Move token counting to model detail.

src/lib/Stats.svelte

@@ -1,44 +1,18 @@
 <script context="module" lang="ts">
-  import { countTokens, getDeliminator, getLeadPrompt, getModelDetail, getRoleEnd, getRoleTag, getStartSequence } from './Models.svelte'
+  import { getModelDetail } from './Models.svelte'
   import type { Chat, Message, Model, Usage } from './Types.svelte'
 
   export const getPrice = (tokens: Usage, model: Model): number => {
     const t = getModelDetail(model)
-    return ((tokens.prompt_tokens * t.prompt) + (tokens.completion_tokens * t.completion))
+    return ((tokens.prompt_tokens * (t.prompt || 0)) + (tokens.completion_tokens * (t.completion || 0)))
   }
 
   export const countPromptTokens = (prompts:Message[], model:Model, chat: Chat):number => {
-    const detail = getModelDetail(model)
+    return getModelDetail(model).countPromptTokens(prompts, model, chat)
-    const count = prompts.reduce((a, m) => {
-      a += countMessageTokens(m, model, chat)
-      return a
-    }, 0)
-    switch (detail.type) {
-      case 'Petals':
-        return count + countTokens(model, getStartSequence(chat)) + countTokens(model, getLeadPrompt(chat))
-      case 'OpenAIChat':
-      default:
-        // Not sure how OpenAI formats it, but this seems to get close to the right counts.
-        // Would be nice to know. This works for gpt-3.5.  gpt-4 could be different.
-        // Complete stab in the dark here -- update if you know where all the extra tokens really come from.
-        return count + 3 // Always seems to be message counts + 3
-    }
   }
 
   export const countMessageTokens = (message:Message, model:Model, chat: Chat):number => {
-    const detail = getModelDetail(model)
+    return getModelDetail(model).countMessageTokens(message, model, chat)
-    const delim = getDeliminator(chat)
-    switch (detail.type) {
-      case 'Petals':
-        return countTokens(model, getRoleTag(message.role, model, chat) + ': ' +
-        message.content + getRoleEnd(message.role, model, chat) + (delim || '###'))
-      case 'OpenAIChat':
-      default:
-        // Not sure how OpenAI formats it, but this seems to get close to the right counts.
-        // Would be nice to know. This works for gpt-3.5.  gpt-4 could be different.
-        // Complete stab in the dark here -- update if you know where all the extra tokens really come from.
-        return countTokens(model, '## ' + message.role + ' ##:\r\n\r\n' + message.content + '\r\n\r\n\r\n')
-    }
   }
 
   export const getModelMaxTokens = (model:Model):number => {

src/lib/Types.svelte

@@ -281,13 +281,15 @@ export type ModelDetail = {
     leadPrompt?: string,
     prompt?: number;
     completion?: number;
-    max?: number;
+    max: number;
     opt?: Record<string, any>;
     preFillMerge?: (existingContent:string, newContent:string)=>string;
     enabled?: boolean;
     hide?: boolean;
     check: (modelDetail: ModelDetail) => Promise<void>;
     getTokens: (val: string) => number[];
+    countPromptTokens: (prompts:Message[], model:Model, chat: Chat) => number;
+    countMessageTokens: (message:Message, model:Model, chat: Chat) => number;
     getEndpoint: (model: Model) => string;
     help: string;
     hideSetting: (chatId: number, setting: ChatSetting) => boolean;

src/lib/providers/openai/models.svelte

@@ -1,7 +1,9 @@
 <script context="module" lang="ts">
     import { getApiBase, getEndpointCompletions, getEndpointGenerations } from '../../ApiUtil.svelte'
+    import { countTokens } from '../../Models.svelte'
+    import { countMessageTokens } from '../../Stats.svelte'
     import { globalStorage } from '../../Storage.svelte'
-    import type { ModelDetail } from '../../Types.svelte'
+    import type { Chat, Message, Model, ModelDetail } from '../../Types.svelte'
     import { chatRequest, imageRequest } from './request.svelte'
     import { checkModel } from './util.svelte'
     import { encode } from 'gpt-tokenizer'
@@ -38,7 +40,19 @@ const chatModelBase = {
   check: checkModel,
   getTokens: (value) => encode(value),
   getEndpoint: (model) => get(globalStorage).openAICompletionEndpoint || (getApiBase() + getEndpointCompletions()),
-  hideSetting: (chatId, setting) => !!hiddenSettings[setting.key]
+  hideSetting: (chatId, setting) => !!hiddenSettings[setting.key],
+  countMessageTokens: (message:Message, model:Model, chat: Chat) => {
+        return countTokens(model, '## ' + message.role + ' ##:\r\n\r\n' + message.content + '\r\n\r\n\r\n')
+  },
+  countPromptTokens: (prompts:Message[], model:Model, chat: Chat):number => {
+        // Not sure how OpenAI formats it, but this seems to get close to the right counts.
+        // Would be nice to know. This works for gpt-3.5.  gpt-4 could be different.
+        // Complete stab in the dark here -- update if you know where all the extra tokens really come from.
+        return prompts.reduce((a, m) => {
+          a += countMessageTokens(m, model, chat)
+          return a
+        }, 0) + 3 // Always seems to be message counts + 3
+  }
 } as ModelDetail
 
 // Reference: https://openai.com/pricing#language-models

src/lib/providers/petals/models.svelte

@@ -1,7 +1,9 @@
 <script context="module" lang="ts">
     import { getPetalsBase, getPetalsWebsocket } from '../../ApiUtil.svelte'
+    import { countTokens, getDeliminator, getLeadPrompt, getRoleEnd, getRoleTag, getStartSequence } from '../../Models.svelte'
+    import { countMessageTokens } from '../../Stats.svelte'
     import { globalStorage } from '../../Storage.svelte'
-    import type { ModelDetail } from '../../Types.svelte'
+    import type { Chat, Message, Model, ModelDetail } from '../../Types.svelte'
     import { chatRequest } from './request.svelte'
     import { checkModel } from './util.svelte'
     import llamaTokenizer from 'llama-tokenizer-js'
@@ -33,7 +35,18 @@ const chatModelBase = {
   request: chatRequest,
   getEndpoint: (model) => get(globalStorage).pedalsEndpoint || (getPetalsBase() + getPetalsWebsocket()),
   getTokens: (value) => llamaTokenizer.encode(value),
-  hideSetting: (chatId, setting) => !!hideSettings[setting.key]
+  hideSetting: (chatId, setting) => !!hideSettings[setting.key],
+  countMessageTokens: (message:Message, model:Model, chat: Chat):number => {
+        const delim = getDeliminator(chat)
+        return countTokens(model, getRoleTag(message.role, model, chat) + ': ' +
+        message.content + getRoleEnd(message.role, model, chat) + (delim || '###'))
+  },
+  countPromptTokens: (prompts:Message[], model:Model, chat: Chat):number => {
+        return prompts.reduce((a, m) => {
+          a += countMessageTokens(m, model, chat)
+          return a
+        }, 0) + countTokens(model, getStartSequence(chat)) + countTokens(model, getLeadPrompt(chat))
+  }
 } as ModelDetail
 
 export const chatModels : Record<string, ModelDetail> = {