cpp-httplib/docs-src/pages/en/llm-app/index.md

title, order, status

title	order	status
Building a Desktop LLM App with cpp-httplib	0	draft

Build an LLM-powered translation desktop app step by step, learning both the server and client sides of cpp-httplib along the way. Translation is just an example — swap it out to build your own summarizer, code generator, chatbot, or any other LLM application.

Dependencies

• llama.cpp — LLM inference engine
• nlohmann/json — JSON parser (header-only)
• webview/webview — WebView wrapper (header-only)
• cpp-httplib — HTTP server/client (header-only)

Chapters

1. Embed llama.cpp and create a REST API — Start with a simple API that accepts text via POST and returns a translation as JSON
2. Add token streaming with SSE — Stream translation results token by token using the standard LLM API approach
3. Add model discovery and download — Use the client to search and download GGUF models from Hugging Face
4. Add a Web UI — Serve a translation UI with static file hosting, making the app accessible from a browser
5. Turn it into a desktop app with WebView — Wrap the web app with webview/webview to create an Electron-like desktop application
6. Code reading: llama.cpp's server implementation — Compare your implementation with production-quality code and learn from the differences