Hello everyone!
While looking at how we handle raw audio inputs on edge hardware, I realized we have a potential vulnerability. Right now, if a user accidentally submits a recording of pure fireground noise (like loud sirens or engine rumble), the system still sends that degraded transcript to the local LLM.
This wastes critical GPU/CPU compute time on the station tablets and forces the AI to try and "hallucinate" data just to fill out the blank schema.
Proposed Solution:
I propose adding an "Intake Triage Gate" right before the Semantic Router. This would be a super lightweight, quantitative pre-check:
- Check Data Sufficiency: Run a fast Python check on the transcript for a minimum word count or basic valid keyword threshold.
- Halt Execution: If the transcript is just background noise, we stop the pipeline instantly before hitting the expensive LLM inference.
- Actionable Error: Return a clean
HTTP 400 so the frontend can immediately tell the user: *"Audio heavily degraded. Please re-record."
This is a core piece of the "Zero-Trust" architecture I outlined in my GSoC proposal to protect local hardware resources. I'd love to put together a quick PR for this pre-compute guardrail if the team thinks it's a good fit!
Hello everyone!
While looking at how we handle raw audio inputs on edge hardware, I realized we have a potential vulnerability. Right now, if a user accidentally submits a recording of pure fireground noise (like loud sirens or engine rumble), the system still sends that degraded transcript to the local LLM.
This wastes critical GPU/CPU compute time on the station tablets and forces the AI to try and "hallucinate" data just to fill out the blank schema.
Proposed Solution:
I propose adding an "Intake Triage Gate" right before the Semantic Router. This would be a super lightweight, quantitative pre-check:
HTTP 400so the frontend can immediately tell the user: *"Audio heavily degraded. Please re-record."This is a core piece of the "Zero-Trust" architecture I outlined in my GSoC proposal to protect local hardware resources. I'd love to put together a quick PR for this pre-compute guardrail if the team thinks it's a good fit!