feat: add serverless memory API functions and memory system package

api/_migrations/001_create_memory_embeddings.sql

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+-- Migration: Create memory_embeddings table for long-term memory storage
+-- This table stores vector embeddings for semantic search of user memories
+
+-- Enable pgvector extension (required for vector similarity search)
+CREATE EXTENSION IF NOT EXISTS vector;
+
+-- Create memory_embeddings table
+CREATE TABLE IF NOT EXISTS memory_embeddings (
+    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
+    user_id TEXT NOT NULL,
+    content TEXT NOT NULL,
+    embedding vector(768),  -- Adjust dimension based on your embedding model
+    metadata JSONB,
+    created_at TIMESTAMPTZ DEFAULT NOW(),
+
+    -- Indexes for performance
+    INDEX idx_memory_user_id (user_id),
+    INDEX idx_memory_created_at (created_at DESC)
+);
+
+-- Create index for vector similarity search (HNSW for better performance)
+CREATE INDEX IF NOT EXISTS idx_memory_embedding_hnsw 
+ON memory_embeddings 
+USING hnsw (embedding vector_cosine_ops);
+
+-- Alternative: IVFFlat index (faster build, slightly slower search)
+-- CREATE INDEX IF NOT EXISTS idx_memory_embedding_ivfflat 
+-- ON memory_embeddings 
+-- USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
+
+-- Grant permissions (adjust based on your database user)
+-- GRANT SELECT, INSERT, UPDATE, DELETE ON memory_embeddings TO your_db_user;
+
+COMMENT ON TABLE memory_embeddings IS 'Stores user memories as vector embeddings for semantic search';
+COMMENT ON COLUMN memory_embeddings.embedding IS 'Vector embedding dimension should match your model (768 for bge-base-en-v1.5, 1536 for text-embedding-3-small, etc.)';

api/_migrations/README.md

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+# Database Migrations
+
+## Setup Instructions
+
+### 1. Connect to your Postgres database
+
+```bash
+psql $POSTGRES_URL
+```
+
+Or use your database provider's console (Neon, Supabase, Vercel Postgres, etc.)
+
+### 2. Run the migration
+
+```sql
+\i 001_create_memory_embeddings.sql
+```
+
+Or copy-paste the SQL content from the file.
+
+### 3. Verify the table was created
+
+```sql
+\d memory_embeddings
+```
+
+You should see the table structure with the `embedding` column of type `vector`.
+
+## Important Notes
+
+### Embedding Dimension
+
+The `embedding vector(768)` dimension must match your embedding model:
+
+- **Cloudflare `@cf/baai/bge-base-en-v1.5`**: 768 dimensions
+- **OpenAI `text-embedding-3-small`**: 1536 dimensions
+- **OpenAI `text-embedding-3-large`**: 3072 dimensions
+- **OpenAI `text-embedding-ada-002`**: 1536 dimensions
+
+To change the dimension, alter the table:
+
+```sql
+-- Example: Change to 1536 for OpenAI embeddings
+ALTER TABLE memory_embeddings
+ALTER COLUMN embedding TYPE vector(1536);
+
+-- Recreate the index
+DROP INDEX IF EXISTS idx_memory_embedding_hnsw;
+CREATE INDEX idx_memory_embedding_hnsw
+ON memory_embeddings
+USING hnsw (embedding vector_cosine_ops);
+```
+
+### Environment Variables
+
+Ensure these are set in your Vercel project:
+
+```env
+# Database connection
+POSTGRES_URL=postgresql://user:pass@host:5432/dbname
+
+# Long-term memory settings
+LONG_TERM_MEMORY_ENABLED=true
+LONG_TERM_MEMORY_PROVIDER=postgres-pgvector
+
+# Embedding provider (choose one)
+MEMORY_EMBEDDING_PROVIDER=cloudflare
+CLOUDFLARE_ACCOUNT_ID=your_account_id
+CLOUDFLARE_API_TOKEN=your_api_token
+MEMORY_EMBEDDING_MODEL=@cf/baai/bge-base-en-v1.5
+
+# Or use OpenAI
+# MEMORY_EMBEDDING_PROVIDER=openai
+# MEMORY_EMBEDDING_API_KEY=sk-...
+# MEMORY_EMBEDDING_MODEL=text-embedding-3-small
+```
+
+## Manual Table Creation (Alternative)
+
+If you prefer to create the table manually without pgvector extension:
+
+```sql
+CREATE TABLE memory_embeddings (
+    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
+    user_id TEXT NOT NULL,
+    content TEXT NOT NULL,
+    embedding TEXT,  -- Store as JSON array string
+    metadata JSONB,
+    created_at TIMESTAMPTZ DEFAULT NOW()
+);
+
+CREATE INDEX idx_memory_user_id ON memory_embeddings(user_id);
+CREATE INDEX idx_memory_created_at ON memory_embeddings(created_at DESC);
+```
+
+Note: This won't support efficient vector similarity search.

