COGNIFLOW: The AI-Powered Knowledge Graph and Development Studio

COGNIFLOW is a cutting-edge application designed to help developers and researchers organize their thoughts, code snippets, and research findings into an interconnected, AI-enhanced knowledge graph. It combines a powerful note-taking interface with a dedicated development studio and utilizes large language models (LLMs) for intelligent analysis, connection discovery, and code assistance.

Now available as an NPM package: @chieji/cogniflow

Key Features

| Feature | Description | AI Integration | | :--- | :--- | :--- | | Knowledge Graph | Visualize and explore the semantic connections between your notes, code, and ideas. | Automatically discovers and suggests new connections between notes. | | Dev Studio | A dedicated environment for writing, testing, and managing code snippets with syntax highlighting and version control. | Provides code completion, debugging assistance, and code diff analysis. | | AI Chat & Tools | Interact with a conversational AI to summarize notes, generate tags, and perform complex data analysis. | Uses Gemini and Hugging Face models for various cognitive tasks. | | Multimodal Analysis | Analyze visual media (images) and generate speech from text directly within the application. | Leverages Gemini's multimodal capabilities. | | Note Management | Organize notes into folders, apply tags, and easily search through your entire knowledge base. | AI-powered summarization and automatic tagging. |

Technology Stack

| Component | Technology | Purpose | | :--- | :--- | :--- | | Frontend | React, TypeScript, Vite | Fast, modern user interface development. | | State Management | (Assumed) React Hooks / Context API | Managing application state. | | Graph Visualization | D3.js | Rendering the interactive knowledge graph. | | AI Services | Google GenAI SDK (@google/genai) | Integration with Gemini models for core AI features. | | Styling | (Assumed) Tailwind CSS or similar | Utility-first CSS framework for rapid styling. |

Installation

As an NPM Package

npm install @chieji/cogniflow

For Development

Prerequisites

• Node.js (LTS version recommended)
• npm (Node Package Manager)

Setup

1. Clone the repository:

   git clone https://github.com/Chieji/COGNIFLOW.git
   cd COGNIFLOW

2. Install dependencies:

   npm install

3. Configure API Key: The application requires a Gemini API Key for its core AI functionalities. Create a file named .env.local in the root of the project and add your key:

   VITE_GEMINI_API_KEY="YOUR_GEMINI_API_KEY_HERE"

4. Run the development server:

   npm run dev

   The application will be available at http://localhost:3000.

5. Build the library:

   npm run build

   Outputs optimized ES and UMD bundles to the dist/ directory.

Contributing

We welcome contributions! Please feel free to submit issues and pull requests.

License

This project is licensed under the MIT License. See the LICENSE file for details.