UNPKG

@huggingface/inference

Version:

Typescript client for the Hugging Face Inference Providers and Inference Endpoints

45 lines (44 loc) 1.87 kB
"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); exports.FeatherlessAITextGenerationTask = exports.FeatherlessAIConversationalTask = void 0; const providerHelper_js_1 = require("./providerHelper.js"); const omit_js_1 = require("../utils/omit.js"); const errors_js_1 = require("../errors.js"); const FEATHERLESS_API_BASE_URL = "https://api.featherless.ai"; class FeatherlessAIConversationalTask extends providerHelper_js_1.BaseConversationalTask { constructor() { super("featherless-ai", FEATHERLESS_API_BASE_URL); } } exports.FeatherlessAIConversationalTask = FeatherlessAIConversationalTask; class FeatherlessAITextGenerationTask extends providerHelper_js_1.BaseTextGenerationTask { constructor() { super("featherless-ai", FEATHERLESS_API_BASE_URL); } preparePayload(params) { return { model: params.model, ...(0, omit_js_1.omit)(params.args, ["inputs", "parameters"]), ...(params.args.parameters ? { max_tokens: params.args.parameters.max_new_tokens, ...(0, omit_js_1.omit)(params.args.parameters, "max_new_tokens"), } : undefined), prompt: params.args.inputs, }; } async getResponse(response) { if (typeof response === "object" && "choices" in response && Array.isArray(response?.choices) && typeof response?.model === "string") { const completion = response.choices[0]; return { generated_text: completion.text, }; } throw new errors_js_1.InferenceClientProviderOutputError("Received malformed response from Featherless AI text generation API"); } } exports.FeatherlessAITextGenerationTask = FeatherlessAITextGenerationTask;