algorithm.js

class SimpleGPT {
    constructor() {
        this.knowledgeBase = [];
        this.logicChain = [];
        this.markovChains = {};
        this.letterChains = {};
        this.syntacticChains = {};
        this.sentimentKeywords = ['счастлив', 'грустно', 'зло', 'взволнован', 'скука', 'радость', 'гнев', 'удивление', 'страх'];
        this.wordAssociations = {};
        this.semanticNetwork = {};
        this.questionWords = ['как', 'что', 'почему', 'когда', 'где', 'кто', 'чей', 'сколько', 'зачем', 'какой'];
        this.contextMemory = [];
        this.deepMemory = [];
        this.attentionWeights = {};
        this.hierarchicalChains = {};
        this.transformerLayers = [];
        this.quantumStates = {};
        this.neuroplasticWeights = {};
        this.holographicMemory = {};
        this.fractalPatterns = {};
        this.temporalNets = {};
        this.chaosFields = {};
        this.entropicMatrices = {};
        this.adaptiveFilters = {};
        this.cognitiveMaps = {};
        this.synapticPaths = {};
        this.neuralOscillators = {};
        this.memeticFields = {};
        this.geneticOperators = {};
        this.hyperdimensionalVectors = {};
        this.topologicalManifolds = {};
        this.morphogeneticFields = {};
        this.quantumEntanglement = {};
        this.holographicProjection = {};
        this.fractalEncoding = {};
        this.temporalFolding = {};
        this.chaosSynchronization = {};
        this.entropicBalancing = {};
        this.adaptiveResonance = {};
        this.cognitiveDissonance = {};
        this.synapticPruning = {};
        this.neuralHarmonics = {};
        this.memeticReplication = {};
        this.geneticDrift = {};
        this.hyperdimensionalProjection = {};
        this.topologicalCompression = {};
        this.morphogeneticResonance = {};
        this.conceptCorrelations = {};
        this.narrativeStructures = {};
        this.emotionalGradients = {};
        this.symbolicMaps = {};
        this.linguisticPatterns = {};
        this.causalChains = {};
        this.abstractionLevels = {};
        this.contextualFrames = {};
        this.eigenVectors = {};
        this.stateMachines = {};
        this.bayesianNetworks = {};
        this.fuzzyLogicSets = {};
        this.feedbackLoops = {};
        this.resonanceChambers = {};
        this.informationFlows = {};
        this.phaseSpace = {};
        this.attractorBasins = {};
        this.semanticGradients = {};
        this.conceptualKernels = {};
        this.rhetoricalDevices = {};
        this.stylisticMatrices = {};
        this.dialogueActs = {};
        this.pragmaticContext = {};
        this.buildTransformerLayers();
    }

    loadTrainingData(data) {
        this.knowledgeBase = data.split('\n').filter(line => line.trim() !== '');
        const buildFunctions = [
            this.buildMarkovChains, this.buildLetterChains, this.buildWordAssociations, this.buildSemanticNetwork,
            this.buildSyntacticChains, this.buildHierarchicalChains, this.buildQuantumStates, this.buildNeuroplasticWeights,
            this.buildHolographicMemory, this.buildFractalPatterns, this.buildTemporalNets, this.buildChaosFields,
            this.buildEntropicMatrices, this.buildAdaptiveFilters, this.buildCognitiveMaps, this.buildSynapticPaths,
            this.buildNeuralOscillators, this.buildMemeticFields, this.buildGeneticOperators, this.buildHyperdimensionalVectors,
            this.buildTopologicalManifolds, this.buildMorphogeneticFields, this.buildQuantumEntanglement, this.buildHolographicProjection,
            this.buildFractalEncoding, this.buildTemporalFolding, this.buildChaosSynchronization, this.buildEntropicBalancing,
            this.buildAdaptiveResonance, this.buildCognitiveDissonance, this.buildSynapticPruning, this.buildNeuralHarmonics,
            this.buildMemeticReplication, this.buildGeneticDrift, this.buildHyperdimensionalProjection, this.buildTopologicalCompression,
            this.buildMorphogeneticResonance, this.buildAnswerTemplates, this.buildDeepMemory, this.buildConceptCorrelations,
            this.buildNarrativeStructures, this.buildEmotionalGradients, this.buildSymbolicMaps, this.buildLinguisticPatterns,
            this.buildCausalChains, this.buildAbstractionLevels, this.buildContextualFrames, this.buildEigenVectors,
            this.buildStateMachines, this.buildBayesianNetworks, this.buildFuzzyLogicSets, this.buildFeedbackLoops,
            this.buildResonanceChambers, this.buildInformationFlows, this.buildPhaseSpace, this.buildAttractorBasins,
            this.buildSemanticGradients, this.buildConceptualKernels, this.buildRhetoricalDevices, this.buildStylisticMatrices,
            this.buildDialogueActs, this.buildPragmaticContext
        ];
        buildFunctions.forEach(fn => fn.call(this, this.knowledgeBase));
    }

    buildTransformerLayers() {
        const transformerFunctions = [
            text => this.applyQuantumSuperposition(text), text => this.applyHolographicReduction(text), text => this.applyFractalCompression(text),
            text => this.applyTemporalConvolution(text), text => this.applyChaosEntanglement(text), text => this.applyEntropicFiltering(text),
            text => this.applyAdaptiveResonanceTransform(text), text => this.applyCognitiveMapping(text), text => this.applySynapticWeights(text),
            text => this.applyNeuralHarmonicsTransform(text), text => this.applyMemeticEvolution(text), text => this.applyGeneticOperations(text),
            text => this.applyHyperdimensionalRotation(text), text => this.applyTopologicalFolding(text), text => this.applyMorphogeneticField(text),
            text => this.applyConceptCorrelation(text), text => this.applyNarrativeShift(text), text => this.applyEmotionalGradient(text),
            text => this.applySymbolicSubstitution(text), text => this.applyLinguisticPattern(text), text => this.applyCausalInference(text),
            text => this.applyAbstractionChange(text), text => this.applyContextualFraming(text), text => this.applyEigenVector(text),
            text => this.applyStateMachine(text), text => this.applyBayesianUpdate(text), text => this.applyFuzzyLogic(text),
            text => this.applyFeedback(text), text => this.applyResonance(text), text => this.applyInformationFlow(text),
            text => this.applyPhaseSpaceJump(text), text => this.applyAttractorBasin(text), text => this.applySemanticGradientShift(text),
            text => this.applyConceptualKernel(text), text => this.applyRhetoricalDevice(text), text => this.applyStylisticMatrix(text),
            text => this.applyDialogueAct(text), text => this.applyPragmaticContext(text)
        ];

