Kognitivekompanion

KognitiveKompanion is a modern and multi-functional AI interaction interface that supports desktop environments such as KDE and provides seamless integration with OpenAI, Ollama, and AMD Ryzen AI hardware acceleration.

Artificial intelligence chatbots Developer tools #AI interaction #Multi-backend #Hardware acceleration #Desktop integration .Python

rating : 2 points

downloads : 9

update time : 2025-04-23

What is MCP Server?

MCP Server acts as a middleware that standardizes communication between AI applications and various model backends. It provides a unified interface regardless of whether you're using cloud-based services like OpenAI or local models through Ollama/Ryzen AI.

How to use MCP Server?

The server runs in the background and automatically handles requests from compatible applications like KognitiveKompanion. No direct interaction is needed for basic usage.

Use Cases

Ideal for: 1) Switching between AI backends without changing application code 2) Managing multiple model instances 3) Implementing advanced features like RAG across different providers

Key Features

Multi-Backend SupportSeamlessly switch between OpenAI, Ollama and AMD Ryzen AI with the same API interface

Smart Context ManagementAutomatically handles conversation history and context window optimization

Hardware AccelerationLeverages AMD Ryzen AI NPU for local model acceleration when available

Pros and Cons

Advantages

Single interface for all supported AI backends

Automatic context management reduces token waste

Hardware acceleration support improves local model performance

Limitations

Slight latency overhead compared to direct backend access

Requires separate setup for each backend

AMD Ryzen AI support limited to specific hardware

Getting Started

Installation

The server is automatically installed with KognitiveKompanion. For standalone use, install via pip:

Configuration

Create a configuration file at ~/.config/mcp/config.yaml with your backend preferences

Running the Server

Start the server in either foreground or background mode:

Usage Scenarios

Switching Between Cloud and LocalUse OpenAI when connected, automatically fallback to Ollama when offline

Hardware Accelerated Local AIUtilize AMD Ryzen AI NPU for faster local model execution

Frequently Asked Questions

Do I need to manually start the MCP server?

How do I know which backend is active?

Additional Resources

MCP Protocol Specification

Technical details of the protocol

Ryzen AI Setup Guide

Configuration for AMD hardware acceleration

🚀 Cognitive Kompanion

A modern and versatile AI interface designed for KDE and other desktop environments, aiming to seamlessly connect to various AI backends, including OpenAI, Ollama, and AMD Ryzen AI hardware acceleration.

🚀 Quick Start

Cognitive Kompanion is a modern AI interface that supports multiple backends. Here's how you can get started:

Installation

Clone the repository:

git clone https://github.com/MagicUnicornInc/KognitiveKompanion.git
cd KognitiveKompanion

Install the dependencies:

pip install -r requirements.txt

Run the application with the desired backend:

# OpenAI backend
./run_openai_gui.sh

# Ollama backend
./run_kde_ai_interface.py

# AMD Ryzen AI (if hardware is supported)
./run_ryzen_ai_model.py

Configuration

For detailed setup of different backends, refer to MULTI_BACKEND_GUIDE.md.

For specific settings regarding AMD Ryzen AI, refer to README_RYZEN_AI_SETUP.md.

✨ Features

Multi-backend Support:
- OpenAI API integration (GPT-4o, GPT-3.5-Turbo, etc.)
- Ollama backend for local models
- AMD Ryzen AI hardware acceleration
Advanced UI:
- Collapsible areas to keep the interface clean
- Chat sidebar for managing chat history
- Modern style with KDE theme integration
- System tray icon and floating window options
Contextual Features:
- Screen capture function to provide visual context
- Audio input support
- Function-enhanced generation (RAG) with a switch
Conversation Management:
- Save and load conversations
- Export chat records

📦 Requirements

Python 3.8+ (Python 3.12 is recommended)
PyQt5
KDE Plasma 5 desktop environment (optional, other desktop environments are also supported)
One of the following backends:
- OpenAI API key
- Locally running Ollama
- AMD Ryzen AI compatible hardware (optional)

📚 Documentation

Project Structure

├── app_root/             # Core application code
│   ├── ui/               # UI components and widgets
│   ├── mcp/              # Model Control Protocol client
│   ├── config/           # Configuration management
│   ├── rag/              # Retrieval Augmented Generation
│   ├── system/           # System integration and optimization
│   └── utils/            # Utility functions
├── amd-ryzen-ai/         # AMD Ryzen AI integration
├── quark-integration/    # Quantization toolkit integration
└── MCP-INTEGRATION-GUIDE.md  # MCP server documentation