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wranglebot

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open source media asset management

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import { SocketServer } from "../../SocketServer.js"; import { WrangleBot } from "../../../core/WrangleBot.js"; import RouteResult from "../../RouteResult.js"; import LogBot from "logbotjs"; export default { method: "post", requiredParams: ["libraryId", "metafileId"], requiredBody: ["engine", "frames"], url: "/library/:libraryId/metafiles/:metafileId/thumbnails/analyse", handler: async (req, res, bot: WrangleBot, server: SocketServer) => { if (!bot.ML) { return new RouteResult(404, "Machine Learning module not loaded"); } const libraryId = req.params.libraryId; const metafileId = req.params.metafileId; const analyseOptions = req.body; if (analyseOptions.engine === "aleph-alpha" && !analyseOptions.prompt) throw new Error("Prompt is required for aleph-alpha engine"); if (analyseOptions.frames.length === 0) throw new Error("Frames are required for analyse. The array must contain at least one frame UUID"); const result = await bot.query.library .one(libraryId) .metafiles.one(metafileId) .analyse({ engine: analyseOptions.engine, frames: analyseOptions.frames, prompt: analyseOptions.prompt, temperature: Number(analyseOptions.temperature), max_tokens: Number(analyseOptions.max_tokens), }); if (result) { if (analyseOptions.save) { if (!analyseOptions.save.key) throw new Error("Key is required for saving analyse result"); const res = bot.query.library.one(libraryId).metafiles.one(metafileId).metadata.put({ key: analyseOptions.save.key, value: result.response, }); if (!res) throw new Error("Failed to save analyse result"); } const metafile = await bot.query.library.one(libraryId).metafiles.one(metafileId).fetch(); server.inform("database", "metafiles", metafile.toJSON()); return new RouteResult(200, result); } else { return new RouteResult(404, { status: "error", message: `No metafile found with id ${metafileId}`, }); } }, };