Working models, everything up until chat endpoint seems to run

src/components/Chat/Chat.tsx

@@ -359,8 +359,10 @@ export const Chat = memo(({ stopConversationRef, courseMetadata }: Props) => {
     if (getCurrentPageName() != 'gpt4') {
       homeDispatch({ field: 'isRetrievalLoading', value: true })
       // Extract text from all user messages in the conversation
-      const token_limit =
-        OpenAIModels[selectedConversation?.model.id as OpenAIModelID].tokenLimit
+      // CHeck models from home context
+      const token_limit = selectedConversation.model.tokenLimit
+      // const token_limit =
+      //   OpenAIModels[selectedConversation?.model.id as OpenAIModelID].tokenLimit
 
       // ! DISABLE MQR FOR NOW -- too unreliable
       // const useMQRetrieval = localStorage.getItem('UseMQRetrieval') === 'true'

src/components/Chat/ModelSelect.tsx

@@ -1,7 +1,6 @@
 import { IconChevronDown, IconExternalLink } from '@tabler/icons-react'
 import { useContext } from 'react'
 import { useMediaQuery } from '@mantine/hooks'
-import { type OpenAIModel } from '@/types/openai'
 import HomeContext from '~/pages/api/home/home.context'
 import { montserrat_heading, montserrat_paragraph } from 'fonts'
 import { Input, Select, Title } from '@mantine/core'
@@ -33,7 +32,7 @@ export const ModelSelect = React.forwardRef<HTMLDivElement, any>(
       selectedConversation &&
         handleUpdateConversation(selectedConversation, {
           key: 'model',
-          value: model as OpenAIModel,
+          value: model,
         })
     }
 

src/pages/api/home/home.state.tsx

@@ -4,6 +4,7 @@ import { FolderInterface } from '@/types/folder'
 import { OpenAIModel, OpenAIModelID } from '@/types/openai'
 import { PluginKey } from '@/types/plugin'
 import { Prompt } from '@/types/prompt'
+import { SupportedModels } from '~/types/LLMProvider'
 
 export interface HomeInitialState {
   apiKey: string
@@ -12,7 +13,7 @@ export interface HomeInitialState {
   lightMode: 'light' | 'dark'
   messageIsStreaming: boolean
   modelError: ErrorMessage | null
-  models: OpenAIModel[]
+  models: SupportedModels
   selectedModel: OpenAIModel | null
   folders: FolderInterface[]
   conversations: Conversation[]

src/pages/api/models.ts

@@ -8,7 +8,7 @@ import {
 
 import { OpenAIModel, OpenAIModelID, OpenAIModels } from '@/types/openai'
 import { decrypt, isEncrypted } from '~/utils/crypto'
-import { LLMProvider, ProviderNames } from '~/types/LLMProviderKeys'
+import { LLMProvider, ProviderNames } from '~/types/LLMProvider'
 import { getOllamaModels } from '~/utils/modelProviders/ollama'
 
 export const config = {
@@ -117,7 +117,6 @@ const handler = async (req: Request): Promise<Response> => {
             return {
               id: model.id,
               name: OpenAIModels[value].name,
-              maxLength: OpenAIModels[value].maxLength,
               tokenLimit: OpenAIModels[value].tokenLimit,
             }
           }
@@ -126,9 +125,13 @@ const handler = async (req: Request): Promise<Response> => {
       })
       .filter((model): model is OpenAIModel => model !== undefined)
 
-    // console.log('Final list of Models: ', models)
+    const finalModels = [...models, ...ollamaModels]
 
-    return new Response(JSON.stringify(models), { status: 200 })
+    console.log('OpenAI Models: ', models)
+    console.log('Ollama Models: ', ollamaModels)
+    console.log('FInal combined: ', finalModels)
+
+    return new Response(JSON.stringify(finalModels), { status: 200 })
   } catch (error) {
     console.error(error)
     return new Response('Error', { status: 500 })

src/types/LLMProviderKeys.ts → src/types/LLMProvider.ts

@@ -1,15 +1,17 @@
-import { OllamaModel } from './OllamaProvider'
+import { OllamaModel } from '~/utils/modelProviders/ollama'
 import { OpenAIModel } from './openai'
 
 export enum ProviderNames {
   Ollama = 'Ollama',
   OpenAI = 'OpenAI',
 }
 
+export type SupportedModels = OllamaModel[] | OpenAIModel[]
+
 export interface LLMProvider {
   provider: ProviderNames
   enabled: boolean
   baseUrl: string
   apiKey?: string
-  models?: OllamaModel[] | OpenAIModel[]
+  models?: SupportedModels
 }

src/types/openai.ts

@@ -3,7 +3,6 @@
 export interface OpenAIModel {
   id: string
   name: string
-  maxLength: number // maximum length of a message in characters... should deprecate
   tokenLimit: number
 }
 
@@ -27,45 +26,38 @@ export const OpenAIModels: Record<OpenAIModelID, OpenAIModel> = {
   [OpenAIModelID.GPT_3_5]: {
     id: OpenAIModelID.GPT_3_5,
     name: 'GPT-3.5 (16k)',
-    maxLength: 12000,
     tokenLimit: 16385,
   },
   [OpenAIModelID.GPT_4]: {
     id: OpenAIModelID.GPT_4,
     name: 'GPT-4 (8k)',
-    maxLength: 24000,
     tokenLimit: 8192,
   },
   [OpenAIModelID.GPT_4_Turbo]: {
     id: OpenAIModelID.GPT_4_Turbo,
     name: 'GPT-4 Turbo (128k)',
-    maxLength: 24000,
     tokenLimit: 128000,
   },
   [OpenAIModelID.GPT_4o]: {
     id: OpenAIModelID.GPT_4o,
     name: 'GPT-4o (128k)',
-    maxLength: 24000,
     tokenLimit: 128000,
   },
 
   // ! Our hard-coded Azure implementation ONLY allows GPT-4, no other azure models on that deployment
   [OpenAIModelID.GPT_4_AZURE]: {
     id: OpenAIModelID.GPT_4_AZURE,
     name: 'GPT-4 Turbo (128k)',
-    maxLength: 24000,
     tokenLimit: 128000,
   },
   [OpenAIModelID.GPT_4_HACKATHON]: {
     id: OpenAIModelID.GPT_4_HACKATHON,
     name: 'GPT-4 Hackathon',
-    maxLength: 24000,
     tokenLimit: 128000,
   },
   [OpenAIModelID.GPT_4_AZURE_04_09]: {
     id: OpenAIModelID.GPT_4_AZURE_04_09,
     name: 'GPT-4 Turbo 0409 (128k)',
-    maxLength: 24000,
     tokenLimit: 128000,
   },
 }

src/utils/modelProviders/ollama.ts

@@ -1,20 +1,23 @@
 export interface OllamaModel {
+  id: string
   name: string
   parameterSize: string
+  tokenLimit: number
 }
 
 export const getOllamaModels = async () => {
-  console.log('In ollama GET endpoint')
   const response = await fetch('https://ollama.ncsa.ai/api/ps')
   if (!response.ok) {
     throw new Error(`HTTP error! status: ${response.status}`)
   }
-
   const data = await response.json()
+
   const ollamaModels: OllamaModel[] = data.models.map((model: any) => {
     return {
+      id: model.name,
       name: model.name,
-      parameterSize: model.parameter_size,
+      parameterSize: model.details.parameter_size,
+      tokenLimit: 4096,
     } as OllamaModel
   })