Agentic-Compaction-and-Pipleline-by-GLM-5/agent-system/core/summarizer.ts

/**
 * Conversation Summarizer Module
 * 
 * Uses LLM to create intelligent summaries of conversations,
 * preserving key information while reducing token count.
 */

import ZAI from 'z-ai-web-dev-sdk';
import { TokenCounter, countTokens } from './token-counter';

export interface SummaryResult {
  summary: string;
  originalTokens: number;
  summaryTokens: number;
  compressionRatio: number;
  keyPoints: string[];
  decisions: string[];
  actionItems: string[];
}

export interface SummarizerOptions {
  maxSummaryTokens?: number;
  preserveRecentMessages?: number;
  extractKeyPoints?: boolean;
  extractDecisions?: boolean;
  extractActionItems?: boolean;
}

export interface ConversationTurn {
  role: 'user' | 'assistant' | 'system';
  content: string;
  timestamp?: Date;
  metadata?: Record<string, unknown>;
}

const DEFAULT_OPTIONS: Required<SummarizerOptions> = {
  maxSummaryTokens: 1000,
  preserveRecentMessages: 3,
  extractKeyPoints: true,
  extractDecisions: true,
  extractActionItems: true
};

/**
 * ConversationSummarizer - Creates intelligent summaries of conversations
 */
export class ConversationSummarizer {
  private zai: Awaited<ReturnType<typeof ZAI.create>> | null = null;
  private tokenCounter: TokenCounter;
  private options: Required<SummarizerOptions>;

  constructor(options: SummarizerOptions = {}) {
    this.options = { ...DEFAULT_OPTIONS, ...options };
    this.tokenCounter = new TokenCounter();
  }

  /**
   * Initialize the summarizer (lazy load ZAI)
   */
  private async init(): Promise<void> {
    if (!this.zai) {
      this.zai = await ZAI.create();
    }
  }

  /**
   * Summarize a conversation
   */
  async summarize(
    messages: ConversationTurn[],
    options?: Partial<SummarizerOptions>
  ): Promise<SummaryResult> {
    await this.init();
    
    const opts = { ...this.options, ...options };
    const originalTokens = this.tokenCounter.countConversation(messages).total;

    // Format conversation for summarization
    const conversationText = this.formatConversationForSummary(messages);

    // Create the summarization prompt
    const prompt = this.buildSummarizationPrompt(conversationText, opts);

    // Get summary from LLM
    const response = await this.zai!.chat.completions.create({
      messages: [
        {
          role: 'assistant',
          content: `You are a precise conversation summarizer. Your task is to create concise summaries that preserve all important information while minimizing tokens.`
        },
        {
          role: 'user',
          content: prompt
        }
      ],
      thinking: { type: 'disabled' }
    });

    const summaryText = response.choices?.[0]?.message?.content || '';
    
    // Parse the structured response
    const parsed = this.parseSummaryResponse(summaryText);
    
    const summaryTokens = countTokens(parsed.summary);
    
    return {
      summary: parsed.summary,
      originalTokens,
      summaryTokens,
      compressionRatio: originalTokens > 0 ? summaryTokens / originalTokens : 0,
      keyPoints: parsed.keyPoints,
      decisions: parsed.decisions,
      actionItems: parsed.actionItems
    };
  }

  /**
   * Format conversation for summarization
   */
  private formatConversationForSummary(messages: ConversationTurn[]): string {
    return messages.map(msg => {
      const timestamp = msg.timestamp?.toISOString() || '';
      return `[${msg.role.toUpperCase()}]${timestamp ? ` (${timestamp})` : ''}: ${msg.content}`;
    }).join('\n\n');
  }

  /**
   * Build the summarization prompt
   */
  private buildSummarizationPrompt(
    conversationText: string,
    options: Required<SummarizerOptions>
  ): string {
    const sections: string[] = [];

    sections.push(`Please summarize the following conversation concisely.`);
    sections.push(`The summary should be under ${options.maxSummaryTokens} tokens.`);

    if (options.extractKeyPoints) {
      sections.push(`\nExtract KEY POINTS as a bullet list.`);
    }
    if (options.extractDecisions) {
      sections.push(`Extract any DECISIONS made as a bullet list.`);
    }
    if (options.extractActionItems) {
      sections.push(`Extract any ACTION ITEMS as a bullet list.`);
    }

    sections.push(`\nFormat your response as:
## SUMMARY
[Your concise summary here]

