args += [
|
|
"--print-timeout",
|
|
f"{int(CLI_TIMEOUT_SECONDS)}s",
|
|
# 긴 deep-loop 축어록을 Windows argv에 싣지 않는다. Agy의 공식 stream-json
|
|
# 입력 계약은 prompt를 stdin의 단일 user 이벤트로 받으므로 명령줄 길이 한계를
|
|
# 피하면서 전체 마스킹 근거를 그대로 보존한다.
|
|
"--input-format",
|
|
"stream-json",
|
|
"--output-format",
|
|
"stream-json",
|
|
]
|
|
proc = await asyncio.create_subprocess_exec(
|
|
*args,
|
|
cwd=str(_cli_runtime_cwd()),
|
|
stdin=asyncio.subprocess.PIPE,
|
|
stdout=asyncio.subprocess.PIPE,
|
|
stderr=asyncio.subprocess.PIPE,
|
|
env=_cli_subprocess_env(),
|
|
)
|
|
assert proc.stdin is not None
|
|
assert proc.stdout is not None
|
|
assert proc.stderr is not None
|
|
stderr_task = asyncio.create_task(proc.stderr.read())
|
|
emitted = ""
|
|
final_text = ""
|
|
tokens_in = 0
|
|
tokens_out = 0
|
|
cached_input_tokens = 0
|
|
result_status = ""
|
|
try:
|
|
# 공식 protocol: 한 줄에 한 user event. 마지막 turn 뒤 stdin을 닫아도 CLI는
|
|
# terminal result를 내보낸 뒤 종료한다. stdin 거절은 child와 stderr를 정리한 뒤
|
|
# provider 오류로 승격해 프로세스를 남기지 않는다.
|
|
try:
|
|
proc.stdin.write(
|
|
(
|
|
json.dumps(
|
|
{"event": "user", "message": {"content": prompt}},
|
|
ensure_ascii=False,
|
|
)
|
|
+ "\n"
|
|
).encode("utf-8")
|
|
)
|
|
await proc.stdin.drain()
|
|
except (BrokenPipeError, ConnectionResetError) as exc:
|
|
raise ProviderError("Agy CLI가 stdin 평가 입력을 수락하지 않았습니다.") from exc
|
|
finally:
|
|
if not proc.stdin.is_closing():
|
|
proc.stdin.close()
|
|
try:
|
|
await proc.stdin.wait_closed()
|
|
except (BrokenPipeError, ConnectionResetError):
|
|
# 이미 종료된 CLI가 close 직후 EOF를 끊어도 finally가 child를 회수한다.
|
|
pass
|
|
async with asyncio.timeout(CLI_TIMEOUT_SECONDS):
|
|
while True:
|
|
raw = await proc.stdout.readline()
|
|
if not raw:
|
|
break
|
|
try:
|
|
event = json.loads(raw.decode("utf-8", errors="replace"))
|
|
except json.JSONDecodeError:
|
|
continue
|
|
if event.get("event") == "step_update":
|
|
update = event.get("step_update") or {}
|
|
if update.get("step_type") == "agent_response":
|
|
delta = str(update.get("text_delta") or "")
|
|
if delta:
|
|
emitted += delta
|
|
yield ProviderStreamEvent(type="delta", text=delta)
|
|
elif event.get("event") == "result":
|
|
result = event.get("result") or {}
|
|
result_status = str(result.get("status") or "")
|
|
final_text = str(result.get("response") or "")
|
|
usage = result.get("usage") or {}
|
|
tokens_in = int(usage.get("input_tokens") or 0)
|
|
tokens_out = int(usage.get("output_tokens") or 0)
|
|
cached_input_tokens = int(
|
|
usage.get("cache_read_tokens")
|
|
or usage.get("cached_input_tokens")
|
|
or 0
|
|
)
|
|
returncode = await proc.wait()
|
|
except TimeoutError as exc:
|
|
raise ProviderError(
|
|
f"Agy CLI 응답 시간이 {int(CLI_TIMEOUT_SECONDS)}초를 넘었습니다."
|
|
) from exc
|
|
finally:
|
|
if proc.returncode is None:
|
|
proc.kill()
|
|
await proc.wait()
|
|
stderr = await stderr_task
|
|
|
|
if returncode != 0:
|
|
raise ProviderError(_safe_process_error(stderr, f"Agy CLI exit {returncode}"))
|
|
if result_status and result_status != "SUCCESS":
|
|
raise ProviderError(f"Agy CLI 생성 실패: {result_status}")
|
|
resolved_text = final_text or emitted
|
|
if not resolved_text.strip():
|
|
raise ProviderError("Agy CLI가 최종 응답을 반환하지 않았습니다.")
