Enchanted Developers Only vs AiRC

Enchanted is chat app for LLM researchers to chat with self hosted models. Enchanted supports Ollama API and all ecosystem models. It is necessary to have a running Ollama server to use this app and specify the server endpoint in app settings. Enchanted supports streaming and latest Chat API with conversation context. You can quickly switch between your models to test your prompts. Enchanted supports Markdown, therefore tables, lists and code will be nicely formatted. The app is in early days, but had a long roadmap to be leading tool for LLM community running self hosted models.

AiRC, is a versatile tool designed to interact with large language models (LLMs) and manage AI models locally or via APIs. It provides a user-friendly interface for chatting with AI models, managing downloaded models, and integrating with external AI services like Ollama and DeepSeek. Here's a breakdown of what the application can do: Key Features: 1. Chat with AI Models: * Users can interact with AI models by sending text prompts and receiving responses. * Supports both Ollama (local models) and DeepSeek (cloud-based models) for generating responses. * The chat interface supports Markdown rendering and syntax highlighting for code blocks, making it suitable for technical discussions. 2. Model Management: * Users can download, delete, and duplicate AI models via the Ollama integration. * The application provides a model management interface where users can view installed models, check for updates, and download new models. * Models can be filtered and sorted by name, size, or last updated date. 3. DeepSeek Integration: * The app integrates with DeepSeek, a cloud-based AI service, allowing users to interact with DeepSeek models. * Users can stream responses from DeepSeek models, enabling real-time interaction. * The app also allows users to check their DeepSeek API balance and manage their API key. 4. System Prompt Customization: * Users can set a system prompt to guide the AI's behavior during conversations. * This feature allows for more customized interactions, such as instructing the AI to act as a specific type of assistant. 5. File and Image Handling: * Users can drag and drop text files and images into the chat interface. * The app supports image previews and allows users to include file content in their prompts. 6. Settings and Customization: * The app provides a settings menu where users can configure server settings (e.g., host, port), enable or disable AI services (Ollama, DeepSeek), and adjust appearance settings (e.g., text size, Markdown rendering). * Users can also enable or disable syntax highlighting and choose between different text sizes for better readability. 7. Error Handling and Notifications: * The app includes robust error handling to manage issues like invalid URLs, missing API keys, or server unavailability. * Users are notified of errors via popovers or alerts, ensuring a smooth user experience. 8. Cross-Platform Support: * The app is designed to work on both macOS and iOS, with platform-specific optimizations for each environment. Use Cases: * AI-Powered Chat: Users can have conversations with AI models, ask questions, get help with coding, or generate creative content. * Model Management: Developers or AI enthusiasts can manage their local AI models, download new ones, and keep them updated. * Technical Assistance: The app's support for Markdown and syntax highlighting makes it ideal for technical discussions, code reviews, or debugging. * Custom AI Interactions: By setting custom system prompts, users can tailor the AI's behavior to specific tasks, such as acting as a tutor, a coding assistant, or a creative writer. Summary: AiRC is a powerful application for interacting with AI models, managing local and cloud-based models, and customizing AI interactions. It’s designed for both casual users and developers who want to leverage AI for various tasks, from casual chatting to technical problem-solving. The app’s integration with Ollama and DeepSeek makes it a versatile tool for anyone working with large language models.