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/agent/tools/memory-tools.ts

@@ -0,0 +1,158 @@
+import { Type } from '@sinclair/typebox';
+import type { ToolDefinition } from '@mariozechner/pi-coding-agent';
+import type { Memory } from '@mosaic/memory';
+import type { EmbeddingProvider } from '@mosaic/memory';
+
+export function createMemoryTools(
+  memory: Memory,
+  embeddingProvider: EmbeddingProvider | null,
+): ToolDefinition[] {
+  const searchMemory: ToolDefinition = {
+    name: 'memory_search',
+    label: 'Search Memory',
+    description:
+      'Search across stored insights and knowledge using natural language. Returns semantically similar results.',
+    parameters: Type.Object({
+      userId: Type.String({ description: 'User ID to search memory for' }),
+      query: Type.String({ description: 'Natural language search query' }),
+      limit: Type.Optional(Type.Number({ description: 'Max results (default 5)' })),
+    }),
+    async execute(_toolCallId, params) {
+      const { userId, query, limit } = params as {
+        userId: string;
+        query: string;
+        limit?: number;
+      };
+
+      if (!embeddingProvider) {
+        return {
+          content: [
+            {
+              type: 'text' as const,
+              text: 'Semantic search unavailable — no embedding provider configured',
+            },
+          ],
+          details: undefined,
+        };
+      }
+
+      const embedding = await embeddingProvider.embed(query);
+      const results = await memory.insights.searchByEmbedding(userId, embedding, limit ?? 5);
+      return {
+        content: [{ type: 'text' as const, text: JSON.stringify(results, null, 2) }],
+        details: undefined,
+      };
+    },
+  };
+
+  const getPreferences: ToolDefinition = {
+    name: 'memory_get_preferences',
+    label: 'Get User Preferences',
+    description: 'Retrieve stored preferences for a user.',
+    parameters: Type.Object({
+      userId: Type.String({ description: 'User ID' }),
+      category: Type.Optional(
+        Type.String({
+          description: 'Filter by category: communication, coding, workflow, appearance, general',
+        }),
+      ),
+    }),
+    async execute(_toolCallId, params) {
+      const { userId, category } = params as { userId: string; category?: string };
+      type Cat = 'communication' | 'coding' | 'workflow' | 'appearance' | 'general';
+      const prefs = category
+        ? await memory.preferences.findByUserAndCategory(userId, category as Cat)
+        : await memory.preferences.findByUser(userId);
+      return {
+        content: [{ type: 'text' as const, text: JSON.stringify(prefs, null, 2) }],
+        details: undefined,
+      };
+    },
+  };
+
+  const savePreference: ToolDefinition = {
+    name: 'memory_save_preference',
+    label: 'Save User Preference',
+    description:
+      'Store a learned user preference (e.g., "prefers tables over paragraphs", "timezone: America/Chicago").',
+    parameters: Type.Object({
+      userId: Type.String({ description: 'User ID' }),
+      key: Type.String({ description: 'Preference key' }),
+      value: Type.String({ description: 'Preference value (JSON string)' }),
+      category: Type.Optional(
+        Type.String({
+          description: 'Category: communication, coding, workflow, appearance, general',
+        }),
+      ),
+    }),
+    async execute(_toolCallId, params) {
+      const { userId, key, value, category } = params as {
+        userId: string;
+        key: string;
+        value: string;
+        category?: string;
+      };
+      type Cat = 'communication' | 'coding' | 'workflow' | 'appearance' | 'general';
+      let parsedValue: unknown;
+      try {
+        parsedValue = JSON.parse(value);
+      } catch {
+        parsedValue = value;
+      }
+      const pref = await memory.preferences.upsert({
+        userId,
+        key,
+        value: parsedValue,
+        category: (category as Cat) ?? 'general',
+        source: 'agent',
+      });
+      return {
+        content: [{ type: 'text' as const, text: JSON.stringify(pref, null, 2) }],
+        details: undefined,
+      };
+    },
+  };
+
+  const saveInsight: ToolDefinition = {
+    name: 'memory_save_insight',
+    label: 'Save Insight',
+    description:
+      'Store a learned insight, decision, or knowledge extracted from the current interaction.',
+    parameters: Type.Object({
+      userId: Type.String({ description: 'User ID' }),
+      content: Type.String({ description: 'The insight or knowledge to store' }),
+      category: Type.Optional(
+        Type.String({
+          description: 'Category: decision, learning, preference, fact, pattern, general',
+        }),
+      ),
+    }),
+    async execute(_toolCallId, params) {
+      const { userId, content, category } = params as {
+        userId: string;
+        content: string;
+        category?: string;
+      };
+      type Cat = 'decision' | 'learning' | 'preference' | 'fact' | 'pattern' | 'general';
+
+      let embedding: number[] | null = null;
+      if (embeddingProvider) {
+        embedding = await embeddingProvider.embed(content);
+      }
+
+      const insight = await memory.insights.create({
+        userId,
+        content,
+        embedding,
+        source: 'agent',
+        category: (category as Cat) ?? 'learning',
+      });
+      return {
+        content: [{ type: 'text' as const, text: JSON.stringify(insight, null, 2) }],
+        details: undefined,
+      };
+    },
+  };
+
+  return [searchMemory, getPreferences, savePreference, saveInsight];
+}