import { type ActionFunctionArgs } from '@remix-run/cloudflare'; import { StreamingTextResponse, parseStreamPart } from 'ai'; import { streamText } from '~/lib/.server/llm/stream-text'; import { stripIndents } from '~/utils/stripIndent'; import type { ProviderInfo } from '~/types/model'; const encoder = new TextEncoder(); const decoder = new TextDecoder(); export async function action(args: ActionFunctionArgs) { return enhancerAction(args); } async function enhancerAction({ context, request }: ActionFunctionArgs) { const { message, model, provider, apiKeys } = await request.json<{ message: string; model: string; provider: ProviderInfo; apiKeys?: Record; }>(); const { name: providerName } = provider; // validate 'model' and 'provider' fields if (!model || typeof model !== 'string') { throw new Response('Invalid or missing model', { status: 400, statusText: 'Bad Request', }); } if (!providerName || typeof providerName !== 'string') { throw new Response('Invalid or missing provider', { status: 400, statusText: 'Bad Request', }); } try { const result = await streamText( [ { role: 'user', content: `[Model: ${model}]\n\n[Provider: ${providerName}]\n\n` + stripIndents` You are a professional prompt engineer specializing in crafting precise, effective prompts. Your task is to enhance prompts by making them more specific, actionable, and effective. I want you to improve the user prompt that is wrapped in \`\` tags. For valid prompts: - Make instructions explicit and unambiguous - Add relevant context and constraints - Remove redundant information - Maintain the core intent - Ensure the prompt is self-contained - Use professional language For invalid or unclear prompts: - Respond with a clear, professional guidance message - Keep responses concise and actionable - Maintain a helpful, constructive tone - Focus on what the user should provide - Use a standard template for consistency IMPORTANT: Your response must ONLY contain the enhanced prompt text. Do not include any explanations, metadata, or wrapper tags. ${message} `, }, ], context.cloudflare.env, undefined, apiKeys, ); const transformStream = new TransformStream({ transform(chunk, controller) { const text = decoder.decode(chunk); const lines = text.split('\n').filter((line) => line.trim() !== ''); for (const line of lines) { try { const parsed = parseStreamPart(line); if (parsed.type === 'text') { controller.enqueue(encoder.encode(parsed.value)); } } catch (e) { // skip invalid JSON lines console.warn('Failed to parse stream part:', line, e); } } }, }); const transformedStream = result.toDataStream().pipeThrough(transformStream); return new StreamingTextResponse(transformedStream); } catch (error: unknown) { console.log(error); if (error instanceof Error && error.message?.includes('API key')) { throw new Response('Invalid or missing API key', { status: 401, statusText: 'Unauthorized', }); } throw new Response(null, { status: 500, statusText: 'Internal Server Error', }); } }