haiku.rag/docs/configuration.md

Configuration

Configuration is done through the use of environment variables.

File Monitoring

Set directories to monitor for automatic indexing:

# Monitor single directory
MONITOR_DIRECTORIES="/path/to/documents"

# Monitor multiple directories
MONITOR_DIRECTORIES="/path/to/documents,/another_path/to/documents"

Embedding Providers

If you use Ollama, you can use any pulled model that supports embeddings.

Ollama (Default)

EMBEDDINGS_PROVIDER="ollama"
EMBEDDINGS_MODEL="mxbai-embed-large"
EMBEDDINGS_VECTOR_DIM=1024

VoyageAI

If you want to use VoyageAI embeddings you will need to install haiku.rag with the VoyageAI extras,

uv pip install haiku.rag --extra voyageai

EMBEDDINGS_PROVIDER="voyageai"
EMBEDDINGS_MODEL="voyage-3.5"
EMBEDDINGS_VECTOR_DIM=1024
VOYAGE_API_KEY="your-api-key"

OpenAI

If you want to use OpenAI embeddings you will need to install haiku.rag with the VoyageAI extras,

uv pip install haiku.rag --extra openai

and set environment variables.

EMBEDDINGS_PROVIDER="openai"
EMBEDDINGS_MODEL="text-embedding-3-small"  # or text-embedding-3-large
EMBEDDINGS_VECTOR_DIM=1536
OPENAI_API_KEY="your-api-key"

Question Answering Providers

Configure which LLM provider to use for question answering.

Ollama (Default)

QA_PROVIDER="ollama"
QA_MODEL="qwen3"
OLLAMA_BASE_URL="http://localhost:11434"

OpenAI

For OpenAI QA, you need to install haiku.rag with OpenAI extras:

uv pip install haiku.rag --extra openai

Then configure:

QA_PROVIDER="openai"
QA_MODEL="gpt-4o-mini"  # or gpt-4, gpt-3.5-turbo, etc.
OPENAI_API_KEY="your-api-key"

Anthropic

For Anthropic QA, you need to install haiku.rag with Anthropic extras:

uv pip install haiku.rag --extra anthropic

Then configure:

QA_PROVIDER="anthropic"
QA_MODEL="claude-3-5-haiku-20241022"  # or claude-3-5-sonnet-20241022, etc.
ANTHROPIC_API_KEY="your-api-key"

Other Settings

Database and Storage

# Default data directory (where SQLite database is stored)
DEFAULT_DATA_DIR="/path/to/data"

Document Processing

# Chunk size for document processing
CHUNK_SIZE=256

# Chunk overlap for better context
CHUNK_OVERLAP=32