.env.example

# ============================================================
# Interview Ace — Environment Configuration
# Copy this file to .env and fill in your values
# ============================================================

# --- LLM Provider (pick one or configure multiple) ---
# Supported: openai, anthropic, google, deepseek, openrouter
LLM_PROVIDER=openai
LLM_API_KEY=sk-your-api-key-here
LLM_MODEL=gpt-4o

# --- Fallback LLM (optional, used when primary fails) ---
# FALLBACK_PROVIDER=deepseek
# FALLBACK_API_KEY=sk-your-fallback-key
# FALLBACK_MODEL=deepseek-chat

# --- Vector Database (for RAG) ---
# Supported: chromadb (local), pinecone, weaviate
VECTOR_DB=chromadb
# PINECONE_API_KEY=
# PINECONE_ENVIRONMENT=

# --- Audio ---
# Audio capture device index (run `python -m scripts.list_devices` to find yours)
AUDIO_DEVICE_INDEX=0
# Sample rate (Hz)
SAMPLE_RATE=16000
# Silence threshold for voice activity detection
SILENCE_THRESHOLD=0.01
# Seconds of silence before segment is considered complete
SILENCE_DURATION=1.5

# --- Voice Profile ---
# Path to the candidate's voice embedding file
VOICE_PROFILE_PATH=./data/voice_profile.pkl

# --- Server ---
BACKEND_HOST=0.0.0.0
BACKEND_PORT=8000
FRONTEND_PORT=3000

# --- Whisper (Speech-to-Text) ---
# Options: tiny, base, small, medium, large-v3
WHISPER_MODEL=base
# Use GPU for Whisper if available
WHISPER_DEVICE=cpu

# --- Knowledge Base ---
# Directory to store ingested documents (resumes, job descriptions, etc.)
KNOWLEDGE_BASE_DIR=./data/knowledge_base

# --- Logging ---
LOG_LEVEL=INFO