# The technical details behind DrawingPics How does DrawPics work from a technical perspective? TLDR: Miniconda + Diffusers + Electron + Excalidraw One of the most important aspects of creating this tool was finding a stable diffusion locally inference solution. There are many solutions available, such as and . I tested the C++ version, but the inference speed was very slow, and Metal GPU support still had issues (you can find relevant issues in their repo). Ultimately, I decided to use python to run it because PyTorch is mature and MPS support is well-established. And I chose Miniconda, because it can create a small, isolated Python environment to run the program. The AI model should run in the background so that we can continuously produce images while you draw. We need to find an RPC method to enable communication between the Python process and Electron's Node.js process. The easiest way is to run a Python HTTP server, but the memory usage is too high. We need a more lightweight solution, so I used xmlrpc for memory efficiency, although there might be better alternatives that I'm unaware of. The AI inference part is handled by diffusers, which is great, but I had to apply some custom patches to make it work in this situation. This can be a bit challenging if you're not familiar with Python. For the frontend, I initially used a low-level canvas library and tried to implement a drawing pad from scratch. However, it had too many details, so I chose a more mature option: Excalidraw. It's fantastic, with the only shortcoming being limited API support. Finally, I combined all these technologies in Electron, ensuring they work smoothly on both the main process and the renderer process. Ok, Is DrawingPics free to use? 80% of the project is free to use. I only charge a lifetime license for the effort I've put in, as I've spent 4 months on it and made numerous improvements based on user feedback. Currently, only Mac is supported. Windows support will be added later. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.drawing.pics/index/blogs/the-technical-details-behind-drawingpics.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.