Aix: +select-Draw

src/apps/draw/create/PromptComposer.tsx

@@ -119,7 +119,7 @@ export function PromptComposer(props: {
   const handleSimpleEnhance = React.useCallback(async () => {
     if (nonEmptyPrompt?.trim()) {
       setIsSimpleEnhancing(true);
-      const improvedPrompt = await imaginePromptFromText(nonEmptyPrompt, null).catch(console.error);
+      const improvedPrompt = await imaginePromptFromText(nonEmptyPrompt, 'DEV').catch(console.error);
       if (improvedPrompt)
         setNextPrompt(improvedPrompt);
       setIsSimpleEnhancing(false);

src/modules/aifn/imagine/imaginePromptFromText.ts

@@ -1,4 +1,4 @@
-import { llmChatGenerateOrThrow, VChatMessageIn } from '~/modules/llms/llm.client';
+import { aixChatGenerateTextNS_Simple } from '~/modules/aix/client/aix.client';
 
 import { getLLMIdOrThrow } from '~/common/stores/llms/store-llms';
 
@@ -13,7 +13,7 @@ Provide output a single image generation prompt and nothing else.`;
 /**
  * Creates a caption for a drawing or photo given some description - used to elevate the quality of the imaging
  */
-export async function imaginePromptFromText(messageText: string, contextRef: string | null): Promise<string | null> {
+export async function imaginePromptFromText(messageText: string, contextRef: string): Promise<string | null> {
 
   // we used the fast LLM, but let's just converge to the chat LLM here
   const llmId = getLLMIdOrThrow(['fast', 'chat'], false, false, 'imagine-prompt-from-text');
@@ -24,12 +24,12 @@ export async function imaginePromptFromText(messageText: string, contextRef: str
   if (!/[.!?]$/.test(messageText)) messageText += '.';
 
   try {
-    const instructions: VChatMessageIn[] = [
-      { role: 'system', content: simpleImagineSystemPrompt },
-      { role: 'user', content: 'Write a minimum of 20-30 words prompt and up to the size of the input, based on the INPUT below.\n\nINPUT:\n' + messageText },
-    ];
-    const chatResponse = await llmChatGenerateOrThrow(llmId, instructions, 'draw-expand-prompt', contextRef, null, null);
-    return chatResponse.content?.trim() ?? null;
+    return (await aixChatGenerateTextNS_Simple(
+      llmId,
+      simpleImagineSystemPrompt,
+      'Write a minimum of 20-30 words prompt and up to the size of the input, based on the INPUT below.\n\nINPUT:\n' + messageText,
+      'draw-expand-prompt', contextRef,
+    )).trim();
   } catch (error: any) {
     console.error('imaginePromptFromText: fetch request error:', error);
     return null;

src/modules/aifn/summarize/summerize.ts

@@ -1,4 +1,4 @@
-import { llmChatGenerateOrThrow, VChatMessageIn } from '~/modules/llms/llm.client';
+import { aixChatGenerateTextNS_Simple } from '~/modules/aix/client/aix.client';
 
 import type { DLLMId } from '~/common/stores/llms/llms.types';
 import { findLLMOrThrow } from '~/common/stores/llms/store-llms';
@@ -82,12 +82,12 @@ async function cleanUpContent(chunk: string, llmId: DLLMId, _ignored_was_targetW
   const autoResponseTokensSize = contextTokens ? Math.floor(contextTokens * outputTokenShare) : null;
 
   try {
-    const instructions: VChatMessageIn[] = [
-      { role: 'system', content: cleanupPrompt },
-      { role: 'user', content: chunk },
-    ];
-    const chatResponse = await llmChatGenerateOrThrow(llmId, instructions, 'chat-ai-summarize', null, null, null, autoResponseTokensSize ?? undefined);
-    return chatResponse?.content ?? '';
+    return (await aixChatGenerateTextNS_Simple(
+      llmId,
+      cleanupPrompt,
+      chunk,
+      'chat-ai-summarize', 'DEV',
+    )).trim();
   } catch (error: any) {
     return '';
   }