@juspay/neurolink
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Universal AI Development Platform with working MCP integration, multi-provider support, voice (TTS/STT/realtime), and professional CLI. 58+ external MCP servers discoverable, multimodal file processing, RAG pipelines. Build, test, and deploy AI applicatio
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TypeScript
/**
* Semantic Chunker
*
* LLM-powered semantic chunking that groups related content together.
* Uses embedding similarity to determine natural breakpoints.
* Best for complex documents where meaning should drive segmentation.
*/
import type { BaseChunkerConfig, Chunk, Chunker, ChunkerValidationResult, SemanticChunkerConfig } from "../../types/index.js";
/**
* Semantic chunker implementation
* Uses embedding similarity to find natural content boundaries
*/
export declare class SemanticChunker implements Chunker {
readonly strategy: "semantic";
chunk(text: string, config?: SemanticChunkerConfig): Promise<Chunk[]>;
/**
* Split text into initial segments for embedding
*/
private splitIntoSegments;
/**
* Get embeddings for segments
*/
private getEmbeddings;
/**
* Find semantic breakpoints using cosine similarity
*/
private findSemanticBreakpoints;
/**
* Group segments based on breakpoints and size limits
*/
private groupSegments;
/**
* Calculate cosine similarity between two vectors
*/
private cosineSimilarity;
/**
* Fallback to simple chunking when embeddings fail
*/
private fallbackChunk;
validateConfig(config: BaseChunkerConfig): ChunkerValidationResult;
}