vibed/edu/.nbd/tickets/b7c95f.md

+++ title = "vector-db" priority = 5 status = "done" ticket_type = "project" dependencies = ["21d9be", "584e0c", "99e1d9", "d9f850", "6ec5ff", "37cdd5", "081a55", "5674ce", "4c961f", "1ef9f4", "e8be9a", "5ed295"] +++

Project: Vector Database Self-Guided Course

This is the top-level project ticket for edu/src/vector-db.md — a self-guided mdbook course on vector databases in the Vibed Learning site (edu/).

The course is modelled on edu/src/markov.md. It teaches vector databases through 12 sections across 4 parts, mixing reading lessons and hands-on Rust programming exercises using Turso (libsql crate) and sqlite-vec for local vector storage.

Course structure

#	Title	Status
§1	What Is a Vector?	Written in full
§2	Embeddings	Stub [nbd:584e0c]
§3	Vector Similarity	Stub [nbd:99e1d9]
§4	What Is a Vector Database?	Stub [nbd:d9f850]
§5	Under the Hood: ANN Algorithms	Stub [nbd:6ec5ff]
§6	Setting Up	Written in full
§7	Exercise 1 — Storing and Retrieving Vectors	Stub [nbd:081a55]
§8	Exercise 2 — K-Nearest Neighbor Search	Stub [nbd:5674ce]
§9	Generating Embeddings in Rust	Stub [nbd:4c961f]
§10	Exercise 3 — Semantic Document Search	Stub [nbd:1ef9f4]
§11	Exercise 4 — Recommendation Engine	Stub [nbd:e8be9a]
§12	Exercise 5 — Retrieval-Augmented Generation	Stub [nbd:5ed295]

Filling a stub

1. Open edu/src/vector-db.md
2. Find the section (e.g. ### 2. Embeddings)
3. Replace the stub line (🚧 Full content tracked in [nbd:...]) with full content
4. Run mdbook build from edu/ — must pass cleanly
5. Mark the section ticket done

Tech stack used in exercises

• Runtime: Tokio async
• DB crate: libsql = "0.9" (Turso / libSQL Rust client)
• Vector support: sqlite-vec, built into libsql — no extra install
• Embeddings: fastembed crate (local) or OpenAI-compatible HTTP API
• Local connection: Builder::new_local("vectors.db").build().await?
• Vector column type: F32_BLOB(d) where d = embedding dimension
• KNN query: vector_top_k('table', vector('[...]'), k) table-valued function
• Distance function: vector_distance_cos(a, b) — 0 = identical, 2 = opposite

This project ticket closes when all 12 section tickets are done and mdbook build passes.