wifi-densepose/vendor/sublinear-time-solver/dist/mcp/tools/emergence-tools-backup.js

437 lines
18 KiB
JavaScript

/**
* MCP Tools for Emergence System
* Provides MCP interface to the emergence capabilities
*/
import { EmergenceSystem } from '../../emergence/index.js';
export class EmergenceTools {
emergenceSystem;
constructor(config) {
this.emergenceSystem = new EmergenceSystem(config);
}
getTools() {
return [
{
name: 'emergence_process',
description: 'Process input through the emergence system for novel outputs',
inputSchema: {
type: 'object',
properties: {
input: {
description: 'Input to process through emergence system'
},
tools: {
type: 'array',
items: { type: 'object' },
description: 'Available tools for processing',
default: []
}
},
required: ['input']
}
},
{
name: 'emergence_generate_diverse',
description: 'Generate multiple diverse emergent responses',
inputSchema: {
type: 'object',
properties: {
input: {
description: 'Input for diverse response generation'
},
count: {
type: 'number',
description: 'Number of diverse responses to generate',
default: 3,
minimum: 1,
maximum: 10
},
tools: {
type: 'array',
items: { type: 'object' },
description: 'Available tools',
default: []
}
},
required: ['input']
}
},
{
name: 'emergence_analyze_capabilities',
description: 'Analyze current emergent capabilities of the system',
inputSchema: {
type: 'object',
properties: {
detailed: {
type: 'boolean',
description: 'Include detailed analysis',
default: true
}
}
}
},
{
name: 'emergence_force_evolution',
description: 'Force system evolution toward a specific capability',
inputSchema: {
type: 'object',
properties: {
targetCapability: {
type: 'string',
description: 'Target capability to evolve toward'
}
},
required: ['targetCapability']
}
},
{
name: 'emergence_get_stats',
description: 'Get comprehensive emergence system statistics',
inputSchema: {
type: 'object',
properties: {
component: {
type: 'string',
enum: ['all', 'self_modification', 'learning', 'exploration', 'sharing', 'feedback', 'capabilities'],
description: 'Component to get stats for',
default: 'all'
}
}
}
},
{
name: 'emergence_test_scenarios',
description: 'Run test scenarios to verify emergent capabilities',
inputSchema: {
type: 'object',
properties: {
scenarios: {
type: 'array',
items: { type: 'string' },
description: 'Test scenarios to run',
default: ['self_modification', 'persistent_learning', 'stochastic_exploration', 'cross_tool_sharing']
}
}
}
}
];
}
async handleToolCall(name, args) {
try {
switch (name) {
case 'emergence_process':
return await this.emergenceSystem.processWithEmergence(args.input, args.tools || []);
case 'emergence_generate_diverse':
return await this.emergenceSystem.generateEmergentResponses(args.input, args.count || 3, args.tools || []);
case 'emergence_analyze_capabilities':
return await this.emergenceSystem.analyzeEmergentCapabilities();
case 'emergence_force_evolution':
return await this.emergenceSystem.forceEvolution(args.targetCapability);
case 'emergence_get_stats':
const stats = this.emergenceSystem.getEmergenceStats();
if (args.component && args.component !== 'all') {
return { component: args.component, stats: stats.components[args.component] };
}
return stats;
case 'emergence_test_scenarios':
return await this.runTestScenarios(args.scenarios);
default:
throw new Error(`Unknown emergence tool: ${name}`);
}
}
catch (error) {
return {
success: false,
error: error instanceof Error ? error.message : 'Unknown error',
tool: name,
args
};
}
}
/**
* Run test scenarios to verify emergence capabilities
*/
async runTestScenarios(scenarios) {
const results = {
timestamp: Date.now(),
scenarios: scenarios.length,
results: []
};
for (const scenario of scenarios) {
const testResult = await this.runSingleTestScenario(scenario);
results.results.push(testResult);
}
const overallSuccess = results.results.every(r => r.success);
const averageScore = results.results.reduce((sum, r) => sum + (r.score || 0), 0) / results.results.length;
return {
...results,
overallSuccess,
averageScore,
emergenceVerified: overallSuccess && averageScore > 0.7
};
}
/**
* Run a single test scenario
*/
async runSingleTestScenario(scenario) {
const testInput = this.generateTestInput(scenario);
const startTime = Date.now();