        this.transformerLayers = [];
        for (let i = 0; i < 7000; i++) {
            const method = transformerFunctions[Math.floor(Math.random() * transformerFunctions.length)];
            this.transformerLayers.push(text => {
                try {
                    const result = method(text);
                    return (typeof result === 'string' && result.trim() !== '') ? result : this.generateFallbackResponse(text);
                } catch (e) {
                    return this.generateFallbackResponse(text);
                }
            });
        }
    }

    applyQuantumSuperposition(text) {
        const words = text.split(' ');
        return words.map(word => {
            const states = this.quantumStates[word] || [word, this.generateWordByLetters(word[0] || 'a')];
            return states[Math.floor(Math.random() * states.length)];
        }).join(' ');
    }

    applyHolographicReduction(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const key = words.slice(0, 2).join(' ');
        const memory = this.holographicMemory[key] || [text];
        return memory[Math.floor(Math.random() * memory.length)];
    }

    applyFractalCompression(text) {
        if (!text) return '';
        const pattern = this.fractalPatterns[text.substring(0, 3)] || text.substring(0, 5);
        if (!pattern) return text;
        return (pattern + text).substring(0, Math.max(text.length, 5));
    }

    applyTemporalConvolution(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const temporalNet = this.temporalNets[words[0]] || {};
        const next = Object.keys(temporalNet);
        if (next.length > 0) {
            return next[Math.floor(Math.random() * next.length)] + ' ' + words.slice(1).join(' ');
        }
        return text;
    }

    applyChaosEntanglement(text) {
        const words = text.split(' ');
        const entangled = words.map(word => {
            const chaos = this.chaosFields[word] || [word];
            return chaos[Math.floor(Math.random() * chaos.length)];
        });
        return entangled.join(' ');
    }

    applyEntropicFiltering(text) {
        const entropyMap = this.calculateEntropy(text);
        return text.split('').filter(char => entropyMap[char] > 0.1).join('');
    }

    calculateEntropy(text) {
        const freq = {};
        if (!text) return {};
        text.split('').forEach(char => {
            freq[char] = (freq[char] || 0) + 1;
        });
        const total = text.length;
        const entropy = {};
        if (total === 0) return {};
        Object.keys(freq).forEach(char => {
            const p = freq[char] / total;
            entropy[char] = -p * Math.log2(p);
        });
        return entropy;
    }

    applyAdaptiveResonanceTransform(text) {
        if (!text) return '';
        const resonance = this.adaptiveResonance[text.substring(0, 5)] || text;
        return resonance.split('').reverse().join('');
    }

    applyCognitiveMapping(text) {
        if (!text) return '';
        const map = this.cognitiveMaps[text.substring(0, 2)] || [text];
        return map[Math.floor(Math.random() * map.length)];
    }

    applySynapticWeights(text) {
        const words = text.split(' ');
        return words.map(word => {
            const weights = this.synapticPaths[word] || { [word]: 1 };
            const choices = Object.keys(weights);
            return choices[Math.floor(Math.random() * choices.length)];
        }).join(' ');
    }

    applyNeuralHarmonicsTransform(text) {
        if (!text) return '';
        const harmonic = this.neuralHarmonics[text.length % 5] || [text];
        return harmonic[Math.floor(Math.random() * harmonic.length)];
    }

    applyMemeticEvolution(text) {
        const memes = this.memeticFields[text] || [text];
        return memes[Math.floor(Math.random() * memes.length)];
    }

    applyGeneticOperations(text) {
        const words = text.split(' ');
        return words.map(word => {
            if (this.geneticOperators[word] && Math.random() < 0.5) {
                return this.geneticOperators[word][Math.floor(Math.random() * this.geneticOperators[word].length)];
            }
            return word;
        }).join(' ');
    }

    applyHyperdimensionalRotation(text) {
        if (!text) return '';
        const dims = this.hyperdimensionalVectors[text.split(' ')[0]] || [text];
        return dims[Math.floor(Math.random() * dims.length)];
    }

    applyTopologicalFolding(text) {
        if (!text) return '';
        const key = text.replace(/\s+/g, '').length % 10;
        const folded = this.topologicalCompression[key] || [text];
        return folded[Math.floor(Math.random() * folded.length)].split('').reverse().join('');
    }

    applyMorphogeneticField(text) {
        if (!text) return '';
        const key = text.substring(text.length - 3);
        const morph = this.morphogeneticFields[key] || [text];
        return morph[Math.floor(Math.random() * morph.length)];
    }

    applyConceptCorrelation(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const concept = words[Math.floor(Math.random() * words.length)];
        const correlated = this.conceptCorrelations[concept] || { [concept]: 1 };
        const choices = Object.keys(correlated);
        const newWord = choices[Math.floor(Math.random() * choices.length)];
        words.splice(Math.floor(Math.random() * words.length), 1, newWord);
        return words.join(' ');
    }

    applyNarrativeShift(text) {
        if (!text) return '';
        const structure = this.narrativeStructures[text.length % 10] || [text];
        return structure[Math.floor(Math.random() * structure.length)];
    }

    applyEmotionalGradient(text) {
        const words = text.split(' ');
        return words.map(word => {
            const gradient = this.emotionalGradients[word];
            if (gradient && Math.random() < 0.3) {
                return gradient;
            }
            return word;
        }).join(' ');
    }

    applySymbolicSubstitution(text) {
        if (!text) return '';
        const key = text[0];
        const symbols = this.symbolicMaps[key] || [text];
        return symbols[Math.floor(Math.random() * symbols.length)];
    }

