found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
Low-latency audio decisions POC
Private TypeScript proof of concept that flags Spanish profanity with Jev Boolean and Score questions and replaces the matching word intervals with a beep via ffmpeg, keeping the original duration.
- Category
- Tools & Integrations
- Published by
- Community
- Author
- santos-sanz
- Added
- 2026-09-22
Tagscommunitytypescriptmoderationguardrailsaudio
Highlights
- Each word is evaluated in its local context with two typed questions: isInsult (Boolean) and severity (Score with four ordered levels).
- The pipeline goes ASR timestamps to parallel Jev evaluations, threshold padding and merging, then an ffmpeg beep overlay.
- The ASR provider is a seam for streaming; the README sketches a live version with a 300-600 ms PCM ring buffer.
- The default 0.72 threshold is explicitly a POC starting point, not a claim of production calibration.
- Uses the official @ai-sdk/typesafe-ai provider with the System One endpoint and jev-latest, overridable with JEV_MODEL.
Quickstart
bash
npm install
export TYPESAFE_AI_API_KEY='YOUR_API_KEY'
npm run check
npm run demoWatch out
No license file, so reuse terms are unclear. Needs Node.js 22+, ffmpeg on PATH and a TypeSafe API key; audio and transcript text are sent to providers, and the demo relies on a word-timestamp sidecar.
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From the community
Posts from builders shipping with Jev right now.
Instant compaction with Jev
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found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
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