## KEY POINTS
- [Key point 1]
- [Key point 2]

## DECISIONS
- [Decision 1]
- [Decision 2]

## ACTION ITEMS
- [Action item 1]
- [Action item 2]

---

CONVERSATION:
${conversationText}`);

    return sections.join('\n');
  }

  /**
   * Parse the structured summary response
   */
  private parseSummaryResponse(text: string): {
    summary: string;
    keyPoints: string[];
    decisions: string[];
    actionItems: string[];
  } {
    const sections = {
      summary: '',
      keyPoints: [] as string[],
      decisions: [] as string[],
      actionItems: [] as string[]
    };

    // Extract summary
    const summaryMatch = text.match(/## SUMMARY\s*([\s\S]*?)(?=##|$)/i);
    if (summaryMatch) {
      sections.summary = summaryMatch[1].trim();
    }

    // Extract key points
    const keyPointsMatch = text.match(/## KEY POINTS\s*([\s\S]*?)(?=##|$)/i);
    if (keyPointsMatch) {
      sections.keyPoints = this.extractBulletPoints(keyPointsMatch[1]);
    }

    // Extract decisions
    const decisionsMatch = text.match(/## DECISIONS\s*([\s\S]*?)(?=##|$)/i);
    if (decisionsMatch) {
      sections.decisions = this.extractBulletPoints(decisionsMatch[1]);
    }

    // Extract action items
    const actionItemsMatch = text.match(/## ACTION ITEMS\s*([\s\S]*?)(?=##|$)/i);
    if (actionItemsMatch) {
      sections.actionItems = this.extractBulletPoints(actionItemsMatch[1]);
    }

    return sections;
  }

  /**
   * Extract bullet points from text
   */
  private extractBulletPoints(text: string): string[] {
    const lines = text.split('\n');
    return lines
      .map(line => line.replace(/^[-*•]\s*/, '').trim())
      .filter(line => line.length > 0);
  }

  /**
   * Create a rolling summary (for continuous conversations)
   */
  async createRollingSummary(
    previousSummary: string,
    newMessages: ConversationTurn[]
  ): Promise<SummaryResult> {
    await this.init();

    const prompt = `You are updating a conversation summary with new messages.

PREVIOUS SUMMARY:
${previousSummary}

NEW MESSAGES:
${this.formatConversationForSummary(newMessages)}

Create an updated summary that integrates the new information with the previous summary.
Keep the summary concise but comprehensive.
Format your response as:
## SUMMARY
[Your updated summary]

## KEY POINTS
- [Updated key points]

## DECISIONS
- [Updated decisions]

## ACTION ITEMS
- [Updated action items]`;

    const response = await this.zai!.chat.completions.create({
      messages: [
        {
          role: 'assistant',
          content: 'You are a conversation summarizer that maintains rolling summaries.'
        },
        {
          role: 'user',
          content: prompt
        }
      ],
      thinking: { type: 'disabled' }
    });

    const summaryText = response.choices?.[0]?.message?.content || '';
    const parsed = this.parseSummaryResponse(summaryText);
    
    return {
      summary: parsed.summary,
      originalTokens: countTokens(previousSummary) + this.tokenCounter.countConversation(newMessages).total,
      summaryTokens: countTokens(parsed.summary),
      compressionRatio: 0,
      keyPoints: parsed.keyPoints,
      decisions: parsed.decisions,
      actionItems: parsed.actionItems
    };
  }

  /**
   * Create a topic-based summary (groups messages by topic)
   */
  async createTopicSummary(
    messages: ConversationTurn[]
  ): Promise<Map<string, SummaryResult>> {
    await this.init();

    // First, identify topics
    const topicResponse = await this.zai!.chat.completions.create({
      messages: [
        {
          role: 'assistant',
          content: 'Identify the main topics in this conversation. Respond with a JSON array of topic names.'
        },
        {
          role: 'user',
          content: this.formatConversationForSummary(messages)
        }
      ],
      thinking: { type: 'disabled' }
    });

    let topics: string[] = [];
    try {
      const topicText = topicResponse.choices?.[0]?.message?.content || '[]';
      topics = JSON.parse(topicText.match(/\[.*\]/s)?.[0] || '[]');
    } catch {
      topics = ['General'];
    }

    // Create summaries for each topic
    const summaries = new Map<string, SummaryResult>();
    
    for (const topic of topics) {
      const summary = await this.summarize(messages, {
        maxSummaryTokens: 500
      });
      summaries.set(topic, summary);
    }

    return summaries;
  }
}

// Singleton instance
export const defaultSummarizer = new ConversationSummarizer();