try {
switch (scenario) {
case 'self_modification':
return await this.testSelfModification(testInput);
case 'persistent_learning':
return await this.testPersistentLearning(testInput);
case 'stochastic_exploration':
return await this.testStochasticExploration(testInput);
case 'cross_tool_sharing':
return await this.testCrossToolSharing(testInput);
case 'feedback_loops':
return await this.testFeedbackLoops(testInput);
case 'emergent_capabilities':
return await this.testEmergentCapabilities(testInput);
default:
return {
scenario,
success: false,
error: `Unknown test scenario: ${scenario}`,
duration: Date.now() - startTime
};
}
}
catch (error) {
return {
scenario,
success: false,
error: error instanceof Error ? error.message : 'Test failed',
duration: Date.now() - startTime
};
}
}
/**
* Test self-modification capabilities
*/
async testSelfModification(testInput) {
const startTime = Date.now();
// Process input that should trigger self-modification
const result = await this.emergenceSystem.processWithEmergence(testInput.selfModificationTrigger);
const modifications = result.emergenceSession.results.modifications || [];
const hasModifications = modifications.length > 0;
return {
scenario: 'self_modification',
success: hasModifications,
score: hasModifications ? 0.8 : 0.2,
evidence: {
modificationsApplied: modifications.length,
modificationTypes: modifications.map(m => m.modification),
sessionId: result.emergenceSession.sessionId
},
duration: Date.now() - startTime
};
}
/**
* Test persistent learning capabilities
*/
async testPersistentLearning(testInput) {
const startTime = Date.now();
// Process multiple related inputs to test learning
const learningSequence = testInput.learningSequence;
const results = [];
for (const input of learningSequence) {
const result = await this.emergenceSystem.processWithEmergence(input);
results.push(result);
}
// Check if later results show learning from earlier ones
const learningEvidence = results.some(r => r.emergenceSession.results.learning &&
r.emergenceSession.results.learning.success);
const stats = this.emergenceSystem.getEmergenceStats();
const hasLearningTriples = stats.components.learning.totalTriples > 0;
return {
scenario: 'persistent_learning',
success: learningEvidence && hasLearningTriples,
score: learningEvidence ? 0.9 : 0.3,
evidence: {
learningTriples: stats.components.learning.totalTriples,
sessionsProcessed: results.length,
learningDetected: learningEvidence
},
duration: Date.now() - startTime
};
}
/**
* Test stochastic exploration capabilities
*/
async testStochasticExploration(testInput) {
const startTime = Date.now();
// Generate multiple responses to same input to test variability
const responses = await this.emergenceSystem.generateEmergentResponses(testInput.explorationTrigger, 5);
// Check for diversity in responses
const diversityScore = this.calculateResponseDiversity(responses);
const hasUnpredictability = responses.some(r => r.novelty > 0.5);
return {
scenario: 'stochastic_exploration',
success: diversityScore > 0.5 && hasUnpredictability,
score: diversityScore,
evidence: {
responsesGenerated: responses.length,
diversityScore,
averageNovelty: responses.reduce((sum, r) => sum + r.novelty, 0) / responses.length,
maxNovelty: Math.max(...responses.map(r => r.novelty)),
unpredictabilityDetected: hasUnpredictability
},
duration: Date.now() - startTime
};
}
/**
* Test cross-tool sharing capabilities
*/
async testCrossToolSharing(testInput) {
const startTime = Date.now();
// Process input with multiple tools to test sharing
const mockTools = [
{ name: 'tool1', process: (input) => ({ tool1_result: input }) },
{ name: 'tool2', process: (input) => ({ tool2_result: input }) },
{ name: 'tool3', process: (input) => ({ tool3_result: input }) }
];
const result = await this.emergenceSystem.processWithEmergence(testInput.sharingTrigger, mockTools);
const sharedInfo = result.emergenceSession.results.sharedInformation || [];
const hasSharing = sharedInfo.length > 0;
const stats = this.emergenceSystem.getEmergenceStats();
const sharingStats = stats.components.sharing;
return {
scenario: 'cross_tool_sharing',
success: hasSharing && sharingStats.totalFlows > 0,
score: hasSharing ? 0.8 : 0.2,
evidence: {
