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"use server"
import type { ChatCompletionMessageParam } from "openai/resources/chat"
import OpenAI from "openai"
import { LLMPredictionFunctionParams } from "@/types"
export async function predict({
systemPrompt,
userPrompt,
nbMaxNewTokens,
llmVendorConfig
}: LLMPredictionFunctionParams): Promise<string> {
const openaiApiKey = `${
llmVendorConfig.apiKey ||
process.env.AUTH_OPENAI_API_KEY ||
""
}`
const openaiApiModel = `${
llmVendorConfig.modelId ||
process.env.LLM_OPENAI_API_MODEL ||
"gpt-4-turbo"
}`
if (!openaiApiKey) { throw new Error(`cannot call OpenAI without an API key`) }
const openaiApiBaseUrl = `${process.env.LLM_OPENAI_API_BASE_URL || "https://api.openai.com/v1"}`
const openai = new OpenAI({
apiKey: openaiApiKey,
baseURL: openaiApiBaseUrl,
})
const messages: ChatCompletionMessageParam[] = [
{ role: "system", content: systemPrompt },
{ role: "user", content: userPrompt },
]
try {
const res = await openai.chat.completions.create({
messages: messages,
stream: false,
model: openaiApiModel,
temperature: 0.8,
max_tokens: nbMaxNewTokens,
// TODO: use the nbPanels to define a max token limit
})
return res.choices[0].message.content || ""
} catch (err) {
console.error(`error during generation: ${err}`)
return ""
}
} |