|
|
if final_text and final_text.startswith(emitted):
|
|
remainder = final_text[len(emitted) :]
|
|
if remainder:
|
|
emitted += remainder
|
|
yield ProviderStreamEvent(type="delta", text=remainder)
|
|
elif not emitted:
|
|
emitted = resolved_text
|
|
yield ProviderStreamEvent(type="delta", text=resolved_text)
|
|
estimate = estimate_reference_cost(
|
|
provider="agy_cli",
|
|
model=model,
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
priced_at=pricing_started_at,
|
|
cached_input_tokens=cached_input_tokens,
|
|
)
|
|
yield ProviderStreamEvent(
|
|
type="done",
|
|
result=ProviderGenerateResult(
|
|
text=resolved_text,
|
|
model=model,
|
|
provider="agy_cli",
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
cost_usd=estimate.cost_usd if estimate is not None else 0.0,
|
|
structured=_structured_or_none(resolved_text, req),
|
|
),
|
|
)
|
|
|
|
|
|
async def _generate_claude_api(
|
|
req: GenerateRequest, system_prompt: str
|
|
) -> ProviderGenerateResult:
|
|
pricing_started_at = _utcnow()
|
|
api_key = os.environ.get("ANTHROPIC_API_KEY", "").strip() or os.environ.get(
|
|
"ANTHROPIC_AUTH_TOKEN", ""
|
|
).strip()
|
|
if not api_key:
|
|
raise ProviderError("ANTHROPIC_API_KEY가 설정되지 않았습니다.")
|
|
model, effort = await _resolve_selection(req, "claude_api")
|
|
messages = [
|
|
{"role": message.role, "content": message.content}
|
|
for message in req.messages
|
|
if message.role != "system"
|
|
]
|
|
payload: dict[str, Any] = {
|
|
"model": model,
|
|
"max_tokens": req.max_tokens,
|
|
"temperature": req.temperature,
|
|
"messages": messages,
|
|
}
|
|
if system_prompt:
|
|
payload["system"] = system_prompt
|
|
if effort:
|
|
payload["output_config"] = {"effort": effort}
|
|
try:
|
|
async with httpx.AsyncClient(timeout=CLI_TIMEOUT_SECONDS) as client:
|
|
response = await client.post(
|
|
f"{ANTHROPIC_API_BASE}/v1/messages",
|
|
headers=_anthropic_headers(api_key),
|
|
json=payload,
|
|
)
|
|
response.raise_for_status()
|
|
body = response.json()
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
raise ProviderError(f"Anthropic Messages API 호출 실패: {exc}") from exc
|
|
text = "".join(
|
|
str(block.get("text") or "")
|
|
for block in body.get("content", [])
|
|
if isinstance(block, dict) and block.get("type") == "text"
|
|
)
|
|
if not text:
|
|
raise ProviderError("Anthropic Messages API가 텍스트 응답을 반환하지 않았습니다.")
|
|
usage = body.get("usage") or {}
|
|
inference_geo = body.get("inference_geo")
|
|
tokens_in = int(usage.get("input_tokens") or 0)
|
|
tokens_out = int(usage.get("output_tokens") or 0)
|
|
estimate = estimate_reference_cost(
|
|
provider="claude_api",
|
|
model=str(body.get("model") or model),
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
priced_at=pricing_started_at,
|
|
cached_input_tokens=int(usage.get("cache_read_input_tokens") or 0),
|
|
)
|
|
return ProviderGenerateResult(
|
|
text=text,
|
|
model=str(body.get("model") or model),
|
|
provider="claude_api",
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
cost_usd=estimate.cost_usd if estimate is not None else 0.0,
|
|
inference_geo=str(inference_geo) if inference_geo else None,
|
|
structured=_structured_or_none(text, req),
|
|
)
|
|
|
|
|
|
def _openai_response_text(body: dict[str, Any]) -> str:
|
|
direct = body.get("output_text")
|
|
if isinstance(direct, str) and direct.strip():
|
|
return direct
|
|
parts: list[str] = []
|
|
for item in body.get("output", []) if isinstance(body, dict) else []:
|
|
if not isinstance(item, dict) or item.get("type") != "message":
|
|
continue
|
|
for content in item.get("content", []):
|
|
if (
|
|
isinstance(content, dict)
|
|
and content.get("type") == "output_text"
|
|
and isinstance(content.get("text"), str)
|
|
):
|
|
parts.append(content["text"])
|
|
return "".join(parts)
|
|
|
|
|
|
async def _generate_openai(
|
|
req: GenerateRequest,
|
|
system_prompt: str,
|
|
user_payload: str,
|
|
) -> ProviderGenerateResult:
|
|
pricing_started_at = _utcnow()
|
|
api_key = os.environ.get("OPENAI_API_KEY", "").strip()
|
|
if not api_key:
|
|
raise ProviderError("OPENAI_API_KEY가 설정되지 않았습니다.")