    applyLinguisticPattern(text) {
        if (!text) return '';
        const patternKey = text.split(' ').length % 5;
        const pattern = this.linguisticPatterns[patternKey] || [text];
        return pattern[Math.floor(Math.random() * pattern.length)];
    }

    applyCausalInference(text) {
        const words = text.split(' ');
        const lastWord = words[words.length - 1];
        const cause = this.causalChains[lastWord] || {};
        const effects = Object.keys(cause);
        if (effects.length > 0) {
            return text + ' потому что ' + effects[Math.floor(Math.random() * effects.length)];
        }
        return text;
    }

    applyAbstractionChange(text) {
        const words = text.split(' ');
        return words.map(word => {
            const level = this.abstractionLevels[word];
            if (level && Math.random() < 0.2) {
                return level[Math.floor(Math.random() * level.length)];
            }
            return word;
        }).join(' ');
    }

    applyContextualFraming(text) {
        if (!text) return '';
        const frame = this.contextualFrames[text.substring(0, 4)] || [text];
        return frame[Math.floor(Math.random() * frame.length)];
    }

    applyEigenVector(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const vector = this.eigenVectors[words[0]] || [text];
        return vector[Math.floor(Math.random() * vector.length)];
    }

    applyStateMachine(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const state = this.stateMachines[words[0]] || { [words.slice(1).join(' ')]: 1 };
        const nextStates = Object.keys(state);
        return words[0] + ' ' + nextStates[Math.floor(Math.random() * nextStates.length)];
    }

    applyBayesianUpdate(text) {
        const words = text.split(' ');
        if (words.length < 2) return text;
        const prior = words[0];
        const evidence = words[1];
        const posterior = this.bayesianNetworks[prior]?.[evidence];
        if (posterior) {
            const choices = Object.keys(posterior);
            words.splice(0, 2, choices[Math.floor(Math.random() * choices.length)]);
            return words.join(' ');
        }
        return text;
    }

    applyFuzzyLogic(text) {
        const words = text.split(' ');
        return words.map(word => {
            const fuzzySet = this.fuzzyLogicSets[word];
            if (fuzzySet && Math.random() < 0.4) {
                return fuzzySet[Math.floor(Math.random() * fuzzySet.length)];
            }
            return word;
        }).join(' ');
    }

    applyFeedback(text) {
        if (!text) return '';
        const loop = this.feedbackLoops[text.length % 10] || [text];
        return loop[Math.floor(Math.random() * loop.length)];
    }

    applyResonance(text) {
        const words = text.split(' ');
        if (words.length === 0) return '';
        const chamber = this.resonanceChambers[words[0]] || [text];
        return chamber[Math.floor(Math.random() * chamber.length)];
    }

    applyInformationFlow(text) {
        const words = text.split(' ');
        if (words.length < 2) return text;
        const from = words[0];
        const flow = this.informationFlows[from];
        if (flow) {
            const to = flow[Math.floor(Math.random() * flow.length)];
            words[1] = to;
            return words.join(' ');
        }
        return text;
    }

    applyPhaseSpaceJump(text) {
        if (!text) return '';
        const key = text.split('').sort().join('').substring(0, 5);
        const newState = this.phaseSpace[key] || [text];
        return newState[Math.floor(Math.random() * newState.length)];
    }

    applyAttractorBasin(text) {
        if (!text) return '';
        const basin = this.attractorBasins[text.substring(0, 2)] || [text];
        return basin[Math.floor(Math.random() * basin.length)];
    }

    applySemanticGradientShift(text) {
        const words = text.split(' ');
        return words.map(word => {
            const gradient = this.semanticGradients[word];
            if (gradient && Math.random() < 0.3) {
                return gradient[Math.floor(Math.random() * gradient.length)];
            }
            return word;
        }).join(' ');
    }

    applyConceptualKernel(text) {
        const words = text.split(' ');
        if (words.length === 0) return text;
        const kernelKey = words[Math.floor(Math.random() * words.length)];
        const kernel = this.conceptualKernels[kernelKey];
        if (kernel) {
            return kernel.replace('%s', text);
        }
        return text;
    }

    applyRhetoricalDevice(text) {
        const devices = Object.keys(this.rhetoricalDevices);
        if (devices.length === 0) return text;
        const device = devices[Math.floor(Math.random() * devices.length)];
        return this.rhetoricalDevices[device](text);
    }

    applyStylisticMatrix(text) {
        const styles = Object.keys(this.stylisticMatrices);
        if (styles.length === 0) return text;
        const style = styles[Math.floor(Math.random() * styles.length)];
        const matrix = this.stylisticMatrices[style];
        return text.split(' ').map(word => matrix[word] || word).join(' ');
    }

    applyDialogueAct(text) {
        const acts = Object.keys(this.dialogueActs);
        if (acts.length === 0) return text;
        const act = acts[Math.floor(Math.random() * acts.length)];
        return this.dialogueActs[act] + ' ' + text;
    }

    applyPragmaticContext(text) {
        const contexts = Object.keys(this.pragmaticContext);
        if (contexts.length === 0) return text;
        const context = contexts[Math.floor(Math.random() * contexts.length)];
        const modification = this.pragmaticContext[context];
        return text + ' ' + modification;
    }


    loadLogicData(data) {
        this.logicChain = data.split('\n').filter(line => line.trim() !== '');
    }

    buildDeepMemory(data) {
        this.deepMemory = data.map(line => {
            const words = line.split(' ').filter(w => w.trim());
            return {
                raw: line,
                tokens: words,
                vector: this.createSemanticVector(words)
            };
        });
    }

    createSemanticVector(words) {
        const vector = {};
        words.forEach(word => {
            const cleanWord = word.toLowerCase().replace(/[^а-яё]/g, '');
            if (!cleanWord) return;

            vector[cleanWord] = (vector[cleanWord] || 0) + 1;

            const similar = this.getSemanticSimilarWords(cleanWord, 3);
            similar.forEach(w => {
                vector[w] = (vector[w] || 0) + 0.7;
            });
        });
        return vector;
    }

