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- Created a new article on "Understanding AI Agents, LLMs, and RAG" detailing the synergy between AI agents, LLMs, and Retrieval-Augmented Generation. - Added an introductory article on "What is Machine Learning?" covering types, model selection, workflow, and evaluation metrics. chore: setup ESLint and Nuxt configuration - Added ESLint configuration for code quality. - Initialized Nuxt configuration with various modules and settings for the application. chore: initialize package.json and TypeScript configuration - Created package.json for dependency management and scripts. - Added TypeScript configuration for the project. feat: implement API endpoints for activity and stats - Developed API endpoint to fetch user activity from Lanyard. - Created a stats endpoint to retrieve Wakatime coding statistics with caching. feat: add various assets and images - Included multiple images and assets for articles and projects. - Added placeholder files to maintain directory structure. refactor: define types for chat, lanyard, time, and wakatime - Created TypeScript types for chat messages, Lanyard activities, time formatting, and Wakatime statistics.
18 lines
379 B
TypeScript
18 lines
379 B
TypeScript
import type { ChatMessage } from '~~/types'
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export const useChatStore = defineStore('chat', () => {
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const messages = ref<ChatMessage[]>([])
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let id = 0
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function addMessage(message: ChatMessage) {
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messages.value.push({ ...message, id: id++ })
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}
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function clearMessages() {
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messages.value = []
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id = 0
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}
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return { messages, addMessage, clearMessages }
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})
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