Apache Answer Plugin: pgvector Vector Search

This plugin enables semantic/vector search in Apache Answer using PostgreSQL with the pgvector extension.

Prerequisites

PostgreSQL 12+ with the pgvector extension installed
An OpenAI-compatible embedding API (e.g., OpenAI, Azure OpenAI, or any compatible provider)

Build Apache Answer with this plugin:

./answer build --with github.com/apache/answer-plugins/vector-search-pgvector

After enabling the plugin in the Admin UI (Admin > Plugins > Vector Search), configure the following fields:

Field	Description	Example
DSN	PostgreSQL connection string	`postgres://user:pass@localhost:5432/answer?sslmode=disable`
Embedding API Host	OpenAI-compatible API base URL	`https://api.openai.com`
Embedding API Key	API key for the embedding service	`sk-...`
Embedding Model	Model name for generating embeddings	`text-embedding-3-small`
Embedding Level	`question` embeds question + all answers + comments together; `answer` embeds each answer separately	`question`
Similarity Threshold	Minimum cosine similarity score (0-1). Default `0` means no filtering	`0.5`

Embedding dimensions are auto-detected from the configured model. No manual dimension configuration is needed.
On first configuration, the plugin creates a table answer_vector_embeddings with a vector column matching the detected dimensions.
If the embedding model changes and produces different dimensions, the table is automatically dropped and recreated.
Uses cosine similarity (<=> operator) for vector search.
A full sync of all questions/answers is triggered when the plugin starts.

Ensure the pgvector extension is installed in your PostgreSQL database:

CREATE EXTENSION IF NOT EXISTS vector;