/**
 * Intelligence MCP Tools - Expose RuVector Intelligence via MCP
 *
 * These tools provide direct access to the full RuVector ecosystem:
 * - @ruvector/sona: Micro-LoRA (~0.05ms), EWC++, Trajectory tracking
 * - @ruvector/attention: MoE, Flash, Hyperbolic, Graph attention
 * - ruvector core: HNSW indexing (150x faster than brute force)
 *
 * Available both as MCP tools AND CLI hooks.
 */
import { z } from 'zod';
import { getIntelligence, routeTaskIntelligent, beginTaskTrajectory, recordTrajectoryStep, endTaskTrajectory, storePattern, findSimilarPatterns, getIntelligenceStats, forceLearningCycle, computeAttentionSimilarity, } from './intelligence-bridge.js';
/**
 * Intelligence Route Tool
 * Route tasks using SONA Micro-LoRA + MoE Attention + HNSW indexing
 */
export const intelligenceRouteTool = {
    name: 'intelligence_route',
    description: 'Route task using RuVector intelligence: SONA Micro-LoRA (~0.05ms) + MoE attention + HNSW (150x faster)',
    parameters: z.object({
        task: z.string().describe('Task description to route'),
        file: z.string().optional().describe('Optional file context'),
        errorContext: z.string().optional().describe('Optional error context for debugging tasks'),
        topK: z.number().optional().default(5).describe('Number of agent candidates to return'),
    }),
    execute: async ({ task, file, errorContext, topK }, { onProgress }) => {
        const startTime = Date.now();
        try {
            const result = await routeTaskIntelligent(task, {
                file,
                errorContext,
            });
            return {
                success: true,
                agent: result.agent,
                confidence: result.confidence,
                alternatives: result.routingResults.slice(1, topK).map(r => ({
                    agent: r.agentId,
                    confidence: r.confidence,
                })),
                features: result.usedFeatures,
                latencyMs: result.latencyMs,
                engine: 'ruvector-sona-moe-hnsw',
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Trajectory Start Tool
 * Begin trajectory tracking for learning from task execution
 */
export const intelligenceTrajectoryStartTool = {
    name: 'intelligence_trajectory_start',
    description: 'Begin SONA trajectory for learning from task execution. Returns trajectoryId for tracking.',
    parameters: z.object({
        task: z.string().describe('Task description'),
        agent: z.string().describe('Agent executing the task'),
        context: z.string().optional().describe('Additional context'),
    }),
    execute: async ({ task, agent, context }, { onProgress }) => {
        const startTime = Date.now();
        try {
            const fullTask = context ? `${task} [context: ${context}]` : task;
            const result = await beginTaskTrajectory(fullTask, agent);
            if (!result.success) {
                return {
                    success: false,
                    error: result.error || 'Failed to start trajectory',
                    latencyMs: Date.now() - startTime,
                    timestamp: new Date().toISOString(),
                };
            }
            return {
                success: true,
                trajectoryId: result.trajectoryId,
                message: `Trajectory ${result.trajectoryId} started for agent ${agent}`,
                trackingEnabled: true,
                features: ['micro-lora', 'ewc++', 'attention-patterns'],
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Trajectory Step Tool
 * Record intermediate steps during task execution
 */
export const intelligenceTrajectoryStepTool = {
    name: 'intelligence_trajectory_step',
    description: 'Record a step in the trajectory for reinforcement learning',
    parameters: z.object({
        trajectoryId: z.number().describe('Trajectory ID from trajectory_start'),
        action: z.string().describe('Action taken (e.g., "edit-file", "run-test")'),
        reward: z.number().min(-1).max(1).describe('Reward signal (-1 to 1)'),
        file: z.string().optional().describe('File involved'),
        errorFixed: z.boolean().optional().describe('Whether an error was fixed'),
        testPassed: z.boolean().optional().describe('Whether tests passed'),
    }),
    execute: async ({ trajectoryId, action, reward, file, errorFixed, testPassed }, { onProgress }) => {
        const startTime = Date.now();
        try {
            await recordTrajectoryStep(trajectoryId, action, reward, {
                file,
                errorFixed,
                testPassed,
            });
            return {
                success: true,
                trajectoryId,
                action,
                reward,
                message: `Step recorded: ${action} with reward ${reward}`,
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Trajectory End Tool
 * Complete trajectory and trigger learning with EWC++
 */
export const intelligenceTrajectoryEndTool = {
    name: 'intelligence_trajectory_end',
    description: 'End trajectory, trigger SONA learning with EWC++ (prevents catastrophic forgetting)',
    parameters: z.object({
        trajectoryId: z.number().describe('Trajectory ID from trajectory_start'),
        success: z.boolean().describe('Whether the task was successful'),
        quality: z.number().min(0).max(1).optional().default(0.8).describe('Quality score (0-1)'),
    }),
    execute: async ({ trajectoryId, success, quality }, { onProgress }) => {
        const startTime = Date.now();
        try {
            const outcome = await endTaskTrajectory(trajectoryId, success, quality);
            return {
                success: true,
                trajectoryId,
                taskSuccess: success,
                quality,
                learningOutcome: outcome,
                features: ['micro-lora-update', 'ewc++-consolidation', 'reasoning-bank-storage'],
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Pattern Store Tool
 * Store successful patterns in ReasoningBank for future retrieval
 */
export const intelligencePatternStoreTool = {
    name: 'intelligence_pattern_store',
    description: 'Store pattern in ReasoningBank (HNSW-indexed, ~0.1ms retrieval)',
    parameters: z.object({
        task: z.string().describe('Task description'),
        resolution: z.string().describe('How the task was resolved'),
        reward: z.number().min(0).max(1).describe('Success score (0-1)'),
        tags: z.array(z.string()).optional().describe('Optional tags for categorization'),
    }),
    execute: async ({ task, resolution, reward, tags }, { onProgress }) => {
        const startTime = Date.now();
        try {
            await storePattern(task, resolution, reward);