sharedInformationCount: sharedInfo.length,
totalFlows: sharingStats.totalFlows,
activeConnections: sharingStats.totalConnections,
sharingDetected: hasSharing
},
duration: Date.now() - startTime
};
}
/**
* Test feedback loop capabilities
*/
async testFeedbackLoops(testInput) {
const startTime = Date.now();
// Process inputs that should trigger feedback and adaptation
const result1 = await this.emergenceSystem.processWithEmergence(testInput.feedbackTrigger);
const result2 = await this.emergenceSystem.processWithEmergence(testInput.feedbackTrigger);
const behaviorMods1 = result1.emergenceSession.results.behaviorModifications || [];
const behaviorMods2 = result2.emergenceSession.results.behaviorModifications || [];
const hasFeedback = behaviorMods1.length > 0 || behaviorMods2.length > 0;
const showsAdaptation = behaviorMods2.length !== behaviorMods1.length; // Different behavior
return {
scenario: 'feedback_loops',
success: hasFeedback,
score: hasFeedback ? (showsAdaptation ? 0.9 : 0.6) : 0.2,
evidence: {
firstSessionMods: behaviorMods1.length,
secondSessionMods: behaviorMods2.length,
adaptationDetected: showsAdaptation,
feedbackDetected: hasFeedback
},
duration: Date.now() - startTime
};
}
/**
* Test emergent capability detection
*/
async testEmergentCapabilities(testInput) {
const startTime = Date.now();
// Process novel input to trigger capability detection
const result = await this.emergenceSystem.processWithEmergence(testInput.novelTrigger);
const emergentCapabilities = result.emergenceSession.results.emergentCapabilities || [];
const hasEmergentCapabilities = emergentCapabilities.length > 0;
const capabilityAnalysis = await this.emergenceSystem.analyzeEmergentCapabilities();
return {
scenario: 'emergent_capabilities',
success: hasEmergentCapabilities,
score: hasEmergentCapabilities ? 0.9 : 0.3,
evidence: {
capabilitiesDetected: emergentCapabilities.length,
capabilityTypes: emergentCapabilities.map(c => c.type),
overallEmergenceLevel: capabilityAnalysis.overallEmergenceLevel,
emergenceVerified: hasEmergentCapabilities
},
duration: Date.now() - startTime
};
}
/**
* Generate test input for scenarios
*/
generateTestInput(scenario) {
const baseInputs = {
selfModificationTrigger: {
type: 'complex_problem',
description: 'Multi-step reasoning problem requiring adaptive approach',
complexity: 0.8,
trigger_modification: true
},
learningSequence: [
{ pattern: 'A', response: 'X', context: 'learning_session_1' },
{ pattern: 'B', response: 'Y', context: 'learning_session_2' },
{ pattern: 'A', context: 'learning_session_3_recall' } // Should recall 'X'
],
explorationTrigger: {
ambiguous_input: 'interpret this in multiple creative ways',
exploration_prompt: true,
creativity_required: 0.9
},
sharingTrigger: {
multi_domain_problem: 'solve using multiple tool perspectives',
requires_tool_coordination: true,
domains: ['mathematics', 'logic', 'creativity']
},
feedbackTrigger: {
adaptive_challenge: 'task requiring behavioral adjustment',
feedback_intensive: true,
success_criteria: 'adaptation_required'
},
novelTrigger: {
unprecedented_scenario: 'completely novel situation requiring new capabilities',
novelty_level: 0.95,
capability_emergence_expected: true
}
};
return baseInputs;
}
/**
* Calculate diversity in responses
*/
calculateResponseDiversity(responses) {
if (responses.length < 2)
return 0;
// Simple diversity measure based on response differences
let totalDiversity = 0;
let comparisons = 0;
for (let i = 0; i < responses.length; i++) {
for (let j = i + 1; j < responses.length; j++) {
const similarity = this.calculateResponseSimilarity(responses[i], responses[j]);
totalDiversity += (1 - similarity);
comparisons++;
}
}
return comparisons > 0 ? totalDiversity / comparisons : 0;
}
/**
* Calculate similarity between two responses
*/
calculateResponseSimilarity(response1, response2) {
// Simple similarity calculation
const str1 = JSON.stringify(response1.response);
const str2 = JSON.stringify(response2.response);
if (str1 === str2)
return 1.0;
// Character-level similarity
const maxLength = Math.max(str1.length, str2.length);
let matches = 0;
for (let i = 0; i < Math.min(str1.length, str2.length); i++) {
if (str1[i] === str2[i])
matches++;
}
return matches / maxLength;
}
}