File size: 1,591 Bytes
9db8ced a1afcb6 9db8ced a1afcb6 9db8ced |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
import { buildPrompt } from "$lib/buildPrompt";
import { textGenerationStream } from "@huggingface/inference";
import { z } from "zod";
import type { Endpoint } from "../endpoints";
export const endpointAwsParametersSchema = z.object({
weight: z.number().int().positive().default(1),
model: z.any(),
type: z.literal("aws"),
url: z.string().url(),
accessKey: z.string().min(1),
secretKey: z.string().min(1),
sessionToken: z.string().optional(),
service: z.union([z.literal("sagemaker"), z.literal("lambda")]).default("sagemaker"),
region: z.string().optional(),
});
export async function endpointAws(
input: z.input<typeof endpointAwsParametersSchema>
): Promise<Endpoint> {
let AwsClient;
try {
AwsClient = (await import("aws4fetch")).AwsClient;
} catch (e) {
throw new Error("Failed to import aws4fetch");
}
const { url, accessKey, secretKey, sessionToken, model, region, service } =
endpointAwsParametersSchema.parse(input);
const aws = new AwsClient({
accessKeyId: accessKey,
secretAccessKey: secretKey,
sessionToken,
service,
region,
});
return async ({ conversation }) => {
const prompt = await buildPrompt({
messages: conversation.messages,
webSearch: conversation.messages[conversation.messages.length - 1].webSearch,
preprompt: conversation.preprompt,
model,
});
return textGenerationStream(
{
parameters: { ...model.parameters, return_full_text: false },
model: url,
inputs: prompt,
},
{
use_cache: false,
fetch: aws.fetch.bind(aws) as typeof fetch,
}
);
};
}
export default endpointAws;
|