session-mcp/src/tools/memories.ts

// Session memory operations for persistent learnings

import { query, queryOne, execute } from '../db.js';
import { getEmbedding, formatEmbedding } from '../embeddings.js';

type MemoryCategory = 'pattern' | 'fix' | 'preference' | 'gotcha' | 'architecture';

interface Memory {
  id: number;
  category: MemoryCategory;
  title: string;
  content: string;
  context: string | null;
  project: string | null;
  session_id: string | null;
  task_id: string | null;
  access_count: number;
  created_at: string;
}

interface MemoryAddArgs {
  category: MemoryCategory;
  title: string;
  content: string;
  context?: string;
  project?: string;
  session_id?: string;
  task_id?: string;
}

interface MemorySearchArgs {
  query: string;
  project?: string;
  category?: MemoryCategory;
  limit?: number;
}

interface MemoryListArgs {
  project?: string;
  category?: MemoryCategory;
  limit?: number;
}

/**
 * Add a new memory/learning (enhanced with session_id and task_id)
 * CF-306: Validates session_id exists before inserting to prevent foreign key violations
 */
export async function memoryAdd(args: MemoryAddArgs): Promise<string> {
  const { category, title, content, context, project, session_id, task_id } = args;

  // CF-306: Validate session_id exists if provided
  let validSessionId = session_id || null;
  if (session_id) {
    const sessionExists = await queryOne<{ exists: boolean }>(
      `SELECT EXISTS(SELECT 1 FROM sessions WHERE id = $1) as exists`,
      [session_id]
    );
    if (!sessionExists?.exists) {
      console.warn(`[CF-306] Session ${session_id} not found in database - using NULL instead`);
      validSessionId = null;
    }
  }

  // Generate embedding for semantic search
  const embedText = `${title}. ${content}`;
  const embedding = await getEmbedding(embedText);
  const embeddingValue = embedding ? formatEmbedding(embedding) : null;

  if (embeddingValue) {
    await execute(
      `INSERT INTO memories (category, title, content, context, project, session_id, task_id, embedding)
       VALUES ($1, $2, $3, $4, $5, $6, $7, $8)`,
      [category, title, content, context || null, project || null, validSessionId, task_id || null, embeddingValue]
    );
  } else {
    await execute(
      `INSERT INTO memories (category, title, content, context, project, session_id, task_id)
       VALUES ($1, $2, $3, $4, $5, $6, $7)`,
      [category, title, content, context || null, project || null, validSessionId, task_id || null]
    );
  }

  return `Stored memory: [${category}] ${title}`;
}

/**
 * Search memories semantically
 */
export async function memorySearch(args: MemorySearchArgs): Promise<string> {
  const { query: searchQuery, project, category, limit = 5 } = args;

  // Generate embedding for search
  const embedding = await getEmbedding(searchQuery);

  if (!embedding) {
    return 'Error: Could not generate embedding for search';
  }

  const embeddingStr = formatEmbedding(embedding);

  let whereClause = 'WHERE embedding IS NOT NULL';
  const params: unknown[] = [embeddingStr, limit];
  let paramIndex = 3;

  if (project) {
    whereClause += ` AND (project = $${paramIndex++} OR project IS NULL)`;
    params.splice(params.length - 1, 0, project);
  }
  if (category) {
    whereClause += ` AND category = $${paramIndex++}`;
    params.splice(params.length - 1, 0, category);
  }

  const memories = await query<Memory & { similarity: number }>(
    `SELECT id, category, title, content, context, project, access_count,
            to_char(created_at, 'YYYY-MM-DD') as created_at,
            1 - (embedding <=> $1) as similarity
     FROM memories
     ${whereClause}
     ORDER BY embedding <=> $1
     LIMIT $2`,
    params
  );

  if (memories.length === 0) {
    return 'No relevant memories found';
  }

  // Update access_count for returned memories
  const ids = memories.map(m => m.id);
  await execute(
    `UPDATE memories SET access_count = access_count + 1, last_accessed_at = NOW() WHERE id = ANY($1)`,
    [ids]
  );

  const lines = ['Relevant memories:\n'];
  for (const m of memories) {
    const sim = Math.round(m.similarity * 100);
    const proj = m.project ? ` [${m.project}]` : '';
    lines.push(`**[${m.category}]${proj}** ${m.title} (${sim}% match)`);
    lines.push(`  ${m.content}`);
    if (m.context) {
      lines.push(`  _Context: ${m.context}_`);
    }
    lines.push('');
  }

