rebrand

commands/message/genai/gemini-pro.js

@@ -0,0 +1,70 @@
+const { gemini, LlmModelsGenerate } = require("../../../labscore/api/obelisk");
+const { createEmbed } = require("../../../labscore/utils/embed");
+const { editOrReply } = require("../../../labscore/utils/message");
+
+const { Permissions } = require("detritus-client/lib/constants");
+
+const { STATIC_ICONS } = require("../../../labscore/utils/statics");
+const { stringwrap, iconPill, smallIconPill } = require("../../../labscore/utils/markdown");
+const { hasFeature } = require("../../../labscore/utils/testing");
+module.exports = {
+  name: 'gemini-pro',
+  label: 'text',
+  aliases: ['gpro'],
+  metadata: {
+    description: `${iconPill("generative_ai", "LIMITED TESTING")}\n${smallIconPill("reply", "Supports Replies")}\n\nRun Gemini 1.0 Pro with a custom prompt.`,
+    description_short: 'Gemini-1.0-Pro',
+    examples: ['gem why do they call it oven when you of in the cold food of out hot eat the food'],
+    category: 'limited',
+    usage: 'gemini-pro <prompt>'
+  },
+  permissionsClient: [Permissions.EMBED_LINKS, Permissions.SEND_MESSAGES, Permissions.USE_EXTERNAL_EMOJIS, Permissions.ATTACH_FILES, Permissions.READ_MESSAGE_HISTORY],
+  run: async (context, args) => {
+    if(!await hasFeature(context, "ai/gemini/text")) return;
+    context.triggerTyping();
+
+    if(!args.text) return editOrReply(context, createEmbed("warning", context, `Missing Parameter (text).`))
+
+    let input = args.text;
+
+    try{
+      await editOrReply(context, createEmbed("ai_custom", context, STATIC_ICONS.ai_gemini))
+
+      let res = await LlmModelsGenerate(context, "gemini-1.5-pro", input, "BLOCK_NONE")
+
+      let description = []
+      let files = [];
+      
+      if(res.response.body.message) return editOrReply(context, createEmbed("error", context, e.response.body.message))
+
+      let output = res.response.body.candidates[0]?.output
+      if(!output) return editOrReply(context, createEmbed("error", context, `Gemini returned an error. Try again later.`)) 
+
+      if(output.length <= 4000) description.push(output)
+      else {
+        files.push({
+          filename: `gemini.${Date.now().toString(36)}.txt`,
+          value: Buffer.from(output)
+        })
+      }
+
+      return editOrReply(context, {
+        embeds:[createEmbed("defaultNoFooter", context, {
+          author: {
+            name: stringwrap(input, 50, false),
+            iconUrl: STATIC_ICONS.ai_gemini
+          },
+          description: description.join('\n'),
+          footer: {
+            text: `Generative AI is experimental • Data submitted to Gemini may be used by Google for training.`
+          }
+        })],
+        files
+      })
+    } catch(e){
+      console.log(e)
+      if(e.response?.body?.message) return editOrReply(context, createEmbed("error", context, e.response.body.message))
+      return editOrReply(context, createEmbed("error", context, `Unable to generate response.`))
+    }
+  }
+};