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@ -10,6 +10,7 @@ Retrieval-Augmented Generation (RAG) library on SQLite.
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- **Multiple embedding providers**: Ollama, VoyageAI, OpenAI
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- **Multiple QA providers**: Ollama, OpenAI, Anthropic
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- **Hybrid search**: Vector + full-text search with Reciprocal Rank Fusion
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- **Reranking**: Optional result reranking with MixedBread AI or Cohere
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- **Question answering**: Built-in QA agents on your documents
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- **File monitoring**: Auto-index files when run as server
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- **40+ file formats**: PDF, DOCX, HTML, Markdown, audio, URLs
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@ -49,8 +50,8 @@ async with HaikuRAG("database.db") as client:
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# Add document
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doc = await client.create_document("Your content")
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# Search
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results = await client.search("query")
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# Search (with optional reranking)
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results = await client.search("query", rerank=True)
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for chunk, score in results:
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print(f"{score:.3f}: {chunk.content}")
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@ -103,6 +103,35 @@ QA_MODEL="claude-3-5-haiku-20241022" # or claude-3-5-sonnet-20241022, etc.
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ANTHROPIC_API_KEY="your-api-key"
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```
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## Reranking
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Reranking improves search quality by re-ordering the initial search results using specialized models. When enabled, the system retrieves more candidates (3x the requested limit) and then reranks them to return the most relevant results.
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### MixedBread AI (Default)
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```bash
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RERANK=true
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RERANK_PROVIDER="mxbai"
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RERANK_MODEL="mixedbread-ai/mxbai-rerank-base-v2"
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```
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### Cohere
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For Cohere reranking, install with Cohere extras:
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```bash
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uv pip install haiku.rag --extra cohere
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```
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Then configure:
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```bash
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RERANK=true
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RERANK_PROVIDER="cohere"
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RERANK_MODEL="rerank-v3.5"
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COHERE_API_KEY="your-api-key"
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```
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## Other Settings
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### Database and Storage
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