    semanticSimilarity(vecA, vecB) {
        const keys = new Set([...Object.keys(vecA), ...Object.keys(vecB)]);
        let dotProduct = 0;
        let magA = 0;
        let magB = 0;

        for (const key of keys) {
            const a = vecA[key] || 0;
            const b = vecB[key] || 0;
            dotProduct += a * b;
            magA += a * a;
            magB += b * b;
        }

        magA = Math.sqrt(magA);
        magB = Math.sqrt(magB);

        return magA && magB ? dotProduct / (magA * magB) : 0;
    }

    findInDeepMemory(query, threshold = 0.65) {
        const queryVector = this.createSemanticVector(query.split(' '));
        const results = [];

        this.deepMemory.forEach(memory => {
            const similarity = this.semanticSimilarity(queryVector, memory.vector);
            if (similarity > threshold) {
                results.push({
                    text: memory.raw,
                    score: similarity
                });
            }
        });

        return results.sort((a, b) => b.score - a.score)
            .slice(0, 7)
            .map(item => item.text);
    }

    buildMarkovChains(data) {
        const maxOrder = 9;
        for (let order = 1; order <= maxOrder; order++) {
            this.markovChains[order] = this.buildMarkovChainForOrder(data, order);
        }
    }

    buildMarkovChainForOrder(data, order) {
        const chain = {};
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            for (let i = 0; i <= words.length - order; i++) {
                const key = words.slice(i, i + order - 1).join(' ');
                const value = words[i + order - 1];
                if (!chain[key]) {
                    chain[key] = [];
                }
                chain[key].push(value);
            }
        });
        return chain;
    }

    buildLetterChains(data) {
        const chain = {};
        data.join(' ').split(/\s+/).forEach(word => {
            for (let i = 0; i < word.length - 1; i++) {
                const key = word[i];
                const next = word[i + 1];
                if (!chain[key]) chain[key] = [];
                chain[key].push(next);
            }
        });
        this.letterChains = chain;
    }

    buildWordAssociations(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim()).map(w => w.toLowerCase().replace(/[^а-яё]/g, ''));
            words.forEach((word, index) => {
                if (!this.wordAssociations[word]) {
                    this.wordAssociations[word] = {};
                }
                for (let j = Math.max(0, index - 7); j < Math.min(words.length, index + 8); j++) {
                    if (index !== j) {
                        const assocWord = words[j];
                        const weight = 1 / (Math.abs(index - j) + 1);
                        this.wordAssociations[word][assocWord] = (this.wordAssociations[word][assocWord] || 0) + weight;
                    }
                }
            });
        });
    }

    buildSemanticNetwork(data) {
        const contextWindow = 15;
        data.forEach(line => {
            const sentences = line.split(/[.!?]+/).filter(s => s.trim());
            sentences.forEach(sentence => {
                const words = sentence.toLowerCase().split(' ').filter(w => w.trim() && w.match(/[а-яё]/g));
                words.forEach((word, i) => {
                    if (!this.semanticNetwork[word]) this.semanticNetwork[word] = {};
                    for (let j = Math.max(0, i - contextWindow); j < Math.min(words.length, i + contextWindow); j++) {
                        if (i !== j) {
                            const contextWord = words[j];
                            const weight = 1 / (Math.abs(i - j) + 1);
                            this.semanticNetwork[word][contextWord] = (this.semanticNetwork[word][contextWord] || 0) + weight;
                        }
                    }
                });
            });
        });
    }

    buildSyntacticChains(data) {
        data.forEach(line => {
            const sentences = line.split(/[.!?]+/).filter(s => s.trim());
            sentences.forEach(sentence => {
                const words = sentence.split(' ').filter(w => w.trim()).map(w => w.toLowerCase().replace(/[^а-яё]/g, ''));
                words.forEach((word, i) => {
                    if (!this.syntacticChains[word]) this.syntacticChains[word] = {};
                    if (i < words.length - 1) {
                        const nextWord = words[i + 1];
                        this.syntacticChains[word][nextWord] = (this.syntacticChains[word][nextWord] || 0) + 1;
                    }
                });
            });
        });
    }

    buildHierarchicalChains(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (!this.hierarchicalChains[word]) this.hierarchicalChains[word] = [];
                if (i < words.length - 2) {
                    this.hierarchicalChains[word].push(words[i + 1] + ' ' + words[i + 2]);
                }
            });
        });
    }

    buildQuantumStates(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (!this.quantumStates[word]) this.quantumStates[word] = [];
                if (i > 0) this.quantumStates[word].push(words[i - 1]);
                if (i < words.length - 1) this.quantumStates[word].push(words[i + 1]);
            });
        });
    }

    buildNeuroplasticWeights(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (!this.neuroplasticWeights[word]) this.neuroplasticWeights[word] = {};
                words.forEach(other => {
                    if (word !== other) {
                        this.neuroplasticWeights[word][other] = (this.neuroplasticWeights[word][other] || 0) + 1;
                    }
                });
            });
        });
    }

    buildHolographicMemory(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length < 2) return;
            const key = words.slice(0, 2).join(' ');
            if (!this.holographicMemory[key]) this.holographicMemory[key] = [];
            this.holographicMemory[key].push(line);
        });
    }

    buildFractalPatterns(data) {
        data.forEach(line => {
            if (line.length > 10) {
                const pattern = line.substring(0, 5);
                this.fractalPatterns[pattern] = line;
            }
        });
    }

    buildTemporalNets(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (!this.temporalNets[word]) this.temporalNets[word] = {};
                if (i < words.length - 1) {
                    const next = words[i + 1];
                    this.temporalNets[word][next] = (this.temporalNets[word][next] || 0) + 1;
                }
            });
        });
    }

    buildChaosFields(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.chaosFields[word]) this.chaosFields[word] = [];
                this.chaosFields[word] = [...new Set([...this.chaosFields[word], ...words])];
            });
        });
    }

    buildEntropicMatrices(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.entropicMatrices[word]) this.entropicMatrices[word] = {};
                words.forEach(other => {
                    if (word !== other) {
                        this.entropicMatrices[word][other] = (this.entropicMatrices[word][other] || 0) + 1;
                    }
                });
            });
        });
    }

