---
title: Agent Course Test
emoji: 🦀
colorFrom: green
colorTo: yellow
sdk: gradio
sdk_version: 5.29.1
app_file: app.py
pinned: false
license: mit
short_description: Agent model to obtain huggingface agent course cert
hf_oauth: true
hf_oauth_expiration_minutes: 480
---


Script to setting up tables and vector search
 "CREATE EXTENSION IF NOT EXISTS vector;"
 """
CREATE TABLE IF NOT EXISTS documents2 (
    id BIGINT PRIMARY KEY,
    content TEXT,
    metadata JSONB,
    embedding VECTOR(1536)
);
"""

create or replace function match_documents_2(
  query_embedding vector(1536),
  match_count int default 5
)
returns table (
  id bigint,
  content text,
  metadata jsonb,
  embedding vector
)
language sql
as $$
  select id, content, metadata, embedding
  from documents2
  order by embedding <#> query_embedding
  limit match_count;
$$;