Hi everyone, I'm building a specialized voice assistant using **Pipecat Flows v0.0.22** and running into a frustrating issue with phone number collection that I can't seem to solve. ### The Stack - **Framework:** Pipecat Flows v0.0.22 (Python) - **STT:** Deepgram Nova-3 (Polish `pl`) - **TTS:** Cartesia (Polish voice) - **Transport:** Local WebRTC (browser-based, no telephony yet) ### The Problem When I dictate a 9-digit Polish phone number (e.g., "690807057"), the assistant receives partial fragments and processes them individually instead of waiting for the full number. For example, if I say "690... 807... 055" (with natural pauses), the bot splits it into: 1. "6" -> sent to LLM -> LLM complains "Received only 1 digit" 2. "980" -> sent to LLM -> LLM complains 3. "5" ... and so on. ### What I Have Tried I've gone through the documentation and tried several fixes, but the "defragmentation" issue persists. 1. **Deepgram Configuration (Current Setup):** I've configured the `LiveOptions` to handle phone numbers and utterance endings explicitly: ```python options = LiveOptions( model="nova-3", language="pl", smart_format=True, # Enabled numerals=True, # Enabled utterance_end_ms=1000, # Set to 1000ms to force waiting interim_results=True # Required for utterance_end_ms ) ``` *Result:* Even with `utterance_end_ms=1000`, Deepgram seems to finalize the results too early during the digit pauses. 2. **VAD Tuning:** - I tried increasing Pipecat's VAD `stop_secs` to `2.0s`. - *Result:* This caused massive latency (2s delay on every response) and didn't solve the valid STT fragmentation (Deepgram still finalized early). I've reverted to `0.5s` (and `0.2s` for barge-in) as `stop_secs=2.0s` is considered an anti-pattern for conversational flows. 3. **Prompt Engineering (Aggressive):** - I instructed the LLM to "call the function IMMEDIATELY with whatever fragments you have". - *Result:* This led to early failures where the LLM would call `capture_phone("6")`, which would fail validation (requires 9 digits), causing the bot to reject the input before the user finished speaking.

I mean a system where one can do 10k calls per day. Has anyone built a system like this using livekit and pipecat. did you do it without using our own GPUs ?

Hello, I'm ahmet. I just joined the community. I had a few experiences for open source ai voice, but I didn't get the result I wanted. First of all, I turned to open source tts - stt models. They are not enough for Turkish at the moment (I serve in Turkey). I guess I will have to train myself. Some of the big companies I talked to have attempted this, but they haven't gotten much results yet. Do you have any advice? Sincerely Thank you.

Hey everyone, Thank you so much for your patience while we got this community ready to launch. It’s finally happening! 🎉 I’ve put together a short video explaining why I started this group and what it’s all about. I’m really excited to meet all of you — passionate, like-minded people working in the voice AI space. Our first meetup is next Friday, and it’ll be all about getting to know each other, hearing about your voice AI projects, and understanding what you’d like to learn on here. In the meantime, let’s start with introductions right here under this post 👇 Please share: - Who you are - What you’re building or working on - What you’d love to learn or explore within this community Can’t wait to see what everyone’s up to!

About a month and a half ago, I pivoted from being a generalist to focusing exclusively on dental practices. Results? Couldn’t be better. 💰 Instant 4-figure MRR 🔗 Exclusive software integrations 🧾 Clients waiting in line 🎯 Recognized as an industry expert 💸 Investor interest and funding opportunities already on the table A lot of founders have already figured out the business use cases — but still struggle with the tech side. That’s where I and my code come in to help. Core features of the platform I’ve built: 🗣️ AI Voice Agent — powered by Vapi & LiveKit ⚙️ AI Voice Agent Configurations — prompt, models, knowledgebase, etc. 📞 Call Logs 🔐 Sign in / Sign up — Google Authentication included 💳 Payment Collection via Stripe 🏢 Multi-Tenant Architecture — one user can be associated with multiple organizations If you’re interested in building your own AI voice agent platform, comment or DM me. 🌐 Check out the website: https://dentai.ai/