    buildAdaptiveFilters(data) {
        data.forEach(line => {
            const key = line.length % 10;
            if (!this.adaptiveFilters[key]) this.adaptiveFilters[key] = [];
            this.adaptiveFilters[key].push(line);
        });
    }

    buildCognitiveMaps(data) {
        data.forEach(line => {
            const key = line.substring(0, 2);
            if (!this.cognitiveMaps[key]) this.cognitiveMaps[key] = [];
            this.cognitiveMaps[key].push(line);
        });
    }

    buildSynapticPaths(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.synapticPaths[word]) this.synapticPaths[word] = {};
                words.forEach(otherWord => {
                    if (word !== otherWord) {
                        this.synapticPaths[word][otherWord] = (this.synapticPaths[word][otherWord] || 0) + 1;
                    }
                });
            });
        });
    }

    buildNeuralOscillators(data) {
        data.forEach(line => {
            const key = line.length % 5;
            if (!this.neuralOscillators[key]) this.neuralOscillators[key] = [];
            this.neuralOscillators[key].push(line);
        });
    }

    buildMemeticFields(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.memeticFields[word]) this.memeticFields[word] = [];
                this.memeticFields[word] = [...new Set([...this.memeticFields[word], ...words.filter(w => w !== word)])];
            });
        });
    }

    buildGeneticOperators(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (!this.geneticOperators[word]) this.geneticOperators[word] = [];
                if (i > 0) this.geneticOperators[word].push(words[i - 1]);
                if (i < words.length - 1) this.geneticOperators[word].push(words[i + 1]);
            });
        });
    }

    buildHyperdimensionalVectors(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length === 0) return;
            const key = words[0];
            if (!this.hyperdimensionalVectors[key]) this.hyperdimensionalVectors[key] = [];
            this.hyperdimensionalVectors[key].push(line);
        });
    }

    buildTopologicalManifolds(data) {
        data.forEach(line => {
            const key = line.split(' ').length;
            if (!this.topologicalManifolds[key]) this.topologicalManifolds[key] = [];
            this.topologicalManifolds[key].push(line);
        });
    }

    buildMorphogeneticFields(data) {
        data.forEach(line => {
            if (line.length < 3) return;
            const key = line.substring(line.length - 3);
            if (!this.morphogeneticFields[key]) this.morphogeneticFields[key] = [];
            this.morphogeneticFields[key].push(line);
        });
    }

    buildQuantumEntanglement(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.quantumEntanglement[word]) this.quantumEntanglement[word] = [];
                words.forEach(other => {
                    if (word !== other && !this.quantumEntanglement[word].includes(other)) {
                        this.quantumEntanglement[word].push(other);
                    }
                });
            });
        });
    }

    buildHolographicProjection(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length === 0) return;
            const key = words[0] + '_' + words.length;
            if (!this.holographicProjection[key]) this.holographicProjection[key] = [];
            this.holographicProjection[key].push(line);
        });
    }

    buildFractalEncoding(data) {
        data.forEach(line => {
            const key = line.replace(/\s+/g, '').substring(0, 4);
            if (!this.fractalEncoding[key]) this.fractalEncoding[key] = [];
            this.fractalEncoding[key].push(line);
        });
    }

    buildTemporalFolding(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.temporalFolding[word]) this.temporalFolding[word] = [];
                this.temporalFolding[word].push(words.join(' '));
            });
        });
    }

    buildChaosSynchronization(data) {
        data.forEach(line => {
            const key = line.split('').filter(c => c.match(/[а-яё]/)).length % 10;
            if (!this.chaosSynchronization[key]) this.chaosSynchronization[key] = [];
            this.chaosSynchronization[key].push(line);
        });
    }

    buildEntropicBalancing(data) {
        data.forEach(line => {
            const key = line.length % 8;
            if (!this.entropicBalancing[key]) this.entropicBalancing[key] = [];
            this.entropicBalancing[key].push(line);
        });
    }

    buildAdaptiveResonance(data) {
        data.forEach(line => {
            if (line.length < 5) return;
            const key = line.substring(0, 5);
            if (!this.adaptiveResonance[key]) this.adaptiveResonance[key] = '';
            this.adaptiveResonance[key] = line;
        });
    }

    buildCognitiveDissonance(data) {
        data.forEach(line => {
            const key = line.split(' ').filter(w => w.length > 3).join('_');
            if (!key) return;
            if (!this.cognitiveDissonance[key]) this.cognitiveDissonance[key] = [];
            this.cognitiveDissonance[key].push(line);
        });
    }

    buildSynapticPruning(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.synapticPruning[word]) this.synapticPruning[word] = [];
                this.synapticPruning[word] = words.filter(w => w !== word);
            });
        });
    }

    buildNeuralHarmonics(data) {
        data.forEach(line => {
            const key = line.length % 5;
            if (!this.neuralHarmonics[key]) this.neuralHarmonics[key] = [];
            this.neuralHarmonics[key].push(line);
        });
    }

    buildMemeticReplication(data) {
        data.forEach(line => {
            const key = line.substring(0, 4);
            if (!this.memeticReplication[key]) this.memeticReplication[key] = [];
            this.memeticReplication[key].push(line);
        });
    }

    buildGeneticDrift(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length === 0) return;
            words.forEach(word => {
                if (!this.geneticDrift[word]) this.geneticDrift[word] = [];
                this.geneticDrift[word].push(words[Math.floor(Math.random() * words.length)]);
            });
        });
    }

    buildHyperdimensionalProjection(data) {
        data.forEach(line => {
            if (!line) return;
            const key = line[0];
            if (!this.hyperdimensionalProjection[key]) this.hyperdimensionalProjection[key] = [];
            this.hyperdimensionalProjection[key].push(line);
        });
    }

    buildTopologicalCompression(data) {
        data.forEach(line => {
            const key = line.replace(/\s+/g, '').length % 10;
            if (!this.topologicalCompression[key]) this.topologicalCompression[key] = [];
            this.topologicalCompression[key].push(line);
        });
    }

