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Here is an example Pipecat project for trying PhoneLLM Alpha 1. Deploy the model to a Modal endpoint with one click. Client from the video in repo too (with all that sweet sweet terminal-ish aura.) Next up, a TTS that can pronounce Merve Tan's name correctly? 😅

Jon Taylor

1,167 subscribers

21,006 просмотров • 21 дней назад •via X (Twitter)

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Комментарии: 6

Фото профиля ata

ata21 дней назад

@bmervetan tts’e merve’yi okutabiliriz. agent kullanıcıdan yeni bir özel isim duyduğunda son audio turn’de ilgili span üzerinde phoneme extraction çalıştıracak, sonra aynı isim için sonraki tts turn’lerine phoneme override enjekte edecek. yw :)

Фото профиля Tim 🚴‍♂️ Builder

Tim 🚴‍♂️ Builder20 дней назад

@bmervetan Für mich ist das Repo fast wichtiger als der Model-Launch: Client plus Deploy-Pfad schaffen erst die Basis für faire Vergleiche. Als Nächstes würde ich ein deutsches Eval-Set für Unterbrechungen, Tool Calls und Namen bauen. Dort zeigt sich, wie alltagstauglich Voice Agents sind.

Фото профиля yian

yian21 дней назад

@bmervetan I tried this model and it didn't know what tomorrow was, (thought today was Thursday, tomorrow was Saturday)

Фото профиля Scott Thomas

Scott Thomas21 дней назад

@bmervetan hi I'm actively building a voice sales agent. I tried phonellm through live kit and it could not tool call very well. Any suggestions? Willing to also give pipecat a try

Фото профиля LukeHalley

LukeHalley21 дней назад

@bmervetan I'm thinking of doing this for our platform - trying to handle bursty traffic without running a GPU 24/7. We currently use API endpoints to keep costs down, as we don't need 24/7 inference, but we'd love this low latency. Any words of wisdom?

Фото профиля Ahmed Omar.

Ahmed Omar.21 дней назад

@bmervetan Jon we'd love to partner. please dm

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