# app/config.py - Application configuration (Production Hardened)

from pydantic_settings import BaseSettings, SettingsConfigDict
from typing import Optional
from functools import lru_cache
from dotenv import load_dotenv
import os

# ════════════════════════════════════════════════════════════════════════════
# FIX 1: HF-SAFE DOTENV LOADING
# On HuggingFace, secrets are injected at runtime. Don't override them.
# ════════════════════════════════════════════════════════════════════════════
if os.getenv("HF_SPACE_ID") is None:
    load_dotenv(override=True)  # Local dev → .env
else:
    load_dotenv(override=False) # HF prod → Secrets only


class Settings(BaseSettings):
    """Application settings loaded from environment variables."""
    
    # Application
    APP_NAME: str = "Scam Honeypot API"
    VERSION: str = "2.5.0"
    DEBUG: bool = False
    GUVI_API_KEY: str = ""  # Must be set via Environment Variable (HF Secrets)
    GUVI_CALLBACK_URL: str = "https://hackathon.guvi.in/api/updateHoneyPotFinalResult"
    
    # SOC Hardening (SIEM Integration)
    SYSLOG_ENABLED: bool = False
    SYSLOG_HOST: str = "localhost"
    SYSLOG_PORT: int = 514
    
    # LLM Configuration
    LLM_PROVIDER: str = "groq"
    OPENAI_API_KEY: Optional[str] = None
    ANTHROPIC_API_KEY: Optional[str] = None
    GROQ_API_KEY: Optional[str] = None
    OPENROUTER_API_KEY: Optional[str] = None

    # Local HF (Offline / Free-Tier) Inference
    # FIX: Enable by default as crash-proof fallback when Groq fails
    USE_LOCAL_HF_MODEL: bool = True  # Auto-fallback when API fails
    HF_LOCAL_MODEL_NAME: str = "facebook/opt-125m"  # Tiny model, runs on CPU
    HF_LOCAL_MAX_TOKENS: int = 80  # Short responses like real SMS/chat
    HF_LOCAL_DEVICE: str = "cpu"  # Explicit so HF Spaces & local dev behave consistently
    
    # ════════════════════════════════════════════════════════════════════════
    # FIX 2: EXPLICIT MODEL DEFAULTS (No None = No Surprises)
    # Aligned with Groq limits and capability-aware fallback chains
    # ════════════════════════════════════════════════════════════════════════
    GPT_MODEL: str = "gpt-4-turbo-preview"
    CLAUDE_MODEL: str = "claude-3-sonnet-20240229"
    GROQ_MODEL: str = "llama-3.3-70b-versatile"
    
    # Per-task model routing (Production Grade)
    MAX_RETRIES: int = 2
    
    # ════════════════════════════════════════════════════════════════════════
    # FIX: HARD LLM CALL LIMITS (Prevent rate limit exhaustion)
    # OPTIMIZED for GUVI's 30s timeout & Groq free tier rate limits
    # ════════════════════════════════════════════════════════════════════════
    MAX_LLM_CALLS_PER_REQUEST: int = 6  # Reduced from 10 - fits within 20s timeout
    MAX_LLM_CALLS_PER_SESSION: int = 20  # Reduced from 30 - prevents key exhaustion
    
    # Per-task model routing (Production Grade)
    # FIX: llama-3.3-70b fails JSON_SCHEMA mode with 400. Use qwen3-32b for structured.
    GROQ_FAST_MODEL: str = "llama-3.1-8b-instant" # Blazing fast (~300 tokens/sec)
    GROQ_SMART_MODEL: str = "qwen/qwen3-32b" # Native reasoning, 60 RPM
    GROQ_NATURAL_MODEL: str = "moonshotai/kimi-k2-instruct-0905" 
    GROQ_STRUCTURED_MODEL: str = "qwen/qwen3-32b" # FIX: Supports JSON_SCHEMA properly
    GROQ_SAFETY_MODEL: str = "meta-llama/llama-guard-4-12b" 
    GROQ_SAFEGUARD_MODEL: str = "openai/gpt-oss-safeguard-20b"

    OPENROUTER_MODEL: str = "meta-llama/llama-3.1-70b-instruct"
    
    # LLM parameters
    LLM_TEMPERATURE: float = 0.7
    LLM_MAX_TOKENS: int = 500
    
    # Conversation
    MAX_CONVERSATION_LENGTH: int = 50
    CONVERSATION_TTL_HOURS: int = 24
    
    # Rate Limiting
    RATE_LIMIT_PER_MINUTE: int = 60
    
    # Feature Flags
    ENABLE_LLM_DETECTION: bool = True
    ENABLE_LLM_RESPONSES: bool = True
    ENABLE_THREAT_INTELLIGENCE: bool = True
    ENABLE_LAW_ENFORCEMENT_API: bool = False  # Disabled for hackathon
    ENABLE_ENGAGEMENT_DELAY: bool = False
    
    # Forensic Clinic (Compound Systems)
    ENABLE_MATH_FORENSICS: bool = False  # 🧮 Claim Verifier (Compound-Mini)
    ENABLE_VISUAL_EVIDENCE: bool = False # 📊 Chart Lab (Compound)
    
    # Database (SQLite default, PostgreSQL/Supabase via env)
    DATABASE_URL: str = "sqlite+aiosqlite:///./data/honeypot.db"
    
    # Compliance
    SANDBOX_MODE: bool = False
    ANONYMIZE_LOGS: bool = True
    SYNTHETIC_DATA_ONLY: bool = False
    
    model_config = SettingsConfigDict(
        env_file=".env",
        env_file_encoding="utf-8",
        case_sensitive=True,
        extra="allow"
    )


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


settings = get_settings()


# ════════════════════════════════════════════════════════════════════════════
# FIX 3 & 4: STARTUP VALIDATION (Fail Fast)
# ════════════════════════════════════════════════════════════════════════════
def validate_production_config():
    """Validates critical config at startup. Raises RuntimeError if invalid."""
    errors = []
    
    # FIX 3: GUVI_API_KEY must be set for scoring
    if not settings.GUVI_API_KEY:
        errors.append("GUVI_API_KEY missing — scoring impossible")

    # FIX 4: Exactly ONE *external* LLM provider key must be set
    # EXCEPTION: When USE_LOCAL_HF_MODEL=True we allow zero external keys
    active_keys = [
        ("GROQ_API_KEY", settings.GROQ_API_KEY),
        ("OPENAI_API_KEY", settings.OPENAI_API_KEY),
        ("ANTHROPIC_API_KEY", settings.ANTHROPIC_API_KEY),
        ("OPENROUTER_API_KEY", settings.OPENROUTER_API_KEY),
    ]
    set_keys = [(name, key) for name, key in active_keys if key]

    if len(set_keys) == 0 and not settings.USE_LOCAL_HF_MODEL:
        errors.append("No LLM API key set — system cannot function (set USE_LOCAL_HF_MODEL=True to enable offline mode)")
    elif len(set_keys) > 1:
        key_names = [name for name, _ in set_keys]
        errors.append(f"Multiple LLM API keys set ({', '.join(key_names)}) — please use exactly one")
    
    # In production, fail hard
    if errors and not settings.DEBUG:
        raise RuntimeError("🚨 CONFIG VALIDATION FAILED:\n  - " + "\n  - ".join(errors))
    elif errors:
        # In debug mode, just warn
        import warnings
        for err in errors:
            warnings.warn(f"⚠️ CONFIG WARNING: {err}")


# Run validation at import time (fail fast)
validate_production_config()