env.example

# OpenAI API Key (required)
OPENAI_API_KEY=sk-...

# Anthropic API Key (required)
ANTHROPIC_API_KEY=sk-ant-...

# Logfire Token (required)
# Get yours at https://logfire.pydantic.dev
LOGFIRE_TOKEN=...

# Logfire Read Token (optional - for fetching logs via API)
# Create a read-only token in your Logfire project settings
LOGFIRE_READ_TOKEN=...

# Database URL (required)
# For local development with Docker Compose:
DATABASE_URL=postgresql://render_qa_user:local_dev_password@localhost:5432/render_qa_db
# For production on Render, this will be auto-injected from the database service

# Pipeline Configuration (optional)
QUALITY_THRESHOLD=85
ACCURACY_THRESHOLD=70  # For monitoring only (not used in quality gate)
AGREEMENT_THRESHOLD=10
MAX_ITERATIONS=1  # First iteration is best; additional iterations degrade quality
MAX_TOKENS=2000
TIMEOUT_SECONDS=30

# RAG Configuration (optional)
RAG_TOP_K=20  # Number of documents to retrieve (higher = more context, but slower)
SIMILARITY_THRESHOLD=0.3  # Cosine similarity threshold (0-1) for document retrieval (lower = more permissive)
VERIFICATION_THRESHOLD=0.30  # Similarity threshold (0-1) for claim verification (lower = more lenient)
EMBEDDING_MODEL=text-embedding-3-small
EMBEDDING_DIMENSIONS=1536

# Model Selection (optional)
ANSWER_MODEL=claude-sonnet-4-6
CLAIMS_MODEL=gpt-5.4-mini
ACCURACY_MODEL=claude-sonnet-4-6
EVAL_MODEL_OPENAI=gpt-5.4-mini
EVAL_MODEL_ANTHROPIC=claude-sonnet-4-6
QUERY_EXPANSION_MODEL=gpt-5.4-mini

# Performance (optional)
ENABLE_CACHING=true
LOG_LEVEL=INFO

# CORS (optional)
# CORS_ORIGINS=["http://localhost:5173","http://localhost:3000"]