daft-examples/.env.example at main · Eventual-Inc/daft-examples · GitHub

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# Daft Examples - Environment Variables
# Copy this file to .env and fill in your API keys:
#   cp .env.example .env

# ============================================================================
# Required for Quickstart Examples (01-05)
# ============================================================================

# OpenAI API Key (required for most examples)
# Get yours at: https://platform.openai.com/api-keys
OPENAI_API_KEY=sk-proj-

# ============================================================================
# Optional for Quickstart Examples
# ============================================================================

# Turbopuffer API Key (optional - for vector search in quickstart/02)
# Get yours at: https://turbopuffer.com
# If not set, quickstart/02 will skip the database write step
TURBOPUFFER_API_KEY=

# ============================================================================
# Optional for Advanced Examples
# ============================================================================

# OpenRouter API Key (for multi-model access)
# Get yours at: https://openrouter.ai/keys
# Used in: examples/prompt/prompt_session.py
OPENROUTER_API_KEY=sk-or-v1-

# HuggingFace Token (for private datasets)
# Get yours at: https://huggingface.co/settings/tokens
# Most examples use public datasets and don't need this
HF_TOKEN=

# AWS Credentials (for S3 data ingestion examples)
# Used in: datasets/common_crawl/, datasets/tpch/
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_SESSION_TOKEN=

# Databricks Unity Catalog (for UC integration examples)
# Used in: examples/prompt/prompt_unity_catalog.py
UC_TABLE_NAME=

# Lakehouse Analytics pipeline (optional - local mode does not need these)
# Used in: pipelines/lakehouse_analytics/
# Set GCP_PROJECT and GCS_BUCKET (both, your own project and bucket) for BigLake
# mode, or AWS_S3_BUCKET for AWS Glue mode. There are no defaults for these.
# Leave all unset for local SQLite Iceberg.
GCP_PROJECT=
GCS_BUCKET=
AWS_S3_BUCKET=
AWS_REGION=us-east-1
LAKEHOUSE_NAMESPACE=analytics
LAKEHOUSE_DIR=.lakehouse

# Generic SQL backfill into the lakehouse
# BACKFILL_QUERY and BACKFILL_SOURCE_TABLE are mutually exclusive.
BACKFILL_SOURCE_URL=
BACKFILL_QUERY=
BACKFILL_SOURCE_TABLE=
BACKFILL_TARGET_TABLE=
BACKFILL_KEY=
BACKFILL_TARGET_NAMESPACE=analytics

# ============================================================================
# Quick Start Guide
# ============================================================================
#
# For hackathon participants - minimum viable setup:
#   1. Copy this file: cp .env.example .env
#   2. Add your OpenAI API key
#   3. Run: uv run quickstart/01_hello_world_prompt.py
#
# That's it! Other API keys are optional and only needed for specific examples.
#
# ============================================================================