add api token to axios request header

package.json

@@ -95,7 +95,7 @@
     "express": "^4.18.2",
     "express-async-handler": "^1.2.0",
     "form-data": "^4.0.0",
-    "gpt-tokenizer": "^2.1.1",
+    "gpt-tokenizer": "^2.1.2",
     "grammy": "^1.22.4",
     "jsqr": "^1.4.0",
     "litllm": "^3.0.0",

src/config.ts

@@ -33,7 +33,8 @@ export default {
     ? parseInt(process.env.SESSION_TIMEOUT)
     : 48, // in hours
   llms: {
-    apiEndpoint: process.env.LLMS_ENDPOINT, // // process.env.LLMS_ENDPOINT, // 'http://127.0.0.1:5000',
+    apiEndpoint: 'http://127.0.0.1:5000', // // process.env.LLMS_ENDPOINT, // 'http://127.0.0.1:5000',
+    apiKey: process.env.LLMS_API_KEY ?? '',
     wordLimit: 50,
     model: 'chat-bison',
     minimumBalance: 0,

src/modules/llms/api/athropic.ts

@@ -8,6 +8,7 @@ import { type OnCallBackQueryData, type OnMessageContext, type ChatConversation
 import { type LlmCompletion } from './llmApi'
 import { LlmsModelsEnum } from '../utils/types'
 import { sleep } from '../../sd-images/utils'
+import { headers, headersStream } from './helper'
 
 const logger = pino({
   name: 'anthropic - llmsBot',
@@ -33,7 +34,7 @@ export const anthropicCompletion = async (
       .map(m => { return { content: m.content, role: m.role } })
   }
   const url = `${API_ENDPOINT}/anthropic/completions`
-  const response = await axios.post(url, data)
+  const response = await axios.post(url, data, headers)
   const respJson = JSON.parse(response.data)
   if (response) {
     const totalInputTokens = respJson.usage.input_tokens
@@ -66,7 +67,7 @@ export const anthropicStreamCompletion = async (
   logger.info(`Handling ${model} stream completion`)
   const data = {
     model,
-    stream: true, // Set stream to true to receive the completion as a stream
+    stream: true,
     system: config.openAi.chatGpt.chatCompletionContext,
     max_tokens: limitTokens ? +config.openAi.chatGpt.maxTokens : undefined,
     messages: conversation.filter(c => c.model === model).map(m => { return { content: m.content, role: m.role } })
@@ -77,17 +78,17 @@ export const anthropicStreamCompletion = async (
   if (!ctx.chat?.id) {
     throw new Error('Context chat id should not be empty after openAI streaming')
   }
-  const response: AxiosResponse = await axios.post(url, data, { responseType: 'stream' })
-  // Create a Readable stream from the response
+
+  const response: AxiosResponse = await axios.post(url, data, headersStream)
+
   const completionStream: Readable = response.data
-  // Read and process the stream
   let completion = ''
   let outputTokens = ''
   let inputTokens = ''
   for await (const chunk of completionStream) {
     const msg = chunk.toString()
     if (msg) {
-      if (msg.startsWith('Input Token')) {
+      if (msg.includes('Input Token:')) {
         const regex = /Input Token: (\d+)(.*)/
         // Execute the regular expression
         const match = regex.exec(msg)
@@ -176,22 +177,21 @@ export const toolsChatCompletion = async (
       .map(m => { return { content: m.content, role: m.role } })
   }
   const url = `${API_ENDPOINT}/anthropic/completions/tools`
-  const response = await axios.post(url, input)
+  const response = await axios.post(url, input, headers)
   const respJson = response.data
   if (respJson) {
     const toolId = respJson.id
     let data
     let counter = 1
     while (true) {
-      const resp = await axios.get(`${API_ENDPOINT}/anthropic/completions/tools/${toolId}`)
+      const resp = await axios.get(`${API_ENDPOINT}/anthropic/completions/tools/${toolId}`, headers)
       data = resp.data
       if (data.status === 'DONE' || counter > 20) {
         break
       }
       counter++
       await sleep(3000)
     }
-    console.log('here', data.status, counter)
     if (data.status === 'DONE' && !data.error && counter < 20) {
       const totalInputTokens = data.data.usage.input_tokens
       const totalOutputTokens = data.data.usage.output_tokens

src/modules/llms/api/helper.ts

@@ -0,0 +1,13 @@
+import config from '../../../config'
+
+export function createHeaders (responseType?: string, apiKey = config.llms.apiKey): Record<string, string | any> {
+  const headers: Record<string, string | any> = {}
+  if (responseType) {
+    headers.responseType = responseType
+  }
+  headers.headers = { Authorization: `Bearer ${apiKey}` }
+  return headers
+}
+
+export const headers = createHeaders()
+export const headersStream = createHeaders('stream')

src/modules/llms/api/llmApi.ts

@@ -4,6 +4,8 @@ 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 { type ChatModel } from '../../open-ai/types'
 
