Semantic Search
Vector Search
Semantic Search
Search for API collections using natural language
POST
Semantic Search
Authentication
Supports both Firebase and API Key authentication.Request Body
string
required
Natural language search query
integer
default:"10"
Maximum number of results (1-100)
Example Request
Response
Returns matching collections ordered by similarity score.string
Collection UUID
string
Collection display name
number
Cosine similarity score (0-1, higher is better)
Example Response
How It Works
- Query Embedding - Your query is converted to a 768-dimensional vector using Vertex AI
- Similarity Search - pgvector performs cosine similarity search against all collection embeddings
- Access Filtering - Results are filtered to collections you have access to
- Ranking - Results are ordered by similarity score (highest first)
Access Control
- Admins: Search across all collections
- Clients: Search only across collections they have access to

