2.7 KiB
Installation
Choose Your Package
haiku.rag is available in two packages:
Full Package (Recommended)
uv pip install haiku.rag
The full package includes all features and extras:
- Document processing (Docling) - PDF, DOCX, PPTX, images, and 40+ file formats
- All embedding providers - VoyageAI
- All rerankers - MixedBread AI, Cohere, Zero Entropy
This is the easiest way to get started with all features enabled.
Slim Package (Minimal Dependencies)
# Minimal installation (no document processing)
uv pip install haiku.rag-slim
# With document processing
uv pip install haiku.rag-slim[docling]
# With specific providers
uv pip install haiku.rag-slim[docling,voyageai,mxbai]
The slim package has minimal dependencies and lets you install only what you need:
docling- PDF, DOCX, PPTX, images, and other document formatsvoyageai- VoyageAI embeddingsmxbai- MixedBread AI rerankingcohere- Cohere rerankingzeroentropy- Zero Entropy reranking
Built-in providers (no extras needed):
- Ollama (default embedding provider)
- OpenAI (GPT models for QA and embeddings)
- Anthropic (Claude models for QA)
See Configuration for configuring providers including advanced options like vLLM.
Requirements
- Python 3.12+
- Ollama (for default embeddings and QA)
Pre-download Models (Optional)
You can prefetch all required runtime models before first use:
haiku-rag download-models
This will download:
- Docling models for document processing
- HuggingFace tokenizer models for chunking
- Any Ollama models referenced by your current configuration
Remote Processing (Optional)
When using haiku.rag-slim, you can skip installing the docling extra and instead use docling-serve for remote document processing. This is useful for:
- Keeping dependencies minimal
- Offloading heavy document processing to a dedicated service
- Production deployments with separate processing infrastructure
See Remote processing for setup instructions and Document Processing for configuration options.
Docker
Two Docker images are available:
Full Image (Self-contained)
Includes all features and document processing built-in:
docker pull ghcr.io/ggozad/haiku.rag:latest
docker run -p 8001:8001 -v $(pwd)/data:/data ghcr.io/ggozad/haiku.rag:latest
Slim Image (Minimal)
Minimal dependencies - use with external docling-serve for document processing:
docker pull ghcr.io/ggozad/haiku.rag-slim:latest
See examples/docker/docker-compose.yml for a complete setup with docling-serve.