{"id":17104,"date":"2025-05-12T11:45:27","date_gmt":"2025-05-12T18:45:27","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=17104"},"modified":"2025-06-13T16:36:05","modified_gmt":"2025-06-13T23:36:05","slug":"couchbase-vector-store-flowise","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/couchbase-vector-store-flowise\/","title":{"rendered":"Introducing Couchbase as a Vector Store in Flowise"},"content":{"rendered":"

We\u2019re excited to announce that Couchbase is now officially supported as a vector store in Flowise, providing users with a powerful, high-performance solution for managing and retrieving vector data. This new integration combines Flowise’s intuitive, no-code AI workflow capabilities with Couchbase\u2019s scalable, flexible vector storage, making it easier than ever to build and deploy AI-driven applications.<\/p>\n

Flowise is an open-source tool that allows users to create and manage AI workflows with a visual, no-code interface. It\u2019s designed to simplify the integration of machine learning models and data pipelines, offering users an accessible and efficient way to incorporate AI into their applications without the need for complex coding.<\/p>\n

In the following sections, we’ll explore some details of this integration.<\/p>\n

Setting up Flowise with Couchbase<\/h2>\n

To get started with the Flowise and Couchbase, you\u2019ll need to follow a few simple steps.<\/p>\n

Installing Flowise<\/h3>\n

There are multiple ways to install Flowise:<\/p>\n

Method 1: Install Flowise locally using NPM<\/h4>\n
    \n
  1. Install Flowise globally:\n
    npm install -g flowise<\/pre>\n<\/li>\n
  2. Start Flowise:\n
    npx flowise start<\/pre>\n<\/li>\n<\/ol>\n
    Method 2: Install Flowise using Docker<\/h4>\n
    There are two ways to deploy Flowise with Docker: Docker Compose<\/em> or Docker Image<\/em>.<\/p>\n
    Using a Docker image<\/h5>\n
      \n
    1. \n
        \n
      1. Clone the Flowise Repository locally:\n
        git clone https:\/\/github.com\/FlowiseAI\/Flowise.git<\/pre>\n<\/li>\n
      2. Navigate to docker folder at the root of the project:\n
        cd docker<\/pre>\n<\/li>\n
      3. Build the Docker image with the following command:\n
        docker build --no-cache -t flowise .<\/pre>\n<\/li>\n
      4. Once the image is built, run the container:\n
        docker run -d --name flowise -p 3000:3000 flowise<\/pre>\n<\/li>\n
      5. To stop the running container:\n
        docker stop flowise<\/pre>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n
        Using Docker Compose<\/h5>\n
          \n
        1. \n
            \n
          1. Clone the Flowise Repository locally:\n
            git clone https:\/\/github.com\/FlowiseAI\/Flowise.git<\/pre>\n<\/li>\n
          2. Navigate to docker folder at the root of the project:\n
            cd docker<\/pre>\n<\/li>\n
          3. Copy the .env.example file and rename it as .env\n
            cp .env.example .env<\/pre>\n<\/li>\n
          4. To start the containers, use Docker Compose:\n
            docker compose up -d<\/pre>\n<\/li>\n
          5. To bring the containers down, use the following command:\n
            docker compose stop<\/pre>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n
            Now you have Flowise installed, you can access it by navigating to https:\/\/localhost:3000<\/a>.<\/p>\n
            Alternatively, you can also use the Flowise Cloud Version<\/a>.<\/p>\n
            Upserting to Couchbase and running a query<\/h3>\n
            Now that Flowise and Couchbase are integrated, you can upsert data into Couchbase and perform vector searches. In this blog, we will show you how to upsert a PDF file into Couchbase using Flowise.<\/p>\n
            1. Upsert data into Couchbase<\/h4>\n
            To upsert data into Couchbase, drag and connect the following nodes on the Flowise canvas:<\/p>\n