wranglebot
Version:
open source media asset management
58 lines (48 loc) • 2.09 kB
text/typescript
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}`,
});
}
},
};