feat(Phase 4): Memory & Intelligence — memory, log, summarization, skills (#91)

Co-authored-by: Jason Woltje <jason@diversecanvas.com>
Co-committed-by: Jason Woltje <jason@diversecanvas.com>

apps/gateway/src/log/summarization.service.ts

@@ -0,0 +1,178 @@
+import { Inject, Injectable, Logger } from '@nestjs/common';
+import type { LogService } from '@mosaic/log';
+import type { Memory } from '@mosaic/memory';
+import { LOG_SERVICE } from './log.tokens.js';
+import { MEMORY } from '../memory/memory.tokens.js';
+import { EmbeddingService } from '../memory/embedding.service.js';
+import type { Db } from '@mosaic/db';
+import { sql, summarizationJobs } from '@mosaic/db';
+import { DB } from '../database/database.module.js';
+
+const SUMMARIZATION_PROMPT = `You are a knowledge extraction assistant. Given the following agent interaction logs, extract the key decisions, learnings, and patterns. Output a concise summary (2-4 sentences) that captures the most important information for future reference. Focus on actionable insights, not raw events.
+
+Logs:
+{logs}
+
+Summary:`;
+
+interface ChatCompletion {
+  choices: Array<{ message: { content: string } }>;
+}
+
+@Injectable()
+export class SummarizationService {
+  private readonly logger = new Logger(SummarizationService.name);
+  private readonly apiKey: string | undefined;
+  private readonly baseUrl: string;
+  private readonly model: string;
+
+  constructor(
+    @Inject(LOG_SERVICE) private readonly logService: LogService,
+    @Inject(MEMORY) private readonly memory: Memory,
+    private readonly embeddings: EmbeddingService,
+    @Inject(DB) private readonly db: Db,
+  ) {
+    this.apiKey = process.env['OPENAI_API_KEY'];
+    this.baseUrl = process.env['SUMMARIZATION_API_URL'] ?? 'https://api.openai.com/v1';
+    this.model = process.env['SUMMARIZATION_MODEL'] ?? 'gpt-4o-mini';
+  }
+
+  /**
+   * Run one summarization cycle:
+   * 1. Find hot logs older than 24h with decision/learning/tool_use categories
+   * 2. Group by session
+   * 3. Summarize each group via cheap LLM
+   * 4. Store as insights with embeddings
+   * 5. Transition processed logs to warm tier
+   */
+  async runSummarization(): Promise<{ logsProcessed: number; insightsCreated: number }> {
+    const cutoff = new Date(Date.now() - 24 * 60 * 60 * 1000); // 24h ago
+
+    // Create job record
+    const [job] = await this.db
+      .insert(summarizationJobs)
+      .values({ status: 'running', startedAt: new Date() })
+      .returning();
+
+    try {
+      const logs = await this.logService.logs.getLogsForSummarization(cutoff, 200);
+      if (logs.length === 0) {
+        await this.db
+          .update(summarizationJobs)
+          .set({ status: 'completed', completedAt: new Date() })
+          .where(sql`id = ${job!.id}`);
+        return { logsProcessed: 0, insightsCreated: 0 };
+      }
+
+      // Group logs by session
+      const bySession = new Map<string, typeof logs>();
+      for (const log of logs) {
+        const group = bySession.get(log.sessionId) ?? [];
+        group.push(log);
+        bySession.set(log.sessionId, group);
+      }
+
+      let insightsCreated = 0;
+
+      for (const [sessionId, sessionLogs] of bySession) {
+        const userId = sessionLogs[0]?.userId;
+        if (!userId) continue;
+
+        const logsText = sessionLogs.map((l) => `[${l.category}] ${l.content}`).join('\n');
+
+        const summary = await this.summarize(logsText);
+        if (!summary) continue;
+
+        const embedding = this.embeddings.available
+          ? await this.embeddings.embed(summary)
+          : undefined;
+
+        await this.memory.insights.create({
+          userId,
+          content: summary,
+          embedding: embedding ?? null,
+          source: 'summarization',
+          category: 'learning',
+          metadata: { sessionId, logCount: sessionLogs.length },
+        });
+        insightsCreated++;
+      }
+
+      // Transition processed logs to warm
+      await this.logService.logs.promoteToWarm(cutoff);
+
+      await this.db
+        .update(summarizationJobs)
+        .set({
+          status: 'completed',
+          logsProcessed: logs.length,
+          insightsCreated,
+          completedAt: new Date(),
+        })
+        .where(sql`id = ${job!.id}`);
+
+      this.logger.log(`Summarization complete: ${logs.length} logs → ${insightsCreated} insights`);
+      return { logsProcessed: logs.length, insightsCreated };
+    } catch (error) {
+      const message = error instanceof Error ? error.message : String(error);
+      await this.db
+        .update(summarizationJobs)
+        .set({ status: 'failed', errorMessage: message, completedAt: new Date() })
+        .where(sql`id = ${job!.id}`);
+      this.logger.error(`Summarization failed: ${message}`);
+      throw error;
+    }
+  }
+
+  /**
+   * Run tier management:
+   * - Warm logs older than 30 days → cold
+   * - Cold logs older than 90 days → purged
+   * - Decay old insight relevance scores
+   */
+  async runTierManagement(): Promise<void> {
+    const warmCutoff = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000);
+    const coldCutoff = new Date(Date.now() - 90 * 24 * 60 * 60 * 1000);
+    const decayCutoff = new Date(Date.now() - 14 * 24 * 60 * 60 * 1000);
+
+    const promoted = await this.logService.logs.promoteToCold(warmCutoff);
+    const purged = await this.logService.logs.purge(coldCutoff);
+    const decayed = await this.memory.insights.decayOldInsights(decayCutoff);
+
+    this.logger.log(
+      `Tier management: ${promoted} logs→cold, ${purged} purged, ${decayed} insights decayed`,
+    );
+  }
+
+  private async summarize(logsText: string): Promise<string | null> {
+    if (!this.apiKey) {
+      this.logger.warn('No API key configured — skipping summarization');
+      return null;
+    }
+
+    const prompt = SUMMARIZATION_PROMPT.replace('{logs}', logsText);
+
+    const response = await fetch(`${this.baseUrl}/chat/completions`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        Authorization: `Bearer ${this.apiKey}`,
+      },
+      body: JSON.stringify({
+        model: this.model,
+        messages: [{ role: 'user', content: prompt }],
+        max_tokens: 300,
+        temperature: 0.3,
+      }),
+    });
+
+    if (!response.ok) {
+      const body = await response.text();
+      this.logger.error(`Summarization API error: ${response.status} ${body}`);
+      return null;
+    }
+
+    const json = (await response.json()) as ChatCompletion;
+    return json.choices[0]?.message.content ?? null;
+  }
+}