Search EmergentDB for similar vectors and rank documents by similarity.
npx skills add https://github.com/justrach/emergent-sdk --skill emdb-search
Please help me install this Agent Skill. Skill: emdb-search Source: https://github.com/justrach/emergent-sdk/tree/main/skills/emdb-search Command: npx skills add https://github.com/justrach/emergent-sdk --skill emdb-search
EmergentDB users need to locate documents by vector similarity and perform semantic search across stored vectors to derive actionable results.
Invoke the EmergentDB search with your query vector to retrieve the top matching documents.
High-intent search queries and answers about installing and using this skill.
Semantic search in EmergentDB is performed by querying with a vector to retrieve and rank documents by vector similarity. You provide a query vector, specify the number of top results, and receive a structured object with matching ids and scores.
Yes, k-nearest-neighbor search supports an includeMetadata flag to retrieve document metadata. When enabled, the structured results object returns ids, scores, and the associated metadata for each matched vector.
Scoping vector similarity search to a subset of documents is achieved using namespace parameters. By specifying a namespace during your query, search operations are restricted to only retrieve similar vectors within that defined scope.
Yes, nearest-neighbor retrieval in EmergentDB can be applied to query expansion. By identifying and ranking similar vectors, the search API returns related content that expands the context of the original query vector.
A vector search API call requires a query vector and a k value to determine the number of results. Optional inputs include the includeMetadata flag and a namespace to scope the similarity ranking and filter the retrieved documents.
Vector search integration is supported through Python and TypeScript SDKs for rapid adoption. You invoke the search function with your query vector to retrieve top matching documents and receive a structured results object directly in your application.
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