Apache Answer Plugin: Weaviate Vector Search

This plugin enables semantic/vector search in Apache Answer using Weaviate.

Prerequisites

Weaviate instance (self-hosted or Weaviate Cloud)
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-weaviate

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

Field	Description	Example
Weaviate Endpoint	Weaviate server URL	`http://localhost:8080`
Weaviate API Key	API key for Weaviate authentication (optional for local instances)
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`

Note: This plugin uses a dual API key pattern -- one for Weaviate authentication and a separate one for the embedding API.

Weaviate handles vector dimensions automatically via its vectorizer: none configuration, so no manual dimension setup is needed.
On first configuration, the plugin creates a class AnswerVector with cosine distance metric.
Uses deterministic UUIDs derived from object IDs for consistent upsert behavior.
A full sync of all questions/answers is triggered when the plugin starts.