Most meeting note-takers are either bloated or overpriced. Plus, the VPS hosting the @gobitsnbytes bot has 512MB RAM and 1 vCPU.
So we built our own transcriber using @GeminiApp@Google@GoogleDeepMind Gemini 3.5 Flash. Here is how we got it running on a micro-server: (1/8)
Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.
Its capabilities exceed those of any model we’ve ever made generally available.
Genuine question for @OlaElectric:
If an Ola S1 Air parked for ~2 weeks can go into “deep discharge” and need an ₹80k battery, with no warranty support, what does your 8‑year battery warranty actually protect?
Our scooter (UP70GX4881) is dead at ~4,000 km.
we've no foundational model that can compete with the latest from us and china, whatever we've compares to their 2024-2025 model that too in indic language 🥀
Most meeting note-takers are either bloated or overpriced. Plus, the VPS hosting the @gobitsnbytes bot has 512MB RAM and 1 vCPU.
So we built our own transcriber using @GeminiApp@Google@GoogleDeepMind Gemini 3.5 Flash. Here is how we got it running on a micro-server: (1/8)
The code is live, pushed to main, and passing all 181 unit tests.
Turns out you don't need expensive SaaS integrations if you leverage basic streams, local FFmpeg, and cloud-side models. (8/8)
We don't keep any audio. Everything is deleted post-processing.
Transcripts are stored in SQLite. Attendees can retrieve them anytime using /meet-transcript, but the access control is tight—you can only pull meetings you actually attended. (7/8)
The merged audio goes to Google's File API, and Gemini 3.5 Flash generates a structured JSON output (summary, key decisions, action items).
The bot then DMs every attendee the notes and attaches the full transcript as a .txt file. (6/8)
Once the voice channel is empty, the bot leaves.
A local FFmpeg process merges the per-user files using their join/leave timestamps as offsets to keep the conversation in sync. We run this in a sequential queue so the 1 vCPU doesn't choke. (5/8)
Since we speak a mix of English, Hindi, and Hinglish, we prompt Gemini to transcribe in whatever language is spoken, but summarize in English.
We also added a quick /hindi text command in the VC chat to trigger the Hindi voice notice on demand. (4/8)