README
¶
Apache Answer Plugin: Qdrant Vector Search
This plugin enables semantic/vector search in Apache Answer using Qdrant.
Prerequisites
- Qdrant instance (self-hosted or Qdrant Cloud)
- An OpenAI-compatible embedding API (e.g., OpenAI, Azure OpenAI, or any compatible provider)
Installation
Build Apache Answer with this plugin:
./answer build --with github.com/apache/answer-plugins/vector-search-qdrant
Configuration
After enabling the plugin in the Admin UI (Admin > Plugins > Vector Search), configure the following fields:
| Field | Description | Example |
|---|---|---|
| Qdrant Endpoint | Qdrant gRPC endpoint | localhost:6334 |
| Qdrant API Key | API key for Qdrant 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 Qdrant authentication and a separate one for the embedding API.
How It Works
- Embedding dimensions are auto-detected from the configured model. No manual dimension configuration is needed.
- On first configuration, the plugin creates a collection
answer_vector_embeddingswith cosine distance metric. - If the embedding model changes and produces different dimensions, the collection is automatically deleted and recreated.
- Uses deterministic UUIDs derived from object IDs for consistent upsert behavior.
- Communicates with Qdrant via gRPC for high performance.
- A full sync of all questions/answers is triggered when the plugin starts.
Running Qdrant Locally
Using Docker:
docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant
The gRPC endpoint will be localhost:6334 and the REST API at localhost:6333.
License
Documentation
¶
Index ¶
- Variables
- type VectorSearchConfig
- type VectorSearchEngine
- func (e *VectorSearchEngine) ConfigFields() []plugin.ConfigField
- func (e *VectorSearchEngine) ConfigReceiver(config []byte) error
- func (e *VectorSearchEngine) DeleteContent(ctx context.Context, objectID string) error
- func (e *VectorSearchEngine) Description() plugin.VectorSearchDesc
- func (e *VectorSearchEngine) Info() plugin.Info
- func (e *VectorSearchEngine) RegisterSyncer(ctx context.Context, syncer plugin.VectorSearchSyncer)
- func (e *VectorSearchEngine) SearchSimilar(ctx context.Context, query string, topK int) ([]plugin.VectorSearchResult, error)
- func (e *VectorSearchEngine) UpdateContent(ctx context.Context, content *plugin.VectorSearchContent) error
Constants ¶
This section is empty.
Variables ¶
View Source
var Info embed.FS
Functions ¶
This section is empty.
Types ¶
type VectorSearchConfig ¶
type VectorSearchConfig struct {
Endpoint string `json:"endpoint"`
APIKey string `json:"api_key"`
EmbeddingAPIHost string `json:"embedding_api_host"`
EmbeddingAPIKey string `json:"embedding_api_key"`
EmbeddingModel string `json:"embedding_model"`
EmbeddingLevel string `json:"embedding_level"`
SimilarityThreshold float64 `json:"similarity_threshold"`
}
VectorSearchConfig holds all plugin configuration.
type VectorSearchEngine ¶
type VectorSearchEngine struct {
Config *VectorSearchConfig
// contains filtered or unexported fields
}
VectorSearchEngine implements plugin.VectorSearch using Qdrant.
func (*VectorSearchEngine) ConfigFields ¶
func (e *VectorSearchEngine) ConfigFields() []plugin.ConfigField
func (*VectorSearchEngine) ConfigReceiver ¶
func (e *VectorSearchEngine) ConfigReceiver(config []byte) error
func (*VectorSearchEngine) DeleteContent ¶
func (e *VectorSearchEngine) DeleteContent(ctx context.Context, objectID string) error
func (*VectorSearchEngine) Description ¶
func (e *VectorSearchEngine) Description() plugin.VectorSearchDesc
func (*VectorSearchEngine) Info ¶
func (e *VectorSearchEngine) Info() plugin.Info
func (*VectorSearchEngine) RegisterSyncer ¶
func (e *VectorSearchEngine) RegisterSyncer(ctx context.Context, syncer plugin.VectorSearchSyncer)
func (*VectorSearchEngine) SearchSimilar ¶
func (e *VectorSearchEngine) SearchSimilar(ctx context.Context, query string, topK int) ([]plugin.VectorSearchResult, error)
func (*VectorSearchEngine) UpdateContent ¶
func (e *VectorSearchEngine) UpdateContent(ctx context.Context, content *plugin.VectorSearchContent) error
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