@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
/**
* Message Builder Utility
* Centralized logic for building message arrays from TextGenerationOptions
* Enhanced with multimodal support for images
*/
import type { ModelMessage } from "ai";
import type { GenerateOptions, MultimodalChatMessage, StreamOptions, TextGenerationOptions } from "../types/index.js";
/**
* Type-safe conversion from MultimodalChatMessage[] to ModelMessage[]
* Filters out invalid content and ensures strict ModelMessage contract compliance
*/
export declare function convertToModelMessages(messages: MultimodalChatMessage[]): ModelMessage[];
/**
* Build a properly formatted message array for AI providers
* Combines system prompt, conversation history, and current user prompt
* Supports both TextGenerationOptions and StreamOptions
* Enhanced with CSV file processing support
*/
export declare function buildMessagesArray(options: TextGenerationOptions | StreamOptions): Promise<ModelMessage[]>;
/**
* Process the unified files array with auto-detection.
* Handles lazy file registration, full processing, and preview injection.
*
* Exported so providers that bypass BaseProvider.generate() (e.g.
* GoogleVertex's native @google/genai path) can still preprocess
* `input.files` — without this, mimetype-hint and text-file inputs
* would silently never reach the model on those paths.
*/
export declare function processUnifiedFilesArray(options: GenerateOptions, maxSize: number, provider: string): Promise<void>;
/**
* Build multimodal message array with image support
* Detects when images are present and routes through provider adapter
*/
export declare function buildMultimodalMessagesArray(options: GenerateOptions, provider: string, model: string): Promise<MultimodalChatMessage[]>;