DISCLAIMER

->->-> FLUJO is still an early preview! Expect it to break at some points, but improve rapidly! <-<-<-

This issue is currently impacting the CHAT feature and the OPENAI-COMPATIBLE ENDPOINT, fix will come asap!

• a hotfix was implemented to restore minimum functionality
• You can still view the whole Flow execution in the terminal output! (after you started the server in a terminal with npm run dev or npm start)
• You can add ~FLUJOEXPAND=1 or ~FLUJODEBUG=1 somewhere in your message to show more details

IMPORTANT SECURITY NOTE

FLUJO has currently EXTENSIVE logging enabled by default! This will expose your encrypted API-Keys to the terminal output!. Be VERY careful when grabbing videos or streaming and showing the terminal output!

FLUJO

FLUJO is an open-source platform that bridges the gap between workflow orchestration, Model-Context-Protocol (MCP), and AI tool integration. It provides a unified interface for managing AI models, MCP servers, and complex workflows - all locally and open-source.

FLUJO is powered by the PocketFlowFramework and built with CLine and a lot of LOVE.

🌟 Key Features

🔑 Environment & API Key Management

• Secure Storage: Store environment variables and API keys with encryption
• Global Access: Use your stored keys across the entire application
• Centralized Management: Keep all your credentials in one secure place

🤖 Model Management

• Multiple Models: Configure and use different AI models simultaneously
• Pre-defined Prompts: Create custom system instructions for each model
• Provider Flexibility: Connect to various API providers (OpenAI, Anthropic, etc.)
• Local Models: Integrate with Ollama for local model execution

🔌 MCP Server Integration

• Easy Installation: Install MCP servers from GitHub or local filesystem
• Server Management: Comprehensive interface for managing MCP servers
• Tool Inspection: View and manage available tools from MCP servers
• Environment Binding: Connect server environment variables to global storage

🔄 Workflow Orchestration

• Visual Flow Builder: Create and design complex workflows
• Model Integration: Connect different models in your workflow
• Tool Management: Allow or restrict specific tools for each model
• Prompt Design: Configure system prompts at multiple levels (Model, Flow, Node)

💬 Chat Interface

• Flow Interaction: Interact with your flows through a chat interface
• Message Management: Disable messages or split conversations to reduce context size
• File Attachments: Attach documents or audio for LLM processing
• Transcription: Process audio inputs with automatic transcription

🔄 External Tool Integration

• OpenAI Compatible Endpoint: Integrate with tools like CLine or Roo
• Seamless Connection: Use FLUJO as a backend for other AI applications

🚀 Getting Started

Prerequisites

• Node.js (v18 or higher)
• npm or yarn

Installation

1. Clone the repository:

   git clone https://github.com/mario-andreschak/FLUJO.git
   cd FLUJO

2. Install dependencies:

   npm install
   # or
   yarn install

3. Start the development server:

   npm run dev
   # or
   yarn dev

4. Open your browser and navigate to:

   http://localhost:4200
   

5. FLUJO feels and works best if you run it compiled:

   npm run build
   npm start

📖 Usage

Setting Up Models

1. Navigate to the Models page
2. Click "Add Model" to create a new model configuration
3. Configure your model with name, provider, API key, and system prompt
4. Save your configuration

Managing MCP Servers

1. Go to the MCP page
2. Click "Add Server" to install a new MCP server
3. Choose from GitHub repository or local filesystem
4. Configure server settings and environment variables
5. Start and manage your server

Creating Workflows

1. Visit the Flows page
2. Click "Create Flow" to start a new workflow
3. Add processing nodes and connect them
4. Configure each node with models and tools
5. Save your flow

Using the Chat Interface

1. Go to the Chat page
2. Select a flow to interact with
3. Start chatting with your configured workflow
4. Attach files or audio as needed
5. Manage conversation context by disabling messages or splitting conversations

🔄 MCP Integration

FLUJO provides comprehensive support for the Model Context Protocol (MCP), allowing you to:

• Install and manage MCP servers
• Inspect server tools
• Connect MCP servers to your workflows
• Reference tools directly in prompts
• Bind environment variables to your global encrypted storage

📄 License

FLUJO is licensed under the MIT License.

🚀 Roadmap

Here's a roadmap of upcoming features and improvements:

• Real-time Voice Feature: Adding support for Whisper.js or OpenWhisper to enable real-time voice capabilities.
• Visual Debugger: Introducing a visual tool to help debug and troubleshoot more effectively.
• MCP Roots Support: Implementing Checkpoints and Restore features within MCP Roots for better control and recovery options.
• MCP Prompts: Enabling users to build custom prompts that fully leverage the capabilities of the MCP server.
• MCP Proxying STDIO<>SSE: Likely utilizing SuperGateway to proxy standard input/output with Server-Sent Events for enhanced communication: Use MCP Servers managed in FLUJo in any other MCP client.
• Enhanced Integrations: Improving compatibility and functionality with tools like Windsurf, Cursor, and Cline.
• Advanced Orchestration: Adding agent-driven orchestration, batch processing, and incorporating features inspired by Pocketflow.
• Online Template Repository: Creating a platform for sharing models, flows, or complete "packages," making it easy to distribute FLUJO flows to others.
• Edge Device Optimization: Enhancing performance and usability for edge devices.

🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📬 Contact

• GitHub: mario-andreschak

Notes:

• You can add ~FLUJO=HTML, ~FLUJO=MARKDOWN, ~FLUJO=JSON, ~FLUJO=TEXT in your message to format the response, this will give varying results in different tools where you integrate FLUJO.
• You can add ~FLUJOEXPAND=1 or ~FLUJODEBUG=1 somewhere in your message to show more details
• in config/features.ts you can change the Logging-level for the whole application
• in config/features.ts you can enable SSE support which is currently disabled by default

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FLUJO - Empowering your AI workflows with open-source orchestration.