82 lines
1.7 KiB
Markdown
82 lines
1.7 KiB
Markdown
# haiku.rag Docker Image
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The full haiku.rag Docker image includes all features and extras (docling, voyageai, mxbai). You can build it locally using the provided Dockerfile.
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## Building the Image
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Build the full image with all features:
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```bash
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docker build -f docker/Dockerfile -t haiku-rag .
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```
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This creates an image with:
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- All document processing capabilities (Docling)
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- VoyageAI embeddings
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- MixedBread AI reranking
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- Full feature set
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## Configuration
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Create a configuration file `haiku.rag.yaml`:
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```yaml
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# haiku.rag.yaml
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environment: production
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embeddings:
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model:
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provider: ollama
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name: nomic-embed-text
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vector_dim: 768
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qa:
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model:
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provider: ollama
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name: qwen3
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```
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See [Configuration docs](https://ggozad.github.io/haiku.rag/configuration/) for all available options.
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## Running
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Mount your config file and data directory:
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```bash
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docker run -p 8001:8001 \
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-v /path/to/haiku.rag.yaml:/app/haiku.rag.yaml \
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-v /path/to/data:/data \
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haiku-rag
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```
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To enable file monitoring, also mount a documents directory:
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```bash
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docker run -p 8001:8001 \
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-v /path/to/haiku.rag.yaml:/app/haiku.rag.yaml \
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-v /path/to/data:/data \
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-v /path/to/docs:/docs \
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haiku-rag haiku-rag serve --mcp --monitor
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```
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Your `haiku.rag.yaml` must reference the **container path** for monitoring:
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```yaml
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monitor:
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directories:
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- /docs # Container path, not host path
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```
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For API keys (OpenAI, Anthropic, etc.), pass them as environment variables:
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```bash
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docker run -p 8001:8001 \
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-v /path/to/haiku.rag.yaml:/app/haiku.rag.yaml \
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-v /path/to/data:/data \
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-e OPENAI_API_KEY=your-key-here \
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haiku-rag
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```
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## Docker Compose
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See `examples/docker/` for a complete setup example.
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