    buildMorphogeneticResonance(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length < 1) return;
            const key = words[0] + (words[words.length - 1] || '');
            if (!this.morphogeneticResonance[key]) this.morphogeneticResonance[key] = [];
            this.morphogeneticResonance[key].push(line);
        });
    }

    buildConceptCorrelations(data) {
        data.forEach(line => {
            const words = line.toLowerCase().replace(/[^а-яё\s]/g, '').split(' ').filter(w => w.trim());
            words.forEach((word, index) => {
                if (!this.conceptCorrelations[word]) this.conceptCorrelations[word] = {};
                for (let i = 0; i < words.length; i++) {
                    if (i !== index) {
                        this.conceptCorrelations[word][words[i]] = (this.conceptCorrelations[word][words[i]] || 0) + 1;
                    }
                }
            });
        });
    }

    buildNarrativeStructures(data) {
        data.forEach(line => {
            const key = line.length % 10;
            if (!this.narrativeStructures[key]) this.narrativeStructures[key] = [];
            this.narrativeStructures[key].push(line);
        });
    }

    buildEmotionalGradients(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                this.sentimentKeywords.forEach(sentiment => {
                    if (line.includes(sentiment)) {
                        this.emotionalGradients[word] = sentiment;
                    }
                });
            });
        });
    }

    buildSymbolicMaps(data) {
        data.forEach(line => {
            if (!line) return;
            const key = line[0];
            if (!this.symbolicMaps[key]) this.symbolicMaps[key] = [];
            this.symbolicMaps[key].push(line);
        });
    }

    buildLinguisticPatterns(data) {
        data.forEach(line => {
            const key = line.split(' ').length % 5;
            if (!this.linguisticPatterns[key]) this.linguisticPatterns[key] = [];
            this.linguisticPatterns[key].push(line);
        });
    }

    buildCausalChains(data) {
        data.forEach(line => {
            const parts = line.split('потому что');
            if (parts.length > 1) {
                const cause = parts[1].trim().split(' ')[0].toLowerCase().replace(/[^а-яё]/g, '');
                const effect = parts[0].trim().split(' ').pop().toLowerCase().replace(/[^а-яё]/g, '');
                if (cause && effect) {
                    if (!this.causalChains[effect]) this.causalChains[effect] = {};
                    this.causalChains[effect][cause] = (this.causalChains[effect][cause] || 0) + 1;
                }
            }
        });
    }

    buildAbstractionLevels(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length > 2) {
                const specific = words[0];
                const general = words.slice(1).join(' ');
                if (!this.abstractionLevels[specific]) this.abstractionLevels[specific] = [];
                this.abstractionLevels[specific].push(general);
            }
        });
    }

    buildContextualFrames(data) {
        data.forEach(line => {
            if (line.length < 4) return;
            const key = line.substring(0, 4);
            if (!this.contextualFrames[key]) this.contextualFrames[key] = [];
            this.contextualFrames[key].push(line);
        });
    }

    buildEigenVectors(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length === 0) return;
            const key = words[0];
            if (!this.eigenVectors[key]) this.eigenVectors[key] = [];
            this.eigenVectors[key].push(line);
        });
    }

    buildStateMachines(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length < 2) return;
            const fromState = words[0];
            const toState = words.slice(1).join(' ');
            if (!this.stateMachines[fromState]) this.stateMachines[fromState] = {};
            this.stateMachines[fromState][toState] = (this.stateMachines[fromState][toState] || 0) + 1;
        });
    }

    buildBayesianNetworks(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length < 3) return;
            const cause = words[0];
            const evidence = words[1];
            const effect = words[2];
            if (!this.bayesianNetworks[cause]) this.bayesianNetworks[cause] = {};
            if (!this.bayesianNetworks[cause][evidence]) this.bayesianNetworks[cause][evidence] = {};
            this.bayesianNetworks[cause][evidence][effect] = (this.bayesianNetworks[cause][evidence][effect] || 0) + 1;
        });
    }

    buildFuzzyLogicSets(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            words.forEach(word => {
                if (!this.fuzzyLogicSets[word]) this.fuzzyLogicSets[word] = [];
                this.fuzzyLogicSets[word] = [...new Set([...this.fuzzyLogicSets[word], ...words])];
            });
        });
    }

    buildFeedbackLoops(data) {
        data.forEach(line => {
            const key = line.length % 10;
            if (!this.feedbackLoops[key]) this.feedbackLoops[key] = [];
            this.feedbackLoops[key].push(line);
        });
    }

    buildResonanceChambers(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length === 0) return;
            const key = words[0];
            if (!this.resonanceChambers[key]) this.resonanceChambers[key] = [];
            this.resonanceChambers[key].push(line);
        });
    }

    buildInformationFlows(data) {
        data.forEach(line => {
            const words = line.split(' ').filter(w => w.trim());
            if (words.length < 2) return;
            const from = words[0];
            const to = words[1];
            if (!this.informationFlows[from]) this.informationFlows[from] = [];
            this.informationFlows[from].push(to);
        });
    }

    buildPhaseSpace(data) {
        data.forEach(line => {
            const key = line.split('').sort().join('').substring(0, 5);
            if (!this.phaseSpace[key]) this.phaseSpace[key] = [];
            this.phaseSpace[key].push(line);
        });
    }

    buildAttractorBasins(data) {
        data.forEach(line => {
            const key = line.substring(0, 2);
            if (!this.attractorBasins[key]) this.attractorBasins[key] = [];
            this.attractorBasins[key].push(line);
        });
    }

    buildSemanticGradients(data) {
        data.forEach(line => {
            const words = line.toLowerCase().replace(/[^а-яё\s]/g, '').split(' ').filter(w => w.trim());
            words.forEach((word, i) => {
                if (i < words.length - 1) {
                    const nextWord = words[i + 1];
                    if (!this.semanticGradients[word]) this.semanticGradients[word] = [];
                    this.semanticGradients[word].push(nextWord);
                }
            });
        });
    }

    buildConceptualKernels(data) {
        data.forEach(line => {
            if (line.includes('%s')) {
                const [key, value] = line.split('%s');
                if (key && value) {
                    const kernelKey = key.trim().split(' ').pop();
                    if (kernelKey) {
                        this.conceptualKernels[kernelKey] = line;
                    }
                }
            }
        });
    }

