# ScamShield AI - Environment Configuration
# Copy this file to .env and fill in the values
# Command: copy env.example .env (Windows) or cp env.example .env (Linux/Mac)

# =====================================================
# Environment
# =====================================================
ENVIRONMENT=development
DEBUG=true
LOG_LEVEL=INFO

# =====================================================
# Groq LLM API
# =====================================================
# Get your API key from: https://console.groq.com/
GROQ_API_KEY=gsk_your_key_here
GROQ_MODEL=llama-3.1-8b-instant
GROQ_MAX_TOKENS=500
GROQ_TEMPERATURE=0.7

# =====================================================
# PostgreSQL Database (OPTIONAL - can be empty for in-memory only)
# =====================================================
# For Supabase: postgresql://postgres:[password]@[host]:5432/postgres
# Leave empty to use in-memory storage only (faster for hackathon)
POSTGRES_URL=

# =====================================================
# Redis Cache (OPTIONAL - can be empty for in-memory only)
# =====================================================
# For Redis Cloud: redis://default:[password]@[host]:[port]
# Leave empty to use in-memory storage only (faster for hackathon)
REDIS_URL=

# =====================================================
# ChromaDB
# =====================================================
CHROMADB_PATH=./chroma_data

# =====================================================
# API Configuration
# =====================================================
API_HOST=0.0.0.0
API_PORT=8000

# =====================================================
# Scam Detection Settings
# =====================================================
MAX_MESSAGE_LENGTH=5000
MAX_TURNS=20
SESSION_TTL=3600
SCAM_THRESHOLD=0.7

# =====================================================
# Rate Limiting
# =====================================================
RATE_LIMIT_PER_MINUTE=100
RATE_LIMIT_PER_HOUR=1000

# =====================================================
# Model Configuration
# =====================================================
# HuggingFace token for accessing gated models (e.g., IndicBERT)
# Get your token from: https://huggingface.co/settings/tokens
HUGGINGFACE_TOKEN=YOUR_TOKEN_HERE
INDICBERT_MODEL=ai4bharat/indic-bert
SPACY_MODEL=en_core_web_sm
EMBEDDING_MODEL=all-MiniLM-L6-v2

# =====================================================
# API Authentication (GUVI Hackathon Requirement)
# =====================================================
# API key for authenticating requests via x-api-key header
# Required for GUVI submission - choose a secure random key
API_KEY=your-secure-api-key-here

# =====================================================
# GUVI Hackathon Integration
# =====================================================
# Callback URL for sending final results to GUVI evaluation endpoint
GUVI_CALLBACK_URL=https://hackathon.guvi.in/api/updateHoneyPotFinalResult
# Set to false to disable GUVI callbacks (for local testing)
GUVI_CALLBACK_ENABLED=true

# =====================================================
# Phase 2: Voice Features (OPTIONAL - disabled by default)
# =====================================================
# Set to true to enable voice endpoints and UI
PHASE_2_ENABLED=false
# Whisper ASR model size: tiny, base, small, medium, large
WHISPER_MODEL=base
# TTS engine: gtts, indic_tts
TTS_ENGINE=gtts
# Enable voice deepfake/synthetic voice detection
VOICE_FRAUD_DETECTION=false
# Audio processing parameters
AUDIO_SAMPLE_RATE=16000
AUDIO_CHUNK_DURATION=5