pgvector examples for Zig
Follow the instructions for your database library:
Or check out some examples:
- Embeddings with OpenAI
- Binary embeddings with Cohere
- Hybrid search with Ollama (Reciprocal Rank Fusion)
- Sparse search with Text Embeddings Inference
Enable the extension
_ = try conn.exec("CREATE EXTENSION IF NOT EXISTS vector", .{});Create a table
_ = try conn.exec("CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3))", .{});Insert vectors
const embedding1 = [_]f32{ 1, 2, 3 };
const embedding2 = [_]f32{ 4, 5, 6 };
_ = try conn.exec("INSERT INTO items (embedding) VALUES ($1::float4[]), ($2::float4[])", .{ embedding1, embedding2 });Get the nearest neighbors
const embedding3 = [_]f32{ 3, 1, 2 };
var result = try conn.query("SELECT id FROM items ORDER BY embedding <-> $1::float4[]::vector LIMIT 5", .{embedding3});Add an approximate index
_ = try conn.exec("CREATE INDEX ON items USING hnsw (embedding vector_l2_ops)", .{});
// or
_ = try conn.exec("CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)", .{});Use vector_ip_ops for inner product and vector_cosine_ops for cosine distance
See a full example
Import libpq
const pg = @cImport({
@cInclude("libpq-fe.h");
});Enable the extension
const res = pg.PQexec(conn, "CREATE EXTENSION IF NOT EXISTS vector");Create a table
const res = pg.PQexec(conn, "CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3))");Insert vectors
const paramValues = [2:0][*c]const u8{ "[1,2,3]", "[4,5,6]" };
const res = pg.PQexecParams(conn, "INSERT INTO items (embedding) VALUES ($1), ($2)", 2, null, ¶mValues, null, null, 0);Get the nearest neighbors
const paramValues = [1:0][*c]const u8{"[3,1,2]"};
const res = pg.PQexecParams(conn, "SELECT * FROM items ORDER BY embedding <-> $1 LIMIT 5", 1, null, ¶mValues, null, null, 0);Add an approximate index
const res = pg.PQexec(conn, "CREATE INDEX ON items USING hnsw (embedding vector_l2_ops)");
// or
const res = pg.PQexec(conn, "CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)");Use vector_ip_ops for inner product and vector_cosine_ops for cosine distance
See a full example
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
git clone https://github.com/pgvector/pgvector-zig.git
cd pgvector-zig
createdb pgvector_zig_test
zig build
zig-out/bin/pg
zig-out/bin/libpqSpecify the path to libpq if needed:
zig build --search-prefix /opt/homebrew/opt/libpqTo run an example:
createdb pgvector_example
zig-out/bin/openai