from functools import lru_cache
from pathlib import Path

from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict


BASE_DIR = Path(__file__).resolve().parents[2]
ROOT_DIR = BASE_DIR.parents[1]


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8", extra="ignore")

    app_name: str = "Gig POC API"
    app_env: str = "development"
    app_host: str = "0.0.0.0"
    app_port: int = 8000
    log_level: str = "INFO"
    app_rate_limit_per_minute: int = 1200
    app_circuit_breaker_error_rate: float = 0.5
    app_circuit_breaker_min_requests: int = 50
    app_circuit_breaker_window_seconds: int = 60
    app_circuit_breaker_cooldown_seconds: int = 30
    alert_webhook_url: str | None = None

    database_url: str = "postgresql+psycopg://gig:gig@postgres:5432/gig_poc"
    database_pool_size: int = 20
    database_max_overflow: int = 30
    database_pool_timeout: int = 30
    qdrant_url: str = "http://qdrant:6333"
    qdrant_collection: str = "gig_poc_entities"
    vector_size: int = 64

    llm_enabled: bool = False
    llm_base_url: str | None = None
    llm_fallback_base_urls: list[str] = Field(default_factory=list)
    llm_api_key: str | None = None
    llm_model: str = "gpt-5.4"
    extraction_llm_max_retries: int = 2

    embedding_backend: str = "hash"  # hash | openai_compatible
    embedding_enabled: bool = False
    embedding_base_url: str | None = None
    embedding_fallback_base_urls: list[str] = Field(default_factory=list)
    embedding_api_key: str | None = None
    embedding_model: str = "text-embedding-3-small"
    embedding_vector_size: int = 1536
    ai_request_timeout_seconds: float = 30.0
    ai_rate_limit_per_minute: int = 120
    ai_circuit_breaker_fail_threshold: int = 5
    ai_circuit_breaker_cooldown_seconds: int = 30

    bootstrap_jobs: int = 100
    bootstrap_workers: int = 300
    default_recall_top_k: int = 30
    default_match_top_n: int = 10

    prompt_dir: Path = Field(default=ROOT_DIR / "packages" / "prompts")
    sample_data_dir: Path = Field(default=ROOT_DIR / "packages" / "sample-data")
    shared_types_dir: Path = Field(default=ROOT_DIR / "packages" / "shared-types")
    data_dir: Path = Field(default=ROOT_DIR / "data")
    match_weights_path: Path = Field(default=ROOT_DIR / "data" / "match_weights.json")

    score_skill_weight: float = 0.35
    score_region_weight: float = 0.20
    score_time_weight: float = 0.15
    score_experience_weight: float = 0.15
    score_reliability_weight: float = 0.15
    ranking_learning_enabled: bool = True
    ranking_learning_rate: float = 0.08
    cache_backend: str = "memory"  # memory | redis
    redis_url: str = "redis://redis:6379/0"
    redis_prefix: str = "gig_poc"
    match_cache_enabled: bool = True
    match_cache_ttl_seconds: int = 30
    query_cache_enabled: bool = True
    query_cache_ttl_seconds: int = 20
    ingest_async_enabled: bool = True
    ingest_queue_max_size: int = 10000
    match_async_enabled: bool = True
    match_queue_max_size: int = 10000


@lru_cache
def get_settings() -> Settings:
    return Settings()