mirror of
https://github.com/Anil-matcha/Open-Generative-AI.git
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032ab0c693
The desktop app already has a bundled sd.cpp engine for local generation. This adds a second, complementary engine: an HTTP client that talks to a user-run Wan2GP Gradio server (https://github.com/deepbeepmeep/Wan2GP). Useful when sd.cpp can't run a target model — Wan2GP brings video models (Wan 2.2, Hunyuan, LTX) and large image models (Flux, Qwen-Image) without bundling Python or weights into the app. Architecture - Each model in the unified catalog now carries a `provider` field (`'sdcpp' | 'wan2gp'`). The renderer's `localAI.generate()` routes to the right backend based on that flag. - sd.cpp keeps its existing IPC channels (`local-ai:*`) untouched. Wan2GP gets its own channel namespace (`wan2gp:*`) and lives in its own `electron/lib/wan2gpProvider.js`. - Wan2GP server URL is persisted in `userData/local-ai/wan2gp.json`. `Settings → Local Models` exposes a config bar to test/save the URL. - Generation streams Gradio v4 SSE protocol; both engines emit progress on the shared `local-ai:progress` channel. ImageStudio - Local-model dropdown now filters out video models (`type === 'video'`) since the studio is image-only. SD 1.5 / SDXL / Z-Image (sd.cpp) and Flux / Qwen-Image (Wan2GP) still surface; Wan/Hunyuan/LTX are hidden until the Video Studio is wired up to the same surface. - Progress event handler updated to tolerate both engines' shapes. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
40 lines
2.1 KiB
JavaScript
40 lines
2.1 KiB
JavaScript
const { contextBridge, ipcRenderer } = require('electron');
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contextBridge.exposeInMainWorld('localAI', {
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isElectron: true,
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// ── sd.cpp engine ──────────────────────────────────────────────────────
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getBinaryStatus: () => ipcRenderer.invoke('local-ai:binary-status'),
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downloadBinary: () => ipcRenderer.invoke('local-ai:download-binary'),
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listModels: () => ipcRenderer.invoke('local-ai:list-models'),
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downloadModel: (modelId) => ipcRenderer.invoke('local-ai:download-model', modelId),
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downloadAuxiliary: (auxKey) => ipcRenderer.invoke('local-ai:download-auxiliary', auxKey),
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deleteModel: (modelId) => ipcRenderer.invoke('local-ai:delete-model', modelId),
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cancelDownload: (modelId) => ipcRenderer.invoke('local-ai:cancel-download', modelId),
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generate: (params) => ipcRenderer.invoke('local-ai:generate', params),
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cancelGeneration: () => ipcRenderer.invoke('local-ai:cancel-generation'),
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// ── Wan2GP engine (remote Gradio server) ───────────────────────────────
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wan2gp: {
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getConfig: () => ipcRenderer.invoke('wan2gp:get-config'),
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setUrl: (url) => ipcRenderer.invoke('wan2gp:set-url', url),
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probe: (url) => ipcRenderer.invoke('wan2gp:probe', url),
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listModels: () => ipcRenderer.invoke('wan2gp:list-models'),
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generate: (params) => ipcRenderer.invoke('wan2gp:generate', params),
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cancelGeneration: () => ipcRenderer.invoke('wan2gp:cancel-generation'),
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},
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// Progress events — both engines emit on local-ai:progress
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onProgress: (callback) => {
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const listener = (_, data) => callback(data);
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ipcRenderer.on('local-ai:progress', listener);
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return () => ipcRenderer.removeListener('local-ai:progress', listener);
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},
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onDownloadProgress: (callback) => {
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const listener = (_, data) => callback(data);
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ipcRenderer.on('local-ai:download-progress', listener);
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return () => ipcRenderer.removeListener('local-ai:download-progress', listener);
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},
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});
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