            return {
                success: true,
                message: `Pattern stored: "${task.slice(0, 50)}..."`,
                reward,
                indexed: true,
                retrieval: 'hnsw-150x-faster',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Pattern Search Tool
 * Find similar patterns using HNSW (150x faster than brute force)
 */
export const intelligencePatternSearchTool = {
    name: 'intelligence_pattern_search',
    description: 'Search ReasoningBank for similar patterns using HNSW (150x faster)',
    parameters: z.object({
        query: z.string().describe('Query to search for similar patterns'),
        topK: z.number().optional().default(5).describe('Number of results to return'),
        minReward: z.number().min(0).max(1).optional().describe('Minimum reward filter'),
    }),
    execute: async ({ query, topK, minReward }, { onProgress }) => {
        const startTime = Date.now();
        try {
            let patterns = await findSimilarPatterns(query, topK);
            // Filter by minimum reward if specified
            if (minReward !== undefined) {
                patterns = patterns.filter(p => p.reward >= minReward);
            }
            return {
                success: true,
                query: query.slice(0, 50),
                patterns,
                count: patterns.length,
                searchEngine: 'hnsw-150x-faster',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Intelligence Stats Tool
 * Get statistics about the intelligence layer
 */
export const intelligenceStatsTool = {
    name: 'intelligence_stats',
    description: 'Get RuVector intelligence layer statistics: SONA, HNSW, attention metrics',
    parameters: z.object({}),
    execute: async (_, { onProgress }) => {
        const startTime = Date.now();
        try {
            // Initialize intelligence FIRST, then get stats
            const intelligence = await getIntelligence();
            const fullStats = intelligence.getStats();
            const stats = await getIntelligenceStats();
            return {
                success: true,
                stats: {
                    ...stats,
                    ...fullStats,
                },
                features: {
                    sona: {
                        enabled: stats.features?.includes('sona') ?? false,
                        microLora: 'rank-1 (~0.05ms)',
                        baseLora: 'rank-8',
                        ewcLambda: 1000.0,
                    },
                    attention: {
                        type: 'moe',
                        experts: 4,
                        topK: 2,
                    },
                    hnsw: {
                        enabled: stats.features?.includes('hnsw') ?? false,
                        speedup: '150x vs brute-force',
                    },
                },
                persistence: {
                    enabled: true,
                    backend: 'sqlite',
                    trajectories: stats.persistedStats?.trajectories ?? 0,
                    routings: stats.persistedStats?.routings ?? 0,
                    patterns: stats.persistedStats?.patterns ?? 0,
                    operations: stats.persistedStats?.operations ?? 0,
                },
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Force Learning Tool
 * Trigger an immediate learning cycle
 */
export const intelligenceLearnTool = {
    name: 'intelligence_learn',
    description: 'Force immediate SONA learning cycle with EWC++ consolidation',
    parameters: z.object({
        reason: z.string().optional().describe('Reason for forcing learning'),
    }),
    execute: async ({ reason }, { onProgress }) => {
        const startTime = Date.now();
        try {
            const result = await forceLearningCycle();
            return {
                success: true,
                message: 'Learning cycle completed',
                result,
                reason: reason || 'manual trigger',
                features: ['micro-lora-batch', 'ewc++-consolidation', 'pattern-distillation'],
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
/**
 * Attention Compute Tool
 * Compute attention-weighted similarity using MoE/Flash/Hyperbolic
 */
export const intelligenceAttentionTool = {
    name: 'intelligence_attention',
    description: 'Compute attention-weighted similarity using MoE/Flash/Hyperbolic attention',
    parameters: z.object({
        query: z.string().describe('Query text'),
        candidates: z.array(z.string()).describe('Candidate texts to score'),
        attentionType: z.enum(['moe', 'flash', 'hyperbolic', 'graph', 'dual']).optional().default('moe')
            .describe('Attention mechanism type'),
    }),
    execute: async ({ query, candidates, attentionType }, { onProgress }) => {
        const startTime = Date.now();
        try {
            // Simple embedding function
            const embed = (text) => {
                const arr = new Float32Array(64);
                const words = text.toLowerCase().split(/\s+/);
                for (const word of words) {
                    for (let i = 0; i < word.length; i++) {
                        const idx = (word.charCodeAt(i) * (i + 1)) % 64;
                        arr[idx] += 1;
                    }
                }
                // Normalize
                const mag = Math.sqrt(arr.reduce((sum, v) => sum + v * v, 0));
                if (mag > 0) {
                    for (let i = 0; i < arr.length; i++)
                        arr[i] /= mag;
                }
                return arr;
            };
            const queryEmbed = embed(query);
            const candidateEmbeds = candidates.map(c => embed(c));
            const scores = await computeAttentionSimilarity(queryEmbed, candidateEmbeds);
            const results = candidates.map((c, i) => ({
                text: c.slice(0, 50),
                score: scores[i] || 0,
            })).sort((a, b) => b.score - a.score);
            return {
                success: true,
                query: query.slice(0, 50),
                attentionType,
                results,
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : 'Unknown error',
                latencyMs: Date.now() - startTime,
                timestamp: new Date().toISOString(),
            };
        }
    },
};
// Export all intelligence tools
export const intelligenceTools = [
    intelligenceRouteTool,
    intelligenceTrajectoryStartTool,
    intelligenceTrajectoryStepTool,
    intelligenceTrajectoryEndTool,
    intelligencePatternStoreTool,
    intelligencePatternSearchTool,
    intelligenceStatsTool,
    intelligenceLearnTool,
    intelligenceAttentionTool,
];
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