f893530471
🎯 Major improvements to MissionControl component: - Always keep input field visible and functional after AI responses - Auto-clear input after submitting questions for better UX - Add dynamic visual indicators (first question vs follow-up) - Improve response layout with clear separation and hints - Enable proper chat-like experience for continuous learning 🌟 Additional enhancements: - Better language-specific messaging throughout interface - Clearer visual hierarchy between input and response areas - Intuitive flow that guides users to ask follow-up questions - Maintains responsive design and accessibility 🔧 Technical changes: - Enhanced MissionControl state management - Improved component layout and styling - Better TypeScript integration across components - Updated tsconfig for stricter type checking
79 lines
3.4 KiB
JavaScript
79 lines
3.4 KiB
JavaScript
"use strict";
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// File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
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if (k2 === undefined) k2 = k;
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var desc = Object.getOwnPropertyDescriptor(m, k);
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if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
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desc = { enumerable: true, get: function() { return m[k]; } };
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}
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Object.defineProperty(o, k2, desc);
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}) : (function(o, m, k, k2) {
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if (k2 === undefined) k2 = k;
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o[k2] = m[k];
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}));
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var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
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Object.defineProperty(o, "default", { enumerable: true, value: v });
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}) : function(o, v) {
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o["default"] = v;
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});
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var __importStar = (this && this.__importStar) || function (mod) {
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if (mod && mod.__esModule) return mod;
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var result = {};
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if (mod != null) for (var k in mod) if (k !== "default" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);
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__setModuleDefault(result, mod);
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return result;
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};
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.Embeddings = void 0;
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const resource_1 = require("../resource.js");
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const Core = __importStar(require("../core.js"));
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class Embeddings extends resource_1.APIResource {
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/**
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* Creates an embedding vector representing the input text.
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*
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* @example
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* ```ts
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* const createEmbeddingResponse =
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* await client.embeddings.create({
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* input: 'The quick brown fox jumped over the lazy dog',
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* model: 'text-embedding-3-small',
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* });
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* ```
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*/
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create(body, options) {
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const hasUserProvidedEncodingFormat = !!body.encoding_format;
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// No encoding_format specified, defaulting to base64 for performance reasons
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// See https://github.com/openai/openai-node/pull/1312
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let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
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if (hasUserProvidedEncodingFormat) {
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Core.debug('Request', 'User defined encoding_format:', body.encoding_format);
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}
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const response = this._client.post('/embeddings', {
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body: {
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...body,
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encoding_format: encoding_format,
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},
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...options,
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});
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// if the user specified an encoding_format, return the response as-is
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if (hasUserProvidedEncodingFormat) {
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return response;
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}
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// in this stage, we are sure the user did not specify an encoding_format
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// and we defaulted to base64 for performance reasons
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// we are sure then that the response is base64 encoded, let's decode it
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// the returned result will be a float32 array since this is OpenAI API's default encoding
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Core.debug('response', 'Decoding base64 embeddings to float32 array');
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return response._thenUnwrap((response) => {
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if (response && response.data) {
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response.data.forEach((embeddingBase64Obj) => {
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const embeddingBase64Str = embeddingBase64Obj.embedding;
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embeddingBase64Obj.embedding = Core.toFloat32Array(embeddingBase64Str);
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});
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}
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return response;
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});
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}
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}
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exports.Embeddings = Embeddings;
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//# sourceMappingURL=embeddings.js.map
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