102 lines
3.6 KiB
TypeScript
102 lines
3.6 KiB
TypeScript
'use server';
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import { OpenAI, AzureOpenAI } from 'openai';
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import { generateObject } from 'ai';
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import { createOpenAI as createGroq } from '@ai-sdk/openai';
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import { z } from 'zod';
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const groq = createGroq({
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baseURL: 'https://api.groq.com/openai/v1',
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apiKey: process.env.GROQ_API_KEY,
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});
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export async function suggestQuestions(history: any[]) {
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'use server';
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const { object } = await generateObject({
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model: groq('llama-3.1-70b-versatile'),
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temperature: 0,
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system:
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`You are a search engine query generator. You 'have' to create only '3' questions for the search engine based on the message history which has been provided to you.
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The questions should be open-ended and should encourage further discussion while maintaining the whole context. Limit it to 5-10 words per question.
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Always put the user input's context is some way so that the next search knows what to search for exactly.
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Try to stick to the context of the conversation and avoid asking questions that are too general or too specific.
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For weather based converations sent to you, always generate questions that are about news, sports, or other topics that are not related to the weather.
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For programming based conversations, always generate questions that are about the algorithms, data structures, or other topics that are related to it or an improvement of the question.
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For location based conversations, always generate questions that are about the culture, history, or other topics that are related to the location.
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For the translation based conversations, always generate questions that may continue the conversation or ask for more information or translations.
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Never use pronouns in the questions as they blur the context.`,
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messages: history,
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schema: z.object({
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questions: z.array(z.string()).describe('The generated questions based on the message history.')
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}),
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});
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return {
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questions: object.questions
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};
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}
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export async function generateSpeech(text: string, voice: 'alloy' | 'echo' | 'fable' | 'onyx' | 'nova' | 'shimmer' = "alloy") {
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if (process.env.OPENAI_PROVIDER === 'azure') {
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if (!process.env.AZURE_OPENAI_API_KEY || !process.env.AZURE_OPENAI_API_URL) {
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throw new Error('Azure OpenAI API key and URL are required.');
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}
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const url = process.env.AZURE_OPENAI_API_URL!;
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const response = await fetch(url, {
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method: 'POST',
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headers: {
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'api-key': process.env.AZURE_OPENAI_API_KEY!,
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({
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model: "tts",
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input: text,
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voice: voice
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})
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});
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if (!response.ok) {
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throw new Error(`Failed to generate speech: ${response.statusText}`);
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}
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const arrayBuffer = await response.arrayBuffer();
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const base64Audio = Buffer.from(arrayBuffer).toString('base64');
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return {
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audio: `data:audio/mp3;base64,${base64Audio}`,
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};
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} else if (process.env.OPENAI_PROVIDER === 'openai') {
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const openai = new OpenAI();
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const response = await openai.audio.speech.create({
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model: "tts-1",
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voice: voice,
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input: text,
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});
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const arrayBuffer = await response.arrayBuffer();
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const base64Audio = Buffer.from(arrayBuffer).toString('base64');
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return {
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audio: `data:audio/mp3;base64,${base64Audio}`,
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};
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} else {
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const openai = new OpenAI();
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const response = await openai.audio.speech.create({
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model: "tts-1",
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voice: voice,
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input: text,
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});
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const arrayBuffer = await response.arrayBuffer();
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const base64Audio = Buffer.from(arrayBuffer).toString('base64');
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return {
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audio: `data:audio/mp3;base64,${base64Audio}`,
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};
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}
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} |