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Vector Databases: Pinecone, Weaviate & pgvector · Aula

Configurando a Extensão pgvector

Instale e configure a extensão pgvector para adicionar tipos e funções de dados vetoriais ao PostgreSQL.

Configurando a Extensão pgvector é uma aula grátis de Vector Databases: Pinecone, Weaviate & pgvector no CoddyKit. Esta é a aula 1 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de Vector Databases: Pinecone, Weaviate & pgvector, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Vector Databases: Pinecone, Weaviate & pgvector inclui 4 aulas no total.

Partes desta aula ainda não foram traduzidas e aparecem em inglês.

Meet pgvector: Vector Power

Welcome to pgvector! This powerful extension brings vector database capabilities directly to your PostgreSQL database.

Why is this cool? It means you can store, index, and query vector embeddings alongside your traditional data, all within the familiar PostgreSQL environment. No need for a separate vector database for simple cases!

Why Use pgvector?

pgvector is perfect for adding semantic search, recommendation systems, and AI features to applications that already use PostgreSQL.

  • Simplicity: Use your existing database skills.
  • Integration: Vectors live with your other data.
  • Cost-Effective: Often cheaper than dedicated vector databases for smaller scales.

Prerequisites: PostgreSQL

Before we can install pgvector, you need to have PostgreSQL installed and running on your system. This lesson assumes you have a working PostgreSQL instance and administrative access.

If you don't have PostgreSQL, you'll need to install it first. Many operating systems offer packages for easy installation.

Connecting to PostgreSQL

To manage your PostgreSQL database and install extensions, you'll typically use the psql command-line tool. Open your terminal or command prompt and connect to your database.

You might need to specify the user and database. For example, connecting as the default 'postgres' user to the default database:

psql -U postgres

Enabling the pgvector Extension

Once you're connected to your PostgreSQL database via psql, enabling an extension is straightforward. PostgreSQL has a built-in mechanism for this.

The key command you'll use is CREATE EXTENSION. This command tells PostgreSQL to load and activate the functionality provided by the specified extension.

The CREATE EXTENSION Command

To enable pgvector, simply run the following command. Make sure you are connected to the specific database where you want to use pgvector.

Note: You might need superuser privileges to create extensions.

CREATE EXTENSION vector;

Verifying Installation

After running CREATE EXTENSION vector;, it's good practice to verify that the extension was successfully installed and is active in your database.

PostgreSQL provides a command within psql to list all installed extensions. This helps confirm pgvector is ready to use.

Listing Active Extensions

Inside psql, use the \dx command to list all installed extensions. You should see 'vector' in the list if the installation was successful.

After confirming, you can exit psql by typing \q.

\dx

Introducing the Vector Type

With pgvector installed, you now have access to a new data type: vector. This type allows you to store arrays of floating-point numbers, which are perfect for embeddings.

When defining a column, you'll specify the vector type and its dimension (e.g., vector(1536) for OpenAI's embeddings).

Quick Check

You've just learned how to enable the pgvector extension. Let's test your understanding!

Recap: pgvector Setup

Great job! In this lesson, you've successfully learned how to set up pgvector.

  • We understood what pgvector is and its benefits.
  • We practiced connecting to PostgreSQL using psql.
  • You now know how to enable the extension with CREATE EXTENSION vector;.
  • Finally, you can verify its installation using \dx.

Now your PostgreSQL database is ready to store and work with vector embeddings!

Perguntas Frequentes

A aula “Configurando a Extensão pgvector” é grátis?

Sim — o texto completo de “Configurando a Extensão pgvector” é grátis para ler aqui na web. Para praticá-la interativamente (um editor de código integrado e um tutor de IA 24/7) e desbloquear o restante do curso de Vector Databases: Pinecone, Weaviate & pgvector, atualize para CoddyKit PRO. O curso de Vector Databases: Pinecone, Weaviate & pgvector inclui 4 aulas no total.

O que vou aprender em “Configurando a Extensão pgvector”?

Instale e configure a extensão pgvector para adicionar tipos e funções de dados vetoriais ao PostgreSQL. Você pratica Vector Databases: Pinecone, Weaviate & pgvector com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.

Preciso ter experiência prévia para começar Vector Databases: Pinecone, Weaviate & pgvector?

Nenhuma experiência prévia é necessária. Vector Databases: Pinecone, Weaviate & pgvector no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 1 de 4.

Quanto tempo leva a aula “Configurando a Extensão pgvector”?

A maioria das aulas CoddyKit leva cerca de 5–10 minutos. Cada uma é compacta e interativa, então você faz progresso constante e retoma exatamente de onde parou entre web e app.

Posso escrever e executar código nesta aula de Vector Databases: Pinecone, Weaviate & pgvector?

Sim. Cada aula de Vector Databases: Pinecone, Weaviate & pgvector inclui um editor de código integrado, então você escreve e executa código real direto no navegador e recebe feedback de IA instantaneamente — nenhuma configuração local necessária.

Todas as aulas deste curso

  1. Configurando a Extensão pgvector
  2. Armazenando Vetores no PostgreSQL
  3. Executando Consultas de Similaridade
  4. Escolhendo métricas de distância no pgvector
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