75 lines
1.9 KiB
Markdown
75 lines
1.9 KiB
Markdown
# Installation
|
|
|
|
## Choose Your Package
|
|
|
|
**haiku.rag** is available in two packages:
|
|
|
|
### Full Package (Recommended)
|
|
|
|
```bash
|
|
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)
|
|
|
|
```bash
|
|
# 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 formats
|
|
- `voyageai` - VoyageAI embeddings
|
|
- `mxbai` - MixedBread AI reranking
|
|
- `cohere` - Cohere reranking
|
|
- `zeroentropy` - 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](configuration.md) 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:
|
|
|
|
```bash
|
|
haiku-rag download-models
|
|
```
|
|
|
|
This will download Docling models and pull any Ollama models referenced by your current configuration.
|
|
|
|
## Docker
|
|
|
|
```bash
|
|
docker pull ghcr.io/ggozad/haiku.rag:latest
|
|
```
|
|
|
|
Run the container with all services:
|
|
|
|
```bash
|
|
docker run -p 8000:8000 -p 8001:8001 -v $(pwd)/data:/data ghcr.io/ggozad/haiku.rag:latest
|
|
```
|
|
|
|
This starts the MCP server on port 8001, with data persisted to `./data`.
|