api/memory/clear.ts

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+import type { VercelRequest, VercelResponse } from '@vercel/node'
+
+import { clearSession } from '../_lib/memory'
+
+export default async function handler(req: VercelRequest, res: VercelResponse) {
+  // Set CORS headers
+  res.setHeader('Access-Control-Allow-Origin', '*')
+  res.setHeader('Access-Control-Allow-Methods', 'POST, OPTIONS')
+  res.setHeader('Access-Control-Allow-Headers', 'Content-Type')
+
+  if (req.method === 'OPTIONS') {
+    return res.status(200).end()
+  }
+
+  if (req.method !== 'POST') {
+    return res.status(405).json({ success: false, error: 'Method not allowed' })
+  }
+
+  try {
+    const body = req.body as { sessionId?: string }
+
+    if (!body?.sessionId || typeof body.sessionId !== 'string') {
+      return res.status(400).json({ success: false, error: 'sessionId is required' })
+    }
+
+    await clearSession(body.sessionId)
+
+    return res.status(200).json({ success: true })
+  }
+  catch (error) {
+    console.error('Error in /api/memory/clear:', error)
+    return res.status(500).json({
+      success: false,
+      error: error instanceof Error ? error.message : String(error),
+    })
+  }
+}

api/memory/config.ts

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+import type { VercelRequest, VercelResponse } from '@vercel/node'
+
+import { getConfiguration, setConfiguration } from '../_lib/memory'
+
+export default async function handler(req: VercelRequest, res: VercelResponse) {
+  // Set CORS headers
+  res.setHeader('Access-Control-Allow-Origin', '*')
+  res.setHeader('Access-Control-Allow-Methods', 'GET, POST, OPTIONS')
+  res.setHeader('Access-Control-Allow-Headers', 'Content-Type')
+
+  if (req.method === 'OPTIONS') {
+    return res.status(200).end()
+  }
+
+  try {
+    if (req.method === 'GET') {
+      const config = getConfiguration()
+      return res.status(200).json({ success: true, data: config })
+    }
+
+    if (req.method === 'POST') {
+      const body = req.body
+
+      if (!body) {
+        return res.status(400).json({ success: false, error: 'Configuration payload is required' })
+      }
+
+      setConfiguration(body)
+      return res.status(200).json({ success: true })
+    }
+
+    return res.status(405).json({ success: false, error: 'Method not allowed' })
+  }
+  catch (error) {
+    console.error('Error in /api/memory/config:', error)
+    return res.status(500).json({
+      success: false,
+      error: error instanceof Error ? error.message : String(error),
+    })
+  }
+}

api/memory/save.ts

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+import type { VercelRequest, VercelResponse } from '@vercel/node'
+
+import { saveMessage } from '../_lib/memory'
+
+export default async function handler(req: VercelRequest, res: VercelResponse) {
+  // Set CORS headers
+  res.setHeader('Access-Control-Allow-Origin', '*')
+  res.setHeader('Access-Control-Allow-Methods', 'POST, OPTIONS')
+  res.setHeader('Access-Control-Allow-Headers', 'Content-Type')
+
+  if (req.method === 'OPTIONS') {
+    return res.status(200).end()
+  }
+
+  if (req.method !== 'POST') {
+    return res.status(405).json({ success: false, error: 'Method not allowed' })
+  }
+
+  try {
+    const body = req.body as { sessionId?: string, message?: unknown, userId?: string }
+
+    console.info('[Memory Debug API] 收到保存请求:', {
+      sessionId: body?.sessionId,
+      userId: body?.userId,
+      messageKeys: body?.message ? Object.keys(body.message) : 'none',
+      messageRole: (body?.message as any)?.role,
+      messageContent: typeof (body?.message as any)?.content === 'string' ? `${(body?.message as any).content.substring(0, 100)}...` : 'non-string',
+      hasPersistLongTerm: !!(body?.message as any)?.metadata?.persistLongTerm,
+      persistLongTermValue: (body?.message as any)?.metadata?.persistLongTerm,
+    })
+
+    if (!body?.sessionId || typeof body.sessionId !== 'string') {
+      return res.status(400).json({ success: false, error: 'sessionId is required' })
+    }
+
+    if (!body?.message || typeof body.message !== 'object') {
+      return res.status(400).json({ success: false, error: 'message payload is required' })
+    }
+
+    await saveMessage(body.sessionId, body.message as any, body.userId)
+
+    console.info('[Memory Debug API] 消息保存成功')
+
+    return res.status(200).json({ success: true })
+  }
+  catch (error) {
+    console.error('Error in /api/memory/save:', error)
+    return res.status(500).json({
+      success: false,
+      error: error instanceof Error ? error.message : String(error),
+    })
+  }
+}

