MCP Reasoner

export class ToTEngine { constructor() { this.beamWidth = 5; this.maxDepth = 3; } async evaluateThought(thought) { // Simple scoring based on thought coherence and relevance const score = Math.random(); // Replace with actual evaluation logic return score; } async generateThoughts(context, numThoughts = 3) { const thoughts = []; const scores = []; for (let i = 0; i < numThoughts; i++) { // In a real implementation, this would use an LLM to generate thoughts const thought = `Thought ${i + 1} about ${context}`; const score = await this.evaluateThought(thought); thoughts.push(thought); scores.push(score); } return { thoughts, scores }; } async expandPath(path) { const { thoughts, scores } = await this.generateThoughts(path[path.length - 1]); return thoughts.map((thought, i) => ({ path: [...path, thought], score: scores[i] })); } async search(initialContext) { let paths = [{ path: [initialContext], score: 1.0 }]; for (let depth = 0; depth < this.maxDepth; depth++) { const newPaths = []; for (const currentPath of paths) { const expansions = await this.expandPath(currentPath.path); newPaths.push(...expansions); } // Keep top k paths based on scores paths = newPaths .sort((a, b) => b.score - a.score) .slice(0, this.beamWidth); } return paths; } }