Hi All, So, as I've told you all a few weeks ago, I've published an open source tool called OPBX - which is a business PBX system, that works on top of Cloudonix and provides some interesting capabilities when working with voice agents. I've added multi-tenant capabilities to it - so if you install it, you can use it to service all your customers. At the same time, I'll be launching a SaaS version of OPBX, completely FREE of charge, so that you can use it and build with it. Next week, I'll be holding a special OPBX training session, showing how to integrate OPBX with VAPI, Retell, etc. In addition, I'll show how to build multi-agent IVR trees, warm transfers that work as they should and more. Cloudonix Velocity Training Registration - https://us02web.zoom.us/meeting/register/6D63tRaYSDihkJtUlpNp-A#/registration OPBX Github Repository - https://github.com/greenfieldtech-nirs/opbx Looking forward to seeing you all. Nir S

Hello devs, Is there any pay as you go plan in livekit for agent deployment in there cloud.

Got my adventure with LiveKit underway last week. After testing @John George 's demo, my demo felt underwhelming. I tried the Gemini Live API but my agent still felt sluggish and the data supported that. I tried switching out different TTS provides and voices the day before so yesterday, I focused on LLMs. I found Llama 4 Scout, installed with the Groq API. Admittedly, I only made one call but what a difference! A lot more testing to do, but finally, there hope on the horizon. Latency is such a killer. (those Cal.com tool calls still take forever). Anyone any thoughts on this Llama 4 Scout?

I built a voice AI assistant for my website using Pipecat and Gemini's native audio model. People kept calling it trying to reverse-engineer how it works, so I just open-sourced the whole thing. It's a good starting point if you want to build your own web-based voice AI demo with low latency and multilingual support. Repo: https://github.com/askjohngeorge/askjg-demo-gemini-pcc System prompt: https://github.com/askjohngeorge/askjg-demo-gemini-pcc/blob/main/bot/prompts/demo_system_prompt.md You can try the live demo at https://askjohngeorge.com/demo (click the mic). Happy to answer questions if you have any.

While wrappers are great for MVPs, building your own orchestration layer gives you 𝗳𝘂𝗹𝗹 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽, 𝘀𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝘁𝗹𝘆 𝗹𝗼𝘄𝗲𝗿 𝗰𝗼𝘀𝘁𝘀, 𝗮𝗻𝗱 𝗴𝗿𝗮𝗻𝘂𝗹𝗮𝗿 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 over the entire conversational pipeline. I designed this engine to fully replace third-party wrappers like Vapi & Retell AI. Here is a deep dive into what’s under the hood: 🔄 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗔𝗴𝗲𝗻𝘁 𝗖𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 (𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗛𝘆𝗱𝗿𝗮𝘁𝗶𝗼𝗻) Hardcoding agents is a trap. I implemented a system that executes an API call upon call initialization. • 𝗛𝗼𝘁-𝗦𝘄𝗮𝗽𝗽𝗮𝗯𝗹𝗲 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝘀: A single engine instance can instantly apply unique System Prompts, Voice IDs, and Temperature settings based on backend parameters. • 𝗥𝗲𝘀𝘂𝗹𝘁: You can power thousands of unique agents (e.g., specific to different businesses) without ever redeploying the core code or creating a new instance. 🛠️ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁-𝗔𝘄𝗮𝗿𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝗥𝗼𝘂𝘁𝗲𝗿 When building raw infrastructure, manually mapping tools to agents is a major architectural hassle. I built specialized helper logic for 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗧𝗼𝗼𝗹 𝗜𝗻𝗷𝗲𝗰𝘁𝗶𝗼𝗻 to solve this. • 𝗠𝗼𝗱𝘂𝗹𝗮𝗿 𝗟𝗼𝗴𝗶𝗰: The router decouples the orchestration engine from business logic. It parses the backend setup and assigns only the specific tools defined in that agent's configuration (e.g., loading "Appointment Booking" tools only when the specific use-case demands it). 💾 𝗗𝗮𝘁𝗮 𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝗲 & 𝗣𝗼𝘀𝘁-𝗖𝗮𝗹𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Logs aren't enough. I built a save_conversation function that aggregates the full session payload and triggers intelligent sub-functions immediately after the call: • 𝗖𝗮𝗹𝗹 𝗦𝘂𝗺𝗺𝗮𝗿𝘆: Generates a natural language recap via LLM. • 𝗖𝗮𝗹𝗹 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻: Structurally classifies the outcome (e.g., "Booked", "Inquiry", "Failed"). • 𝗧𝗲𝗹𝗲𝗺𝗲𝘁𝗿𝘆: Captures precise Token Usage (for billing) and Latency statistics alongside the transcript. 🛡️ 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗚𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 To prevent runaway costs and "zombie" connections, I engineered active background monitors: • 𝗜𝗻𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗠𝗼𝗻𝗶𝘁𝗼𝗿: Detects silence (30s default) and gracefully terminates the session.