SShortSingh.
Back to feed

Developer Connects AI Desktop Pet Michelle to Telegram for Remote Access

0
·1 views

A developer has extended Michelle, an Electron-based AI desktop companion powered by the Claude API, to be accessible via Telegram on a mobile phone. The integration was inspired by a moment at an AI creator meetup where the developer wanted to consult Michelle on the spot but could not. The setup uses Telegram's polling mechanism, requiring no port forwarding, while the AI's core logic continues to run on the developer's personal PC. A single-user access control ensures only the registered owner can interact with the bot. The developer plans to move Michelle's backend to a cloud server for always-on availability and enable task execution and approval prompts through Telegram.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer launches Porfilr, a no-code portfolio builder for devs at $19 one-time fee

A developer has launched Porfilr, a no-code portfolio builder designed to help developers create and publish a professional portfolio in around 10 minutes. The tool allows users to add projects, link their GitHub, and generate a single shareable URL suitable for job applications and recruiter outreach. Porfilr is free to start, with a Pro tier available for a one-time payment of $19. The platform is built on React, Vite, Vercel serverless functions, Supabase, and Resend, and is live at porfilr.com. The creator is actively seeking feedback from the developer community to guide future improvements.

0
ProgrammingDEV Community ·

Why Payment APIs Must Implement Idempotency From Day One

Idempotency ensures that a payment API processes a request exactly once, even if the client sends it multiple times due to network failures or timeouts. Without it, retried requests can result in duplicate charges, triggering compliance issues and customer disputes. The standard approach requires clients to generate a unique UUID key per request, which the server stores alongside the response and reuses on repeat submissions. Experts recommend pairing the key with the user ID and operation type to prevent accidental cross-user deduplication. The idempotency store must guarantee durability and atomicity — a simple Redis cache with default eviction settings is insufficient for this purpose.

0
ProgrammingDEV Community ·

Bifrost Gateway Offers Unified Control Layer for Multi-Provider Enterprise AI Traffic

Bifrost is an LLM gateway designed to help enterprises manage multiple AI providers — including OpenAI, Anthropic, and Groq — through a single unified API endpoint. The tool handles routing, load balancing, and automatic failover across providers, so applications remain operational even when a primary provider goes down. It introduces 'Virtual Keys' as a governance mechanism, allowing organizations to set per-team budget limits, rate limits, and model access controls from one place. Security, finance, and compliance teams gain centralized visibility into AI usage and costs without requiring changes to application-level code. The gateway aims to reduce the operational complexity that arises when enterprises rely on multiple AI providers with differing APIs, authentication models, and billing structures.

0
ProgrammingDEV Community ·

New Platform Centralizes AI Interview Prep Across LLMs, RAG, and Agents

A developer has launched AI Interview Question (aiinterviewquestion.com), a dedicated platform to help candidates prepare for modern AI engineering roles. The resource addresses the growing demand for professionals skilled in areas like Retrieval-Augmented Generation, vector databases, prompt engineering, and AI agents. Unlike traditional ML interview prep, the platform covers over a dozen topics ranging from LangChain and Model Context Protocol to OpenAI APIs and computer vision. Questions are structured from beginner to advanced levels, reflecting the increasingly practical nature of today's AI job interviews. The platform targets a wide audience, including software engineers transitioning into AI, full-stack developers, students, and senior engineers pursuing AI architect positions.