76 lines
3.3 KiB
Markdown
76 lines
3.3 KiB
Markdown
# haiku.rag
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Agentic RAG built on [LanceDB](https://lancedb.com/), [Pydantic AI](https://ai.pydantic.dev/), and [Docling](https://docling-project.github.io/docling/).
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## Features
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- **Hybrid search** — Vector + full-text with Reciprocal Rank Fusion
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- **Question answering** — QA agents with citations (page numbers, section headings)
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- **Reranking** — MxBAI, Cohere, Zero Entropy, or vLLM
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- **Research agents** — Multi-agent workflows via pydantic-graph: plan, search, evaluate, synthesize
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- **RLM agent** — Complex analytical tasks via sandboxed Python code execution (aggregation, computation, multi-document analysis)
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- **Conversational RAG** — Chat TUI and web application for multi-turn conversations with session memory
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- **Document structure** — Stores full [DoclingDocument](https://docling-project.github.io/docling/concepts/docling_document/), enabling structure-aware context expansion
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- **Multiple providers** — Embeddings: Ollama, OpenAI, VoyageAI, LM Studio, vLLM. QA/Research: any model supported by Pydantic AI
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- **Local-first** — Embedded LanceDB, no servers required. Also supports S3, GCS, Azure, and LanceDB Cloud
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- **CLI & Python API** — Full functionality from command line or code
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- **MCP server** — Expose as tools for AI assistants (Claude Desktop, etc.)
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- **Visual grounding** — View chunks highlighted on original page images
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- **File monitoring** — Watch directories and auto-index on changes
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- **Time travel** — Query the database at any historical point with `--before`
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- **Inspector** — TUI for browsing documents, chunks, and search results
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## Quick Start
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Install haiku.rag:
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```bash
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uv pip install haiku.rag
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```
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Use from Python:
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```python
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from haiku.rag.client import HaikuRAG
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async with HaikuRAG("database.lancedb", create=True) as client:
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# Add a document
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doc = await client.create_document("Your content here")
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# Search documents
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results = await client.search("query")
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# Ask questions (returns answer and citations)
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answer, citations = await client.ask("Who is the author of haiku.rag?")
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```
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Or use the CLI:
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```bash
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haiku-rag add "Your document content"
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haiku-rag add "Your document content" --meta author=alice
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haiku-rag add-src /path/to/document.pdf --title "Q3 Financial Report" --meta source=manual
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haiku-rag search "query"
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haiku-rag ask "Who is the author of haiku.rag?"
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haiku-rag chat # Interactive conversation mode
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```
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## Documentation
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- [Getting started](tutorial.md) - Tutorial
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- [Installation](installation.md) - Install haiku.rag with different providers
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- [Architecture](architecture.md) - System overview and data flow
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- [Configuration](configuration/index.md) - Environment variables and settings
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- [CLI](cli.md) - Command line interface usage
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- [Python](python.md) - Python API reference
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- [Custom Pipelines](custom-pipelines.md) - Build custom processing workflows
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- [Agents](agents/index.md) - QA, chat, and research agents
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- [RLM Agent](agents/rlm.md) - Complex analytical tasks via code execution
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- [Applications](apps.md) - Chat TUI, web app, and inspector
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- [Server](server.md) - File monitoring and server mode
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- [MCP](mcp.md) - Model Context Protocol integration
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- [Remote processing](remote-processing.md) - Remote document processing with docling-serve
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## License
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This project is licensed under the [MIT License](https://raw.githubusercontent.com/ggozad/haiku.rag/main/LICENSE).
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