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Skip the OAuth & API quota trap: poll YouTube Live chat keylessly from your LAN workstation with Python's raw_decode and push instant mobile alerts via #NixOS# #Python# #SelfHosted#
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Introducing - the Agentic OS you've been waiting for. 🧩 Compose teams of specialised AI agents from plugins. No model lock-in. No vendor platform. Your infrastructure, your data. ✅ Privacy-first: sensitive data never leaves your infra in plaintext. Tokenised before every LLM call, with a verifiable receipt per round. ✅ Plugin-driven: channels, integrations, tools, sub-agents as signed ZIPs. ✅ Self-hostable: Docker Compose up and running in minutes. ✅ Built for EU operations: GDPR-aware by design, EN/DE bilingual. Public preview is live. 🌐 🔗 #OpenSource# #AI# #AIAgents# #Privacy# #SelfHosted#
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Self-hosted WhatsApp API Gateway with pluggable architecture
Self-hosted Multilogin alternative for isolated browser profiles
Self-hosted YouTube media server for archiving and playback
Maps self-hosted infrastructure by scanning networks, Zigbee, and Z-Wave devices to generate automated documentation.
🔐 Self-hosted Bob includes a Keycloak-based identity service that integrates with LDAP or Active Directory for corporate sign-in, access management, and user provisioning.
This self-hosted media player for your home server provides YouTube-like browsing of your media files in a Vue UI 🍿 -
Brings up a self-hosted wiki with LaTeX editing and offline capabilities using one Docker command.
the charm of local/self-hosted AI is to run abliterated models: Qwen-3.8-27b-abliterated 110~120 tps on ½ nvidia rtx6k (½ bc cheaper and just enough size to run it). image+text, context 230K. possibly the best hill-climbed and actually usable abliterated model on a low budget gpu. the prefilling speed is slower than RadixArk's nvfp4 as their weights and the activations are 4-bit, so every matrix multiply runs natively on Blackwell tensor cores. but this gap shrinks in practice as most of the time cost in my long-horizon tasks is on decoding. if u haven't tried any abliterated models before, you definitely need it. also comparing their reasoning chain side by side vs the regular model, the difference is huge.
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