    buildRhetoricalDevices(data) {
        this.rhetoricalDevices = {
            metaphor: (text) => {
                const words = text.split(' ');
                if (words.length < 2) return text;
                const subject = words[0];
                const vehicle = this.getSemanticSimilarWords(words[words.length - 1], 1)[0] || 'мир';
                return `${subject} это ${vehicle}`;
            },
            simile: (text) => {
                const words = text.split(' ');
                if (words.length < 2) return text;
                const subject = words[0];
                const vehicle = this.getSemanticSimilarWords(words[words.length - 1], 1)[0] || 'сон';
                return `${subject} как ${vehicle}`;
            },
            anaphora: (text) => {
                const words = text.split(' ');
                if (words.length < 2) return text;
                const phrase = words.slice(0, 2).join(' ');
                return `${phrase}, ${phrase.toLowerCase()}`;
            }
        };
    }

    buildStylisticMatrices(data) {
        this.stylisticMatrices = {
            formal: { 'привет': 'здравствуйте', 'пока': 'до свидания' },
            poetic: { 'ветер': 'дыхание небес', 'река': 'зеркало времени' }
        };
    }

    buildDialogueActs(data) {
        this.dialogueActs = {
            greeting: 'Привет,',
            question: 'Скажи,',
            statement: 'Я думаю, что',
            farewell: 'До встречи,'
        };
    }

    buildPragmaticContext(data) {
        this.pragmaticContext = {
            formal: 'с уважением',
            informal: 'кстати',
            uncertain: 'возможно'
        };
    }


    buildAnswerTemplates(data) {
        this.answerTemplates = data.filter(line => line.length > 15 && line.length < 100);
    }

    getSemanticSimilarWords(word, count = 10) {
        const cleanWord = word.toLowerCase().replace(/[^а-яё]/g, '');
        if (!this.semanticNetwork[cleanWord]) return [];
        return Object.entries(this.semanticNetwork[cleanWord])
            .sort((a, b) => b[1] - a[1])
            .slice(0, count)
            .map(entry => entry[0]);
    }

    findSimilarWordsByLetters(word, threshold = 0.4) {
        const cleanWord = word.toLowerCase().replace(/[^а-яё]/g, '');
        const words = Object.keys(this.wordAssociations);
        let similar = words.filter(w => {
            const minLen = Math.min(cleanWord.length, w.length);
            let distance = 0;
            for (let i = 0; i < minLen; i++) {
                if (cleanWord[i] !== w[i]) distance++;
            }
            distance += Math.abs(cleanWord.length - w.length);
            return distance / Math.max(cleanWord.length, w.length) <= (1 - threshold);
        });
        if (!similar.length) {
            similar = words.slice(0, 5);
        }
        return similar;
    }

    ensureCoherence(words) {
        if (!words || words.length === 0) return [this.generateWordByLetters('а')];
        return words.filter((word, i) => {
            if (i === 0) return true;
            const prevWord = words[i - 1]?.toLowerCase().replace(/[^а-яё]/g, '');
            const currentWord = word?.toLowerCase().replace(/[^а-яё]/g, '');
            if (!prevWord || !currentWord) return false;
            if (this.syntacticChains[prevWord]?.[currentWord] || this.semanticNetwork[prevWord]?.[currentWord]) {
                return true;
            }
            return Math.random() > 0.6;
        });
    }

    generateWordByLetters(seed = '') {
        let result = seed?.[0] || ['а', 'б', 'в', 'г', 'д', 'е', 'ё'][Math.floor(Math.random() * 7)];
        for (let i = 0; i < 4 + Math.floor(Math.random() * 6); i++) {
            const lastChar = result[result.length - 1];
            const next = this.letterChains[lastChar] || ['а', 'о', 'и', 'е', 'у', 'н', 'т'];
            result += next[Math.floor(Math.random() * next.length)];
        }
        return result;
    }

    generateFallbackResponse(topic = 'что') {
        const randomWords = Object.keys(this.wordAssociations);
        if (randomWords.length === 0) return this.generateWordByLetters('а');
        const fallback = this.generateMarkovResponse(topic || randomWords[Math.floor(Math.random() * randomWords.length)]);
        return fallback || this.generateWordByLetters('а');
    }

    analyzeTopic(input) {
        const words = input.toLowerCase().split(' ').filter(w => w.trim() && w.match(/[а-яё]/));
        let topicScore = {};
        words.forEach(word => {
            const similarWords = this.getSemanticSimilarWords(word, 5);
            similarWords.forEach(w => {
                const associates = this.getSemanticSimilarWords(w, 5);
                associates.forEach(assoc => {
                    topicScore[assoc] = (topicScore[assoc] || 0) + (this.semanticNetwork[w]?.[assoc] || 1);
                });
            });
        });
        const topic = Object.entries(topicScore)
            .sort((a, b) => b[1] - a[1])
            .slice(0, 5)
            .map(entry => entry[0])
            .join(' ');
        return {
            isQuestion: input.endsWith('?') || words.some(w => this.questionWords.includes(w)),
            questionWord: words.find(w => this.questionWords.includes(w)) || null,
            topic: topic || input
        };
    }

    transformPhrase(phrase) {
        const words = phrase.split(' ').filter(w => w.trim());
        const transformedWords = this.ensureCoherence(words.map(word => this.transformWord(word)));
        return transformedWords.join(' ') || this.generateWordByLetters('а');
    }

    transformWord(word) {
        const clean = word.toLowerCase().replace(/[^а-яё]/g, '');
        if (Math.random() < 0.5) {
            const associates = this.getSemanticSimilarWords(clean, 5);
            if (associates.length > 0) {
                return associates[Math.floor(Math.random() * associates.length)];
            }
        }
        if (this.wordAssociations[clean]) {
            const associates = Object.entries(this.wordAssociations[clean]);
            if (associates.length > 0) {
                const weights = associates.map(entry => entry[1]);
                const total = weights.reduce((sum, w) => sum + w, 0);
                if (total > 0) {
                    const rand = Math.random() * total;
                    let sum = 0;
                    for (const [assocWord, weight] of associates) {
                        sum += weight;
                        if (rand <= sum) return assocWord;
                    }
                }
            }
        }
        return clean || this.generateWordByLetters(clean);
    }

