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import { get } from "svelte/store";
import { OPENAI_API_KEY, HF_ENDPOINT } from "$lib/store";
import { Configuration, OpenAIApi } from "openai";
import { getInference } from "./getInference";
import type { LLM } from "$lib/types";
import type { TextGenerationOutput } from "@huggingface/inference";
async function OpenAILLMCall(prompt: string) {
const openai = new OpenAIApi(
new Configuration({ apiKey: get(OPENAI_API_KEY) })
);
const textAnswer =
(
await openai.createCompletion({
model: "text-davinci-003",
prompt: prompt,
max_tokens: 1000,
})
).data.choices[0].text ?? "";
return textAnswer;
}
async function HFLLMCall(prompt: string) {
const formattedPrompt = "<|user|>" + prompt + "<|end|><|assistant|>";
let output: TextGenerationOutput;
if (!!get(HF_ENDPOINT)) {
output = await getInference()
.endpoint(get(HF_ENDPOINT))
.textGeneration({
inputs: formattedPrompt,
parameters: {
max_new_tokens: 1400,
},
});
} else {
output = await getInference().textGeneration({
inputs: formattedPrompt,
model: "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
parameters: {
max_new_tokens: 900,
},
});
}
const text = output.generated_text.slice(formattedPrompt.length);
return text;
}
export const OpenAILLM: LLM = {
name: "OpenAI",
call: OpenAILLMCall,
};
export const HFLLM: LLM = {
name: "Hugging Face",
call: HFLLMCall,
};
export const LLMs = [OpenAILLM, HFLLM];
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