Openai o1 models command

.husky/pre-commit

@@ -2,4 +2,4 @@
 . "$(dirname -- "$0")/_/husky.sh"
 
 npm run lint
-tsc --noEmit
+npx tsc --noEmit

.nvmrc

@@ -0,0 +1 @@
+v18

src/bot.ts

@@ -34,7 +34,7 @@ import { WalletConnect } from './modules/walletconnect'
 import { BotPayments } from './modules/payment'
 import { BotSchedule } from './modules/schedule'
 import config from './config'
-import { commandsHelpText, FEEDBACK, LOVE, MODELS, SUPPORT, TERMS, LANG, ALIAS } from './constants'
+import { commandsHelpText, FEEDBACK, LOVE, SUPPORT, TERMS, LANG, ALIAS } from './constants'
 import prometheusRegister, { PrometheusMetrics } from './metrics/prometheus'
 
 import { chatService, statsService } from './database/services'
@@ -57,6 +57,7 @@ import { VoiceToVoiceGPTBot } from './modules/voice-to-voice-gpt'
 // import { VoiceCommand } from './modules/voice-command'
 import { createInitialSessionData } from './helpers'
 import { LlamaAgent } from './modules/subagents'
+import { llmModelManager } from './modules/llms/utils/llmModelsManager'
 
 Events.EventEmitter.defaultMaxListeners = 30
 
@@ -504,10 +505,13 @@ bot.command('support', async (ctx) => {
 })
 
 bot.command('models', async (ctx) => {
+  const models = llmModelManager.generateTelegramOutput()
+  console.log(models)
   writeCommandLog(ctx as OnMessageContext).catch(logErrorHandler)
-  return await ctx.reply(MODELS.text, {
+  return await ctx.reply(models, {
     parse_mode: 'Markdown',
-    link_preview_options: { is_disabled: true }
+    link_preview_options: { is_disabled: true },
+    message_thread_id: ctx.message?.message_thread_id
   })
 })
 

src/helpers.ts

@@ -1,5 +1,6 @@
 import config from './config'
-import { LlmsModelsEnum } from './modules/llms/utils/types'
+import { LlmModelsEnum } from './modules/llms/utils/llmModelsManager'
+import { type DalleImageSize } from './modules/llms/utils/types'
 import { type BotSessionData } from './modules/types'
 
 export function createInitialSessionData (): BotSessionData {
@@ -38,14 +39,14 @@ export function createInitialSessionData (): BotSessionData {
     },
     dalle: {
       numImages: config.openAi.dalle.sessionDefault.numImages,
-      imgSize: config.openAi.dalle.sessionDefault.imgSize,
+      imgSize: config.openAi.dalle.sessionDefault.imgSize as DalleImageSize,
       isEnabled: config.openAi.dalle.isEnabled,
       imgRequestQueue: [],
       isProcessingQueue: false,
       imageGenerated: [],
       isInscriptionLotteryEnabled: config.openAi.dalle.isInscriptionLotteryEnabled,
       imgInquiried: []
     },
-    currentModel: LlmsModelsEnum.GPT_4
+    currentModel: LlmModelsEnum.GPT_4O
   }
 }

src/modules/llms/api/athropic.ts

@@ -6,9 +6,9 @@ import { pino } from 'pino'
 import config from '../../../config'
 import { type OnCallBackQueryData, type OnMessageContext, type ChatConversation } from '../../types'
 import { type LlmCompletion } from './llmApi'
-import { LlmsModelsEnum } from '../utils/types'
 import { sleep } from '../../sd-images/utils'
 import { headers, headersStream } from './helper'
+import { LlmModelsEnum } from '../utils/llmModelsManager'
 
 const logger = pino({
   name: 'anthropic - llmsBot',
@@ -22,7 +22,7 @@ const API_ENDPOINT = config.llms.apiEndpoint // 'http://127.0.0.1:5000' // confi
 
 export const anthropicCompletion = async (
   conversation: ChatConversation[],
-  model = LlmsModelsEnum.CLAUDE_OPUS
+  model = LlmModelsEnum.CLAUDE_3_OPUS
 ): Promise<LlmCompletion> => {
   logger.info(`Handling ${model} completion`)
   const data = {
@@ -59,7 +59,7 @@ export const anthropicCompletion = async (
 
 export const anthropicStreamCompletion = async (
   conversation: ChatConversation[],
-  model = LlmsModelsEnum.CLAUDE_OPUS,
+  model = LlmModelsEnum.CLAUDE_3_OPUS,
   ctx: OnMessageContext | OnCallBackQueryData,
   msgId: number,
   limitTokens = true
@@ -158,7 +158,7 @@ export const anthropicStreamCompletion = async (
 
 export const toolsChatCompletion = async (
   conversation: ChatConversation[],
-  model = LlmsModelsEnum.CLAUDE_OPUS
+  model = LlmModelsEnum.CLAUDE_3_OPUS
 ): Promise<LlmCompletion> => {
   logger.info(`Handling ${model} completion`)
   const input = {

src/modules/llms/api/llmApi.ts

@@ -2,9 +2,9 @@ import axios from 'axios'
 import config from '../../../config'
 import { type ChatConversation } from '../../types'
 import pino from 'pino'
-import { LlmsModels, LlmsModelsEnum } from '../utils/types'
 import { type ChatModel } from '../utils/types'
 import { headers } from './helper'
+import { llmModelManager, LlmModelsEnum } from '../utils/llmModelsManager'
 
 // import { type ChatModel } from '../../open-ai/types'
 
@@ -39,8 +39,8 @@ interface QueryUrlDocument {
   conversation?: ChatConversation[]
 }
 
-export const getChatModel = (modelName: string): ChatModel => {
-  return LlmsModels[modelName]
+export const getChatModel = (modelName: string): ChatModel | undefined => {
+  return llmModelManager.getModel(modelName) as ChatModel//  LlmsModels[modelName]
 }
 
 export const getChatModelPrice = (
@@ -111,7 +111,7 @@ export const deleteCollection = async (collectionName: string): Promise<void> =>
 
 export const llmCompletion = async (
   conversation: ChatConversation[],
-  model = LlmsModelsEnum.BISON
+  model = LlmModelsEnum.CHAT_BISON
 ): Promise<LlmCompletion> => {
   const data = {
     model, // chat-bison@001 'chat-bison', //'gpt-3.5-turbo',