|
|
model, effort = await _resolve_selection(req, "openai")
|
|
if req.ai_role == "client":
|
|
messages: list[dict[str, str]] = [
|
|
{"role": "user", "content": user_payload}
|
|
]
|
|
else:
|
|
messages = [
|
|
{"role": message.role, "content": message.content}
|
|
for message in req.messages
|
|
if message.role != "system"
|
|
]
|
|
payload: dict[str, Any] = {
|
|
"model": model,
|
|
"input": messages,
|
|
"max_output_tokens": req.max_tokens,
|
|
# 상담 시뮬레이션 입력을 OpenAI의 응답 상태 저장소에 남기지 않는다.
|
|
# 회기 기록의 SSOT는 Vignette의 NAS PostgreSQL뿐이다.
|
|
"store": False,
|
|
}
|
|
if system_prompt:
|
|
payload["instructions"] = system_prompt
|
|
if effort:
|
|
payload["reasoning"] = {"effort": effort}
|
|
else:
|
|
payload["temperature"] = req.temperature
|
|
try:
|
|
async with httpx.AsyncClient(timeout=CLI_TIMEOUT_SECONDS) as client:
|
|
response = await client.post(
|
|
f"{OPENAI_API_BASE}/responses",
|
|
headers={
|
|
"Authorization": f"Bearer {api_key}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
json=payload,
|
|
)
|
|
response.raise_for_status()
|
|
body = response.json()
|
|
except (httpx.HTTPError, ValueError) as exc:
|
|
raise ProviderError(f"OpenAI Responses API 호출 실패: {exc}") from exc
|
|
if not isinstance(body, dict):
|
|
raise ProviderError("OpenAI Responses API가 객체 응답을 반환하지 않았습니다.")
|
|
text = _openai_response_text(body).strip()
|
|
if not text:
|
|
raise ProviderError("OpenAI Responses API가 텍스트 응답을 반환하지 않았습니다.")
|
|
usage = body.get("usage") or {}
|
|
tokens_in = int(usage.get("input_tokens") or 0)
|
|
tokens_out = int(usage.get("output_tokens") or 0)
|
|
input_details = usage.get("input_tokens_details") or {}
|
|
estimate = estimate_reference_cost(
|
|
provider="openai",
|
|
model=str(body.get("model") or model),
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
priced_at=pricing_started_at,
|
|
cached_input_tokens=int(input_details.get("cached_tokens") or 0),
|
|
)
|
|
inference_geo = body.get("inference_geo")
|
|
return ProviderGenerateResult(
|
|
text=text,
|
|
model=str(body.get("model") or model),
|
|
provider="openai",
|
|
tokens_in=tokens_in,
|
|
tokens_out=tokens_out,
|
|
cost_usd=estimate.cost_usd if estimate is not None else 0.0,
|
|
inference_geo=str(inference_geo) if inference_geo else None,
|
|
structured=_structured_or_none(text, req),
|
|
)
|
|
|
|
|
|
async def generate_with_provider(
|
|
req: GenerateRequest,
|
|
*,
|
|
system_prompt: str,
|
|
user_payload: str,
|
|
) -> ProviderGenerateResult:
|
|
provider = req.provider
|
|
if provider == "codex_cli":
|
|
return await _generate_codex(req, system_prompt, user_payload)
|
|
if provider == "agy_cli":
|
|
return await _generate_agy(req, system_prompt, user_payload)
|
|
if provider == "claude_api":
|
|
return await _generate_claude_api(req, system_prompt)
|
|
if provider == "openai":
|
|
return await _generate_openai(req, system_prompt, user_payload)
|
|
if provider == "openrouter":
|
|
return await _generate_openrouter(req, system_prompt, user_payload)
|
|
raise ProviderError(f"이 게이트웨이에서 실행할 수 없는 provider입니다: {provider}")
|
|
|
|
|
|
async def stream_with_provider(
|
|
req: GenerateRequest,
|
|
*,
|
|
system_prompt: str,
|
|
user_payload: str,
|
|
) -> AsyncIterator[ProviderStreamEvent]:
|
|
"""Provider가 제공하는 가장 이른 출력 단위를 공통 delta/done 계약으로 바꾼다."""
|
|
if req.provider == "agy_cli":
|
|
async for event in _stream_agy(req, system_prompt, user_payload):
|
|
yield event
|
|
return
|
|
result = await generate_with_provider(
|
|
req,
|
|
system_prompt=system_prompt,
|
|
user_payload=user_payload,
|
|
)
|
|
yield ProviderStreamEvent(type="delta", text=result.text)
|
|
yield ProviderStreamEvent(type="done", result=result)
|