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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" | |
}` | |
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 "" | |
} | |
} |