LLM as Router: Intent Classification for a Local Telegram Email Agent
The article discusses the development of a local AI email agent that utilizes a three-tier routing system for intent classification. It emphasizes the importance of handling natural language commands effectively while maintaining the efficiency of explicit commands. The system aims to provide a more intuitive user experience by allowing users to interact with the agent in a conversational manner.
- ▪The AI email agent integrates various technologies including Gmail, Telegram, and SQLite.
- ▪It features a three-tier routing system that distinguishes between slash commands, direct compound commands, and natural language queries.
- ▪The router uses a local LLM to classify natural language inputs, ensuring a more user-friendly interaction.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3854341) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Sviatoslav Barbutsa Posted on Jun 3 LLM as Router: Intent Classification for a Local Telegram Email Agent #ai #programming #architecture #software Building a Private, Local AI Email Agent (3 Part Series) 1 From Inbox to Character: Building a Private, Local AI Email Agent 2 How /search and /ask Work: Local Hybrid RAG with ChromaDB + SQLite FTS5 3 LLM as Router: Intent Classification for a Local Telegram Email Agent In the first article, I showed the whole Llamail system: Gmail,…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
