Flowise Ai Pre-configured by Miri Infotech Inc. on Ubuntu

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About

Flowise AI is a powerful open-source tool designed to make building LLM-based applications accessible and intuitive. Built on top of LangChain, Flowise provides a visual interface where users can create, customize, and deploy AI workflows using a drag-and-drop node system. This no-code/low-code platform allows developers, data scientists, and non-technical users to connect components like language models, vector databases, APIs, and more—visually and efficiently.

Flowise enables rapid prototyping and deployment of complex AI applications, such as chatbots, retrieval-augmented generation (RAG) systems, data agents, and more. It supports multiple LLM providers (OpenAI, Cohere, Hugging Face, etc.), vector stores (Pinecone, Chroma, Weaviate, etc.), and integrates easily into existing infrastructure with REST APIs and embedding capabilities.

Key Highlights :

100% open-source under the MIT License; customizable and extensible.

Drag-and-drop interface to design LLM workflows easily.

Built on LangChain for robust, modular, and scalable LLM pipelines.

Native support for Chroma, Pinecone, Weaviate, FAISS, etc.

Works with OpenAI, Cohere, Hugging Face, Azure, and more.

Integrate with other tools and systems via API endpoints.

 

 

You can subscribe to Mautic, an AWS Marketplace product and launch an instance from the product’s AMI using the Amazon EC2 launch wizard.

To launch an instance from the AWS Marketplace using the launch wizard

  • Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/
  • From the Amazon EC2 dashboard, choose Launch Instance. On the Choose an Amazon Machine Image (AMI) page, choose the AWS Marketplace category on the left. Find a suitable AMI by browsing the categories, or using the search functionality. Choose Select to choose your product.
  • A dialog displays an overview of the product you’ve selected. You can view the pricing information, as well as any other information that the vendor has provided. When you’re ready, choose Continue.
  • On the Choose an Instance Type page, select the hardware configuration and size of the instance to launch. When you’re done, choose Next: Configure Instance Details.
  • On the next pages of the wizard, you can configure your instance, add storage, and add tags. For more information about the different options you can configure, see Launching an Instance. Choose Next until you reach the Configure Security Group page.
  • The wizard creates a new security group according to the vendor’s specifications for the product. The security group may include rules that allow all IP addresses (0.0.0.0/0) access on SSH (port 22) on Linux or RDP (port 3389) on Windows. We recommend that you adjust these rules to allow only a specific address or range of addresses to access your instance over those ports
  • When you are ready, choose Review and Launch.
  • On the Review Instance Launch page, check the details of the AMI from which you’re about to launch the instance, as well as the other configuration details you set up in the wizard. When you’re ready, choose Launch to select or create a key pair, and launch your instance.
  • Depending on the product you’ve subscribed to, the instance may take a few minutes or more to launch. You are first subscribed to the product before your instance can launch. If there are any problems with your credit card details, you will be asked to update your account details. When the launch confirmation page displays.

Usage/Deployment Instructions

Step 1: SSH into your instance with username ubuntu and key pair to start the application

Username: ubuntu

ssh -i ssh_key.pem ubuntu@instance-IP

Run below commands to start flowsie :-

cd /home/ubuntu

docker start flowise

docker ps

Step 2: Use your web browser to access the application at:

http://<instance-ip-address>:3000

 

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    Highlights

    • icon

      Drag-and-drop interface to design LLM workflows easily.

    • icon

      Built on LangChain for robust, modular, and scalable LLM pipelines.

    • icon

      Works with OpenAI, Cohere, Hugging Face and more

    • icon

      Integrate with other tools and systems via API endpoints.

    • icon

      Extend functionality by building custom nodes in TypeScript or JavaScript.

    Application Installed

    • icon Linux