 const API_ENDPOINT = config.llms.apiEndpoint // config.llms.apiEndpoint // 'http://localhost:8080' // http://127.0.0.1:5000' // config.llms.apiEndpoint
@@ -58,7 +60,7 @@ export const getChatModelPrice = (
 export const llmAddUrlDocument = async (args: LlmAddUrlDocument): Promise<string> => {
   const data = { ...args }
   const endpointUrl = `${API_ENDPOINT}/collections/document`
-  const response = await axios.post(endpointUrl, data)
+  const response = await axios.post(endpointUrl, data, headers)
   if (response) {
     return response.data.collectionName
   }
@@ -72,7 +74,7 @@ interface LlmCheckCollectionStatusOutput {
 }
 export const llmCheckCollectionStatus = async (name: string): Promise<LlmCheckCollectionStatusOutput> => {
   const endpointUrl = `${API_ENDPOINT}/collections/document/${name}` // ?collectionName=${collectionName}`
-  const response = await axios.get(endpointUrl)
+  const response = await axios.get(endpointUrl, headers)
   if (response) {
     return response.data
   }
@@ -91,7 +93,7 @@ interface QueryUrlDocumentOutput {
 export const queryUrlDocument = async (args: QueryUrlDocument): Promise<QueryUrlDocumentOutput> => {
   const data = { collectionName: args.collectioName, prompt: args.prompt, conversation: args.conversation }
   const endpointUrl = `${API_ENDPOINT}/collections/query`
-  const response = await axios.post(endpointUrl, data)
+  const response = await axios.post(endpointUrl, data, headers)
   if (response) {
     return response.data
   }
@@ -117,7 +119,7 @@ export const llmCompletion = async (
     messages: conversation.filter(c => c.model === model)
   }
   const url = `${API_ENDPOINT}/llms/completions`
-  const response = await axios.post(url, data)
+  const response = await axios.post(url, data, headers)
 
   if (response) {
     const totalInputTokens = response.data.usage.prompt_tokens

src/modules/llms/api/openai.ts

@@ -45,7 +45,6 @@ export async function postGenerateImg (
   const response = await openai.images.generate(
     payload as OpenAI.Images.ImageGenerateParams
   )
-  console.log(response)
   return response.data
 }
 

src/modules/llms/api/pdfHandler.ts

@@ -1,6 +1,7 @@
 import axios, { AxiosError } from 'axios'
 import config from '../../../config'
 import { type ChatConversation } from '../../types'
+import { headers } from './helper'
 
 export interface PdfCompletion {
   completion: ChatConversation | undefined
@@ -12,7 +13,7 @@ export const handlePdf = async (prompt: string): Promise<PdfCompletion> => {
   try {
     const data = { question: prompt }
     const url = `${config.llms.pdfUrl}/ask`
-    const response = await axios.post(url, data)
+    const response = await axios.post(url, data, headers)
     if (response) {
       console.log(response.data)
       return {

src/modules/llms/api/vertex.ts

@@ -6,6 +6,7 @@ import { type Readable } from 'stream'
 import { GrammyError } from 'grammy'
 import { pino } from 'pino'
 import { LlmsModelsEnum } from '../utils/types'
+import { headers, headersStream } from './helper'
 
 const API_ENDPOINT = config.llms.apiEndpoint // config.llms.apiEndpoint  // 'http://127.0.0.1:5000' // config.llms.apiEndpoint
 
@@ -37,7 +38,7 @@ export const vertexCompletion = async (
   }
 
   const url = `${API_ENDPOINT}/vertex/completions`
-  const response = await axios.post(url, data)
+  const response = await axios.post(url, data, headers)
   if (response) {
     const totalInputTokens = 4 // response.data.usage.prompt_tokens;
     const totalOutputTokens = 5 // response.data.usage.completion_tokens;
@@ -77,7 +78,7 @@ export const vertexStreamCompletion = async (
   if (!ctx.chat?.id) {
     throw new Error('Context chat id should not be empty after openAI streaming')
   }
-  const response: AxiosResponse = await axios.post(url, data, { responseType: 'stream' })
+  const response: AxiosResponse = await axios.post(url, data, headersStream)
   // Create a Readable stream from the response
   const completionStream: Readable = response.data
   // Read and process the stream

src/modules/llms/claudeBot.ts

@@ -120,7 +120,7 @@ export class ClaudeBot extends LlmsBase {
       (hasClaudeOpusPrefix(ctx.message?.text ?? '') !== '')
     ) {
       this.updateSessionModel(ctx, LlmsModelsEnum.CLAUDE_OPUS)
-      await this.onChat(ctx, LlmsModelsEnum.CLAUDE_OPUS, false, false) // true)
+      await this.onChat(ctx, LlmsModelsEnum.CLAUDE_OPUS, true, false)
       return
     }
     if (ctx.hasCommand([SupportedCommands.claudeSonnet, SupportedCommands.sonnet, SupportedCommands.sonnetShort])) {