create-ai-chat-context-experimental/dist/esm/parsers/ConversationSummaryParser.js

Phase 2: TypeScript rewrite - AI Chat Context & Memory System with conversation extraction and AICF format support (powered by aicf-core v2.1.0).

/**
 * This file is part of create-ai-chat-context-experimental.
 * Licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later).
 * See LICENSE file for details.
 */
import { ExtractionError } from '../types/index.js';
import { Ok, Err } from '../types/index.js';
/**
 * Parse and aggregate conversation messages into comprehensive summary
 * Preserves FULL content - NO TRUNCATION
 */
export class ConversationSummaryParser {
    /**
     * Extract comprehensive conversation summary from ALL messages
     * NO TRUNCATION - preserves full content
     *
     * @param messages - Array of messages to summarize
     * @returns Result with ConversationSummary or error
     */
    extractSummary(messages) {
        try {
            if (!messages || messages.length === 0) {
                return Ok(this.emptyConversationSummary());
            }
            const userMessages = messages.filter((m) => m.role === 'user');
            const aiMessages = messages.filter((m) => m.role === 'assistant');
            // Aggregate user queries with full content
            const userQueries = userMessages.map((m, i) => `[User ${i + 1}] ${m.content}`).join('\n\n');
            // Aggregate AI responses with full content
            const aiResponses = aiMessages.map((m, i) => `[AI ${i + 1}] ${m.content}`).join('\n\n');
            // Create full conversation with timestamps and roles
            const fullConversation = messages
                .map((m, i) => {
                const role = m.role.toUpperCase();
                const timestamp = m.timestamp;
                return `[${i + 1}] ${role} (${timestamp}):\n${m.content}`;
            })
                .join('\n\n---\n\n');
            // Calculate metrics
            const metrics = this.calculateMetrics(messages);
            const summary = {
                userQueries,
                aiResponses,
                fullConversation,
                metrics,
            };
            return Ok(summary);
        }
        catch (error) {
            const message = error instanceof Error ? error.message : 'Unknown error';
            return Err(new ExtractionError(`Failed to extract conversation summary: ${message}`, error));
        }
    }
    /**
     * Calculate metrics about the conversation
     * @param messages - Messages to analyze
     * @returns ConversationMetrics
     */
    calculateMetrics(messages) {
        const totalChars = messages.reduce((sum, m) => sum + m.content.length, 0);
        const avgMessageLength = messages.length > 0 ? Math.round(totalChars / messages.length) : 0;
        return {
            totalMessages: messages.length,
            userMessages: messages.filter((m) => m.role === 'user').length,
            aiMessages: messages.filter((m) => m.role === 'assistant').length,
            totalChars,
            avgMessageLength,
        };
    }
    /**
     * Create empty conversation summary
     * @returns Empty ConversationSummary
     */
    emptyConversationSummary() {
        return {
            userQueries: '',
            aiResponses: '',
            fullConversation: '',
            metrics: {
                totalMessages: 0,
                userMessages: 0,
                aiMessages: 0,
                totalChars: 0,
                avgMessageLength: 0,
            },
        };
    }
}
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