Initial commit: RAG pipeline for semantic search over personal journal archive

Vector search with cross-encoder re-ranking, hybrid BM25+vector retrieval,
incremental index updates, and multiple LLM backends (Ollama local, OpenAI API).

NOTES.md

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+Simple query in ChatGPT produced 
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+Metric | Best For | Type | Notes
+-- | -- | -- | --
+Cosine Similarity | L2-normalized vectors | Similarity | Scale-invariant
+Dot Product | Transformer embeddings | Similarity | Fast, especially on GPUs
+Euclidean Distance | Raw vectors with meaningful norms | Distance | Sensitive to scale
+Jaccard | Sparse binary or set-based data | Similarity | Discrete features
+Soft Cosine | Sparse with semantic overlap | Similarity | Better for text-term overlap
+Learned Similarity | Fine-tuned deep models | Varies | Best accuracy, slowest retrieval
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