Baidu VectorDB (Mochow)

npm install @mochow/mochow-sdk-node

from mem0 import Memory

config = {
    "vector_store": {
        "provider": "baidu",
        "config": {
            "endpoint": "http://your-mochow-endpoint:8287",
            "account": "root",
            "api_key": "your-api-key",
            "database_name": "mem0",
            "table_name": "mem0_table",
            "embedding_model_dims": 1536,
            "metric_type": "COSINE"
        }
    }
}

m = Memory.from_config(config)
messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about a thriller movie? They can be quite engaging."},
    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
]
m.add(messages, user_id="alice", metadata={"category": "movies"})

import { Memory } from "mem0ai/oss";

const memory = new Memory({
  embedder: {
    provider: "openai",
    config: {
      apiKey: process.env.OPENAI_API_KEY || "",
      model: "text-embedding-3-small",
      embeddingDims: 1536,
    },
  },
  vectorStore: {
    provider: "baidu",
    config: {
      endpoint: process.env.BAIDU_ENDPOINT || "",
      account: process.env.BAIDU_ACCOUNT || "root",
      apiKey: process.env.BAIDU_API_KEY || "",
      databaseName: "mem0",
      tableName: "mem0_table",
      embeddingModelDims: 1536,
      metricType: "COSINE",
    },
  },
  llm: {
    provider: "openai",
    config: {
      apiKey: process.env.OPENAI_API_KEY || "",
      model: "gpt-5-mini",
    },
  },
});