    composeNewAnswer(topic) {
        const templates = this.answerTemplates
            .filter(t => t.toLowerCase().includes(topic.toLowerCase().slice(0, 3)))
            .slice(0, 5);
        if (templates.length > 0) {
            const template = templates[Math.floor(Math.random() * templates.length)];
            const words = template.split(' ').filter(w => w.trim());
            const topicWords = topic.split(' ').filter(w => w.trim());
            words.splice(Math.floor(Math.random() * words.length), 0, ...topicWords);
            return this.ensureCoherence(words).join(' ') || this.generateFallbackResponse(topic);
        }
        return this.generateMarkovResponse(topic) || this.generateFallbackResponse(topic);
    }

    reformulateResponse(text, isQuestion = false) {
        let words = text.split(' ').filter(w => w.trim()).map(w => this.transformWord(w));
        words = this.ensureCoherence(words);
        if (isQuestion && Math.random() > 0.7) {
            const addition = this.generateMarkovResponse(words[0] || 'что', 2) || this.generateWordByLetters('а');
            return words.join(' ') + ' ' + addition;
        }
        return words.join(' ') || this.generateWordByLetters('а');
    }

    generateMarkovResponse(input, order = 4) {
        const words = input.split(' ').filter(w => w.trim());
        if (words.length === 0) return this.generateFallbackResponse();
        let response = [];
        const validOrder = Math.min(order, 9);
        let currentKey = words.slice(0, validOrder - 1).join(' ');
        for (let i = 0; i < 50; i++) {
            const chain = this.markovChains[validOrder] || this.syntacticChains;
            const nextWords = chain[currentKey] || this.syntacticChains[currentKey.split(' ').pop()] || [];
            if (!nextWords.length) break;
            const nextWord = this.getNextWordByProbability(nextWords);
            response.push(nextWord);
            const keyParts = currentKey.split(' ');
            keyParts.push(nextWord);
            if (keyParts.length >= validOrder) {
                keyParts.shift();
            }
            currentKey = keyParts.join(' ');
        }
        return this.ensureCoherence(response).join(' ') || this.generateFallbackResponse(input);
    }

    getNextWordByProbability(words) {
        if (!words || words.length === 0) return 'что';
        return words[Math.floor(Math.random() * words.length)];
    }

    processMultipleInputs(inputs) {
        const responses = inputs.map(input => {
            const { isQuestion, topic } = this.analyzeTopic(input);
            let response;
            const deepMemoryResults = this.findInDeepMemory(topic);
            if (deepMemoryResults.length > 0 && Math.random() < 0.7) {
                response = deepMemoryResults[Math.floor(Math.random() * deepMemoryResults.length)];
            } else if (isQuestion) {
                const knowledgeResults = this.findInKnowledgeBase(topic);
                if (knowledgeResults.length > 0) {
                    response = knowledgeResults[Math.floor(Math.random() * knowledgeResults.length)];
                } else {
                    response = this.composeNewAnswer(topic);
                }
            } else {
                const markovResponse = this.generateMarkovResponse(input);
                const similarFromKB = this.findByPartialMatch(input);
                response = similarFromKB.length > 0 && Math.random() < 0.5 ? similarFromKB[0] : markovResponse;
            }
            this.contextMemory.push({ input, response });
            return this.reformulateResponse(response, isQuestion);
        });
        return responses.join('. ') || this.generateFallbackResponse();
    }

    generateResponse(input) {
        const inputs = input.split(/[.,!?;]+/).filter(i => i.trim() !== '');
        if (inputs.length > 1) {
            return this.processMultipleInputs(inputs);
        }

        const { isQuestion, topic } = this.analyzeTopic(input);
        let source;

        const deepMemoryResults = this.findInDeepMemory(topic, 0.7);
        if (deepMemoryResults.length > 0 && Math.random() < 0.8) {
            source = deepMemoryResults[Math.floor(Math.random() * deepMemoryResults.length)];
        } else if (isQuestion) {
            const knowledgeResults = this.findInKnowledgeBase(topic);
            const logicResults = this.findInLogicChain(topic);
            if (knowledgeResults.length > 0 && Math.random() < 0.6) {
                source = knowledgeResults[Math.floor(Math.random() * knowledgeResults.length)];
            } else if (logicResults.length > 0 && Math.random() < 0.4) {
                source = logicResults[Math.floor(Math.random() * logicResults.length)];
            } else {
                source = this.composeNewAnswer(topic);
            }
        } else {
            const knowledgeResults = this.findInKnowledgeBase(input);
            if (knowledgeResults.length > 0 && Math.random() < 0.5) {
                source = knowledgeResults[Math.floor(Math.random() * knowledgeResults.length)];
            } else {
                source = this.generateMarkovResponse(input, 5);
            }
        }

        let processedResponse = source;
        for (const layer of this.transformerLayers) {
            processedResponse = layer(processedResponse);
        }

        this.contextMemory.push({ input, response: processedResponse });
        if (this.contextMemory.length > 10) this.contextMemory.shift();

        return this.reformulateResponse(processedResponse, isQuestion) || this.generateFallbackResponse(topic);
    }

    findByPartialMatch(input) {
        const partialMatches = [];
        const lowerInput = input.toLowerCase();
        this.knowledgeBase.forEach(line => {
            if (line.toLowerCase().startsWith(lowerInput.slice(0, 3))) {
                partialMatches.push(line);
            }
        });
        return partialMatches.slice(0, 5);
    }

    findInKnowledgeBase(query) {
        return this.knowledgeBase.filter(line => line.toLowerCase().includes(query.toLowerCase())).slice(0, 5);
    }

    findInLogicChain(query) {
        return this.logicChain.filter(line => line.toLowerCase().includes(query.toLowerCase())).slice(0, 5);
    }
}

module.exports = SimpleGPT;