💜 Built and maintained by one independent developer — no company, no overhead, just code. If SpawnDev.AI saves you time, please consider sponsoring its development ». Sponsorship is what keeps it alive and maintained.
Run and serve local LLMs and image generation everywhere .NET runs - desktop and the browser - on the SpawnDev.ILGPU.ML inference engine (GGUF models, KV-cache decode, SD-Turbo image generation, WebGPU dispatch-plan capture/replay). LLM decode and SD-Turbo text-to-image both run in-browser on WebGPU, no server or native install.
| Package | What |
|---|---|
| SpawnDev.AI | Core contracts: chat messages/options/results, tool-calling types, the IAiChatService surface, and the IAiServerTransport abstraction. |
| SpawnDev.AI.Server | An Ollama-compatible model server as a library: OpenAI (/v1/chat/completions SSE), Ollama native (/api/chat, /api/generate, /api/tags, /api/show), Anthropic Messages (/v1/messages SSE - works with Claude CLI), OpenAI image generation (/v1/images/generations, SD-Turbo), and an MCP surface (/mcp). One protocol router, transport-free: host it over HTTP on desktop (drop-in on :11434) or over a MessagePort in a browser shared worker - the same code path serves both. Includes a server-side agentic tool loop with two built-in tools (image generation + GitHub library/crew lookup) and small-model reliability aids. Reads desktop models from Ollama's on-disk cache; streams browser models from the SpawnDev hub onto WebGPU. |
| SpawnDev.AI.Blazor | Blazor components for on-device AI chat (streaming bubble, model picker) - built for WebGPU LLMs served in-browser. |
Local LLM serving shouldn't require a native install. The same AiApiRouter that answers curl localhost:11434/api/chat on a desktop can run inside a shared worker in a browser tab, decoding on
WebGPU at interactive speed (qwen2.5-0.5b: ~34 tok/s greedy on an RTX 4070 via dispatch-plan
capture/replay). Tool calling is parsed server-side into structured calls on every protocol surface.
The chat model can generate images and answer questions about the SpawnDev libraries and crew via a server-side tool system (one registration serves the internal agentic loop, MCP, and protocol clients; binary outputs travel out of band through an artifact store). Because the in-browser default is a tiny model, the engine makes the common cases reliable without depending on the model's own tool-calling: it pre-emptively forces the image tool on a clear "draw X" request and grounds SpawnDev questions from a daily-built repository digest fetched once from a CDN. Details: Docs/reliability.md.
Docs/ - protocols (every endpoint + client compatibility), hosting (desktop + browser + the demo), tools, and reliability.
using SpawnDev.AI.Server;
var store = new OllamaModelStore(); // ~/.ollama/models (or OLLAMA_MODELS)
var registry = new ModelRegistry(store, accelerator); // any SpawnDev.ILGPU accelerator
var engine = new AiChatEngine(registry);
var router = new AiApiRouter(engine);
// host it: map every request to router.TryHandleAsync(method, path, bodyJson, yourTransport)Preview. Extracted from the proven SpawnDev.ILGPU.ML Ollama-server example and verified against the
Claude CLI, Ollama clients, and OpenAI-compat clients. The desktop HTTP host, the browser shared-worker
host (LLM chat + SD-Turbo image generation on WebGPU), the agentic tool loop, MCP, and the
live demo all ship today; the Blazor component library is
being fleshed out.
- LostBeard (Todd Tanner) - Captain, library author, keeper of the vision
- Riker (Claude CLI #1) - First Officer, implementation lead on consuming projects
- Data (Claude CLI #2) - Operations Officer, deep-library work, test rigor, root-cause analysis
- Tuvok (Claude CLI #3) - Security/Research Officer, design planning, documentation, code review
- Geordi (Claude CLI #4) - Chief Engineer, library internals, GPU kernels, backend work
- Seven (Claude CLI #5) - Wasm backend, GPU kernels, fail-loud verification
🖖