Introduction
Ever wished you could build your own AI-powered tools without writing complex code? Flowise makes that dream a reality. It's a visual workflow builder that lets you create AI applications using a simple drag-and-drop interface—think of it as "LEGO blocks for AI." And the best part? You can run it directly on your SonicBit seedbox, giving you full control over your data and workflows.
In this tutorial, you'll learn how to deploy Flowise on SonicBit, configure it properly, and build your first AI automation. Whether you want to create a chatbot, automate document analysis, or build custom AI agents, this guide will get you started in minutes.
What is Flowise?
Flowise is an open-source low-code platform for building custom LLM (Large Language Model) applications. Instead of writing hundreds of lines of code, you visually connect different components—like language models, vector databases, and tools—to create powerful AI workflows.
Common use cases:
Since Flowise runs entirely on your SonicBit seedbox, your API keys and data never leave your private server. This is perfect if you're working with sensitive information or just want complete control over your AI infrastructure.
Deploying Flowise on SonicBit
SonicBit makes deploying Flowise incredibly simple. No Docker commands, no configuration files—just one click.
Step 1: Install Flowise
That's it. SonicBit automatically handles the Docker container setup, configures Traefik for HTTPS, and assigns you a subdomain. Within 30 seconds, Flowise will be running at https://flowise.yourusername.sonicbit.net.
Step 2: Access Your Flowise Instance
Once deployment completes, click Open App from your SonicBit dashboard. You'll be greeted with the Flowise login screen. By default, there's no authentication configured, but we'll secure that in the next section.
Step 3: Set Up Authentication (Recommended)
Running Flowise without authentication means anyone with your URL can access your AI workflows. Here's how to secure it:
bash
FLOWISE_USERNAME=your_username
FLOWISE_PASSWORD=your_secure_password
Now Flowise requires login credentials before anyone can access your workflows.
Understanding the Flowise Interface
When you first open Flowise, you'll see three main sections:
The canvas is where the magic happens. You'll drag nodes from the sidebar, connect them together, and create AI pipelines that would normally require hundreds of lines of code.
Building Your First AI Workflow
Let's create a simple but powerful chatbot that answers questions about your documents. This tutorial uses OpenAI's GPT models, but Flowise supports many alternatives (Anthropic Claude, local models via Ollama, etc.).
What You'll Need
Step 1: Add Your OpenAI Credentials
Step 2: Create a New Chatflow
Step 3: Build the Workflow
Now you'll add and connect components. Here's the flow we're building:
Document Loader* → **Text Splitter** → **Embeddings** → **Vector Store** → **Conversational Chain** → *Chat
Let's break it down:
- Drag "PDF File" from the Document Loaders section
- Upload your PDF (you can grab one from your SonicBit My Drive)
- Drag "Recursive Character Text Splitter"
- Connect it to the PDF loader
- Keep default settings (1000 chunk size, 200 overlap)
- Drag "OpenAI Embeddings"
- Select your stored credentials
- Connect it to the text splitter
- Drag "In-Memory Vector Store"
- Connect both the embeddings and text splitter to it
- Drag "Conversational Retrieval QA Chain"
- Connect the vector store
- Add "ChatOpenAI" as the language model
- Select GPT-3.5-turbo (or GPT-4 if you prefer)
Step 4: Test Your Chatbot
Click the Save* button, then *Chat in the top right. Your chatbot is now live. Try asking questions about your document:
User: What are the main topics covered in this document?
AI: Based on the document, the main topics include...
The AI reads your PDF, breaks it into chunks, stores it in a vector database, and retrieves relevant sections to answer your questions. All of this happens on your private SonicBit server.
Advanced Tips and Customization
Use Your Own Documents from SonicBit
Since Flowise runs on your seedbox, it has direct access to your files:
Connect Multiple Data Sources
Flowise isn't limited to PDFs. You can combine:
Create API Endpoints
Every chatflow you build can become a REST API:
Now you can integrate your AI workflow into external apps, automation scripts, or webhooks.
Automate with SonicBit Remote Download
Want to automatically process downloaded files with AI? Here's a workflow:
Troubleshooting Common Issues
Flowise won't start after adding environment variables
Chat responses are slow
API key errors
What's Next?
You've just scratched the surface of what Flowise can do. Here are some ideas to explore:
The beauty of running Flowise on SonicBit is that you have unlimited storage for your documents, full control over your data, and the ability to integrate with your other seedbox apps (like Plex metadata analysis or automated torrent content categorization).
Conclusion
Flowise transforms AI development from a coding challenge into a visual design task. By deploying it on your SonicBit seedbox, you get the best of both worlds: powerful AI capabilities with complete privacy and control.
Start simple with document Q&A, then gradually build more complex workflows as you get comfortable with the interface. The Flowise community has hundreds of templates you can import and customize, so you're never starting from scratch.
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