@venturekit-pro/ai API

Functions

Embeddings

Function	Description
`createEmbedder(config)`	Create an embedder for generating vectors
`createEmbeddingConfig(options)`	Create embedding configuration

Embedder interface:

Method	Description
`embed(text: string)`	Generate a single vector
`embedBatch(texts: string[])`	Generate vectors for multiple texts

Vector Stores

Function	Description
`createVectorStore(config)`	Create a vector store instance
`createVectorStoreConfig(options)`	Create vector store configuration

VectorStore interface:

Method	Description
`upsert(items)`	Insert or update vectors
`query(vector, options)`	Query similar vectors

RAG Pipeline

Function	Description
`createRagPipeline(config)`	Create a RAG pipeline
`createRagConfig(options)`	Create RAG configuration
`chunkText(text, options)`	Split text into chunks

RagPipeline interface:

Method	Description
`ingest(chunks)`	Ingest document chunks
`retrieve(query, options)`	Retrieve relevant context

Agents

Function	Description
`createAgent(config)`	Create an AI agent
`createAgentConfig(options)`	Create agent configuration
`defineTool(definition)`	Define a tool for agent use

Agent interface:

Method	Description
`run(prompt)`	Run the agent with a user prompt

Types

AI-related types are exported from ./types/index.js, including embedding configs, vector store configs, RAG configs, agent configs, and tool definitions.

Constants

Constant	Description
`DEFAULT_EMBEDDING_CONFIG`	Default embedding configuration
`DEFAULT_VECTOR_STORE_CONFIG`	Default vector store configuration
`DEFAULT_RAG_CONFIG`	Default RAG configuration
`DEFAULT_AGENT_CONFIG`	Default agent configuration