api/memory/search.ts

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+import type { VercelRequest, VercelResponse } from '@vercel/node'
+
+import { searchSimilar } from '../_lib/memory'
+
+export default async function handler(req: VercelRequest, res: VercelResponse) {
+  // Set CORS headers
+  res.setHeader('Access-Control-Allow-Origin', '*')
+  res.setHeader('Access-Control-Allow-Methods', 'POST, OPTIONS')
+  res.setHeader('Access-Control-Allow-Headers', 'Content-Type')
+
+  if (req.method === 'OPTIONS') {
+    return res.status(200).end()
+  }
+
+  if (req.method !== 'POST') {
+    return res.status(405).json({ success: false, error: 'Method not allowed' })
+  }
+
+  try {
+    const body = req.body as { query?: string, userId?: string, limit?: number }
+
+    console.info('[Memory Debug Search] 收到搜索请求:', {
+      query: body?.query,
+      userId: body?.userId,
+      limit: body?.limit,
+    })
+
+    if (!body?.query || typeof body.query !== 'string') {
+      return res.status(400).json({ success: false, error: 'query is required' })
+    }
+
+    if (!body?.userId || typeof body.userId !== 'string') {
+      return res.status(400).json({ success: false, error: 'userId is required' })
+    }
+
+    const results = await searchSimilar(
+      body.query,
+      body.userId,
+      typeof body.limit === 'number' ? body.limit : undefined,
+    )
+
+    console.info('[Memory Debug Search] 搜索结果数量:', results.length)
+    console.info('[Memory Debug Search] 搜索成功，返回结果')
+
+    return res.status(200).json({ success: true, data: results })
+  }
+  catch (error) {
+    console.error('Error in /api/memory/search:', error)
+    return res.status(500).json({
+      success: false,
+      error: error instanceof Error ? error.message : String(error),
+    })
+  }
+}

api/memory/session/[sessionId].ts

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+import type { VercelRequest, VercelResponse } from '@vercel/node'
+
+import { getRecentMessages } from '../../_lib/memory'
+
+export default async function handler(req: VercelRequest, res: VercelResponse) {
+  // Set CORS headers
+  res.setHeader('Access-Control-Allow-Origin', '*')
+  res.setHeader('Access-Control-Allow-Methods', 'GET, OPTIONS')
+  res.setHeader('Access-Control-Allow-Headers', 'Content-Type')
+
+  if (req.method === 'OPTIONS') {
+    return res.status(200).end()
+  }
+
+  if (req.method !== 'GET') {
+    return res.status(405).json({ success: false, error: 'Method not allowed' })
+  }
+
+  try {
+    const { sessionId } = req.query
+
+    if (!sessionId || typeof sessionId !== 'string') {
+      return res.status(400).json({ success: false, error: 'sessionId is required' })
+    }
+
+    const limitParam = req.query.limit as string | undefined
+    const limit = limitParam ? Number.parseInt(limitParam, 10) : undefined
+
+    const messages = await getRecentMessages(sessionId, Number.isNaN(limit) ? undefined : limit)
+
+    return res.status(200).json({ success: true, data: messages })
+  }
+  catch (error) {
+    console.error('Error in /api/memory/session/[sessionId]:', error)
+    return res.status(500).json({
+      success: false,
+      error: error instanceof Error ? error.message : String(error),
+    })
+  }
+}

api/package.json

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+{
+  "name": "@proj-airi/api",
+  "version": "0.7.2-beta.3",
+  "private": true,
+  "description": "Vercel serverless API functions for AIRI",
+  "dependencies": {
+    "@qdrant/js-client-rest": "^1.15.1",
+    "@upstash/redis": "^1.35.5",
+    "@vercel/kv": "^1.0.1",
+    "@vercel/node": "^5.3.26",
+    "@vercel/postgres": "^0.8.0",
+    "openai": "^4.95.1",
+    "pg": "^8.16.3"
+  },
+  "devDependencies": {
+    "@types/node": "^24.6.2",
+    "@types/pg": "^8.6.6",
+    "typescript": "~5.9.3"
+  }
+}