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voxwright

Offline voice-agent application layer: session core with byte-deterministic replay, spoken-LLM adapters (scripted/replay/loopback-mock), injection-safe function-call grammar, slot grounding, workflow engine with compensation and resume, permissioned tool sandbox, repair-dialog policies, task-success and latency evaluation. NumPy core, torch extra.

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GITHUB · launched Oct 30, 2026 · 31 upvotes (top 41%) · 0 views

Niche: ai voice agents and platforms · 197 launches, 20 in the last 7 days ▲ +25% · Explore this niche →

Category and tags

  • Horizontal
  • Agent / copilot
  • Developer
  • AI-native
  • Hobby / open-source project
  • dialog-system
  • evaluation
  • function-calling
  • numpy
  • offline-first
  • prompt-injection
  • +6 more

Visit website ↗ Source listing ↗

Could you build this?

Partial The session core, workflow engine, function-call grammar, and evaluation harness are substantial but standard software engineering that AI assistance can help write. Real-time spoken-LLM performance, however, depends on audio and latency work that needs domain experience and real speech data.

What it would actually take: Build it as a Python library (NumPy core, optional PyTorch) with deterministic event logs, pluggable ASR/TTS/LLM adapters, a sandboxed tool runner, and a workflow state machine with compensations. The hard parts are latency-tuned streaming audio and evaluation on realistic speech data, which need speech and dialogue specialists.

Competitors

Other products that read as similar to this one : 324 launches clear the similarity bar, closest 8 shown.

Attention rank: #130 of 325 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 358 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.