An AI plugin for Embarcadero RAD Studio IDE (XE5 to 12.1) integrating ChatGPT, Writesonic, YouChat, and offline Ollama for code assistance.
ChatGPTWizard is an AI plugin for Embarcadero RAD Studio IDE that integrates multiple AI services, including ChatGPT, Writesonic, YouChat, and offline Ollama models, directly into the Delphi development environment. It enables developers to generate code, find bugs, write tests, optimize logic, and get explanations without leaving their IDE, streamlining the coding process with AI-powered assistance.
Delphi developers using Embarcadero RAD Studio versions XE5 to 12.1 who want to integrate AI-assisted coding, code analysis, and automation directly into their IDE workflow.
It uniquely supports both online AI services and offline Ollama models for privacy and flexibility, offers deep IDE integration with context menus and dockable forms, and is tailored specifically for the Delphi ecosystem with features like class-level operations and history management.
A ChatGPT, Gemini, Claude, and Ollama(offline) plug-in for Embarcadero RAD Studio IDE XE5 to 12.1
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Supports ChatGPT, Writesonic, YouChat online, and Ollama offline, giving developers choice and privacy options, as highlighted in the README's setup guide for local models.
Offers inline code assistance with cpt: delimiters, context menus for bugs/tests, and a dockable form, seamlessly blending AI into the RAD Studio workflow without switching apps.
Uses SQLite-based history with fuzzy string search to save and reuse prompts, reducing token costs and improving efficiency, as demonstrated in the README's screenshots.
Allows analysis and manipulation of entire Delphi classes with custom prompts using @Class placeholder, though best for small classes due to API limitations.
Explicitly not updated for RAD Studio 12.2+, where Embarcadero's built-in AI replaces it, limiting long-term viability for users upgrading their IDE.
Relies on paid API keys for online services with usage caps, adding ongoing expenses; the README warns that some keys require purchasing credits after limits.
Setting up Ollama for offline mode involves downloading models and configuring URLs, with performance varying by hardware, making it less plug-and-play.
Class view feature can't handle thousands of lines due to API constraints, restricting its use for big projects, as admitted in the README's notes.