/**
 * Local VLM (Vision Language Model) MCP Tools
 *
 * Tools for Chandra local GPU image analysis of legal and medical documents.
 * Uses ChandraClient for analysis and VLMPipeline for batch processing.
 *
 * 100% local GPU processing via Chandra VLM.
 * NO cloud API calls, NO fallbacks.
 *
 * CRITICAL: NEVER use console.log() - stdout is reserved for JSON-RPC protocol.
 * Use console.error() for all logging.
 *
 * @module tools/vlm-local
 */
import { type ToolResponse, type ToolDefinition } from './shared.js';
/**
 * VLM is only available when TORCH_DEVICE is explicitly a GPU device.
 * 'auto' means the entrypoint hasn't resolved it yet (misconfiguration).
 * Matches the logic in health.ts: vlm_available = device starts with 'cuda' or is 'mps'.
 */
export declare function isVLMAvailable(): boolean;
/**
 * Handle ocr_vlm_describe - Generate detailed description of a single image using Chandra VLM
 *
 * Looks up the image in the database by image_id, runs local VLM analysis,
 * stores the result in the DB (updates images table vlm_description, vlm_model),
 * creates provenance records, and generates an embedding for searchability.
 */
export declare function handleVLMDescribe(params: Record<string, unknown>): Promise<ToolResponse>;
/**
 * Handle ocr_vlm_process - Process VLM on a single document or all pending images
 *
 * If document_id is provided, processes all images in that document.
 * If document_id is omitted, processes all pending images across all documents.
 */
export declare function handleVLMProcess(params: Record<string, unknown>): Promise<ToolResponse>;
/**
 * Handle ocr_vlm_status - Get VLM processing status and statistics
 *
 * Returns stats about processed/pending/failed images and model info.
 * Works on the currently selected database.
 */
export declare function handleVLMStatus(params: Record<string, unknown>): Promise<ToolResponse>;
/**
 * Local VLM tools collection for MCP server registration
 */
export declare const vlmLocalTools: Record<string, ToolDefinition>;
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