06443947bf
신규 파일: - classifier_service.py: exaone binary classifier (sufficient/insufficient) parallel with evidence, circuit breaker, timeout 5s - refusal_gate.py: multi-signal fusion (score + classifier) AND 조건, conservative fallback 3-tier (classifier 부재 시) - grounding_check.py: strong/weak flag 분리 strong: fabricated_number + intent_misalignment(important keywords) weak: uncited_claim + low_overlap + intent_misalignment(generic) re-gate: 2+ strong → refuse, 1 strong → partial - sentence_splitter.py: regex 기반 (Phase 3.5b KSS 업그레이드) - classifier.txt: exaone Y+ prompt (calibration examples 포함) - search_synthesis_partial.txt: partial answer 전용 프롬프트 - 102_ask_events.sql: /ask 관측 테이블 (completeness 3-분리 지표) - queries.yaml: Phase 3.5 smoke test 평가셋 10개 수정 파일: - search.py /ask: classifier parallel + refusal gate + grounding re-gate + defense_layers 로깅 + AskResponse completeness/aspects/confirmed_items - config.yaml: classifier model 섹션 (exaone3.5:7.8b GPU Ollama) - config.py: classifier optional 파싱 - AskAnswer.svelte: 4분기 렌더 (full/partial/insufficient/loading) - ask.ts: Completeness + ConfirmedItem 타입 P1 실측: exaone ternary 불안정 → binary gate 축소. partial은 grounding이 담당. 토론 9라운드 확정. plan: quiet-meandering-nova.md Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
112 lines
3.3 KiB
Python
112 lines
3.3 KiB
Python
"""설정 로딩 — config.yaml + credentials.env"""
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import os
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from pathlib import Path
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import yaml
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from pydantic import BaseModel
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class AIModelConfig(BaseModel):
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endpoint: str
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model: str
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max_tokens: int = 4096
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timeout: int = 60
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daily_budget_usd: float | None = None
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require_explicit_trigger: bool = False
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class AIConfig(BaseModel):
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gateway_endpoint: str
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primary: AIModelConfig
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fallback: AIModelConfig
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premium: AIModelConfig
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embedding: AIModelConfig
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vision: AIModelConfig
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rerank: AIModelConfig
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# Phase 3.5a: exaone classifier (optional — 없으면 score-only gate)
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classifier: AIModelConfig | None = None
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class Settings(BaseModel):
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# DB
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database_url: str = ""
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# AI
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ai: AIConfig | None = None
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# NAS
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nas_mount_path: str = "/documents"
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nas_pkm_root: str = "/documents/PKM"
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# 인증
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jwt_secret: str = ""
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totp_secret: str = ""
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# kordoc
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kordoc_endpoint: str = "http://kordoc-service:3100"
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# 분류 체계
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taxonomy: dict = {}
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document_types: list[str] = []
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def load_settings() -> Settings:
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"""config.yaml + 환경변수에서 설정 로딩"""
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# 환경변수 (docker-compose에서 주입)
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database_url = os.getenv("DATABASE_URL", "")
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jwt_secret = os.getenv("JWT_SECRET", "")
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totp_secret = os.getenv("TOTP_SECRET", "")
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kordoc_endpoint = os.getenv("KORDOC_ENDPOINT", "http://kordoc-service:3100")
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# config.yaml — Docker 컨테이너 내부(/app/config.yaml) 또는 프로젝트 루트
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config_path = Path("/app/config.yaml")
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if not config_path.exists():
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config_path = Path(__file__).parent.parent.parent / "config.yaml"
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ai_config = None
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nas_mount = "/documents"
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nas_pkm = "/documents/PKM"
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if config_path.exists():
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with open(config_path) as f:
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raw = yaml.safe_load(f)
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if "ai" in raw:
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ai_raw = raw["ai"]
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ai_config = AIConfig(
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gateway_endpoint=ai_raw.get("gateway", {}).get("endpoint", ""),
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primary=AIModelConfig(**ai_raw["models"]["primary"]),
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fallback=AIModelConfig(**ai_raw["models"]["fallback"]),
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premium=AIModelConfig(**ai_raw["models"]["premium"]),
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embedding=AIModelConfig(**ai_raw["models"]["embedding"]),
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vision=AIModelConfig(**ai_raw["models"]["vision"]),
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rerank=AIModelConfig(**ai_raw["models"]["rerank"]),
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classifier=(
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AIModelConfig(**ai_raw["models"]["classifier"])
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if "classifier" in ai_raw.get("models", {})
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else None
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),
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)
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if "nas" in raw:
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nas_mount = raw["nas"].get("mount_path", nas_mount)
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nas_pkm = raw["nas"].get("pkm_root", nas_pkm)
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taxonomy = raw.get("taxonomy", {}) if config_path.exists() and raw else {}
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document_types = raw.get("document_types", []) if config_path.exists() and raw else []
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return Settings(
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database_url=database_url,
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ai=ai_config,
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nas_mount_path=nas_mount,
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nas_pkm_root=nas_pkm,
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jwt_secret=jwt_secret,
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totp_secret=totp_secret,
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kordoc_endpoint=kordoc_endpoint,
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taxonomy=taxonomy,
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document_types=document_types,
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)
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settings = load_settings()
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