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

/**
 * List memories (non-semantic)
 */
export async function memoryList(args: MemoryListArgs): Promise<string> {
  const { project, category, limit = 20 } = args;

  let whereClause = 'WHERE 1=1';
  const params: unknown[] = [];
  let paramIndex = 1;

  if (project) {
    whereClause += ` AND (project = $${paramIndex++} OR project IS NULL)`;
    params.push(project);
  }
  if (category) {
    whereClause += ` AND category = $${paramIndex++}`;
    params.push(category);
  }

  params.push(limit);

  const memories = await query<Memory>(
    `SELECT id, category, title, content, context, project, access_count,
            to_char(created_at, 'YYYY-MM-DD') as created_at
     FROM memories
     ${whereClause}
     ORDER BY created_at DESC
     LIMIT $${paramIndex}`,
    params
  );

  if (memories.length === 0) {
    return `No memories found${project ? ` for project ${project}` : ''}`;
  }

  const lines = [`Memories${project ? ` (${project})` : ''}:\n`];
  for (const m of memories) {
    const proj = m.project ? `[${m.project}] ` : '';
    const accessed = m.access_count > 0 ? ` (accessed ${m.access_count}x)` : '';
    lines.push(`• [${m.category}] ${proj}${m.title}${accessed}`);
    lines.push(`  ${m.content.slice(0, 100)}${m.content.length > 100 ? '...' : ''}`);
  }

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

/**
 * Delete a memory by ID
 */
export async function memoryDelete(id: number): Promise<string> {
  const result = await execute('DELETE FROM memories WHERE id = $1', [id]);

  if (result === 0) {
    return `Memory not found: ${id}`;
  }

  return `Deleted memory: ${id}`;
}

/**
 * Get memories relevant to current context (for session start)
 */
export async function memoryContext(project: string | null, taskDescription?: string): Promise<string> {
  const lines: string[] = [];

  // Get project-specific memories
  if (project) {
    const projectMemories = await query<Memory>(
      `SELECT category, title, content FROM memories
       WHERE project = $1
       ORDER BY access_count DESC, created_at DESC
       LIMIT 5`,
      [project]
    );

    if (projectMemories.length > 0) {
      lines.push(`**${project} Memories:**`);
      for (const m of projectMemories) {
        lines.push(`• [${m.category}] ${m.title}: ${m.content}`);
      }
      lines.push('');
    }
  }

  // If task description provided, do semantic search
  if (taskDescription) {
    const embedding = await getEmbedding(taskDescription);
    if (embedding) {
      const relevant = await query<Memory>(
        `SELECT category, title, content, project
         FROM memories
         WHERE embedding IS NOT NULL
         ORDER BY embedding <=> $1
         LIMIT 3`,
        [formatEmbedding(embedding)]
      );

      if (relevant.length > 0) {
        lines.push('**Relevant memories for this task:**');
        for (const m of relevant) {
          const proj = m.project ? `[${m.project}] ` : '';
          lines.push(`• ${proj}${m.title}: ${m.content}`);
        }
      }
    }
  }

  // Get recent gotchas (always useful)
  const gotchas = await query<Memory>(
    `SELECT title, content FROM memories
     WHERE category = 'gotcha'
     ORDER BY created_at DESC
     LIMIT 3`,
    []
  );

  if (gotchas.length > 0) {
    lines.push('\n**Recent gotchas:**');
    for (const g of gotchas) {
      lines.push(`⚠️ ${g.title}: ${g.content}`);
    }
  }

  return lines.length > 0 ? lines.join('\n') : 'No memories to surface';
}