Python implementation of WebRTC and ORTC for real-time peer-to-peer communication
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{
"context": "This evaluation assesses how effectively the engineer uses the aiortc package to implement audio level computation, specifically leveraging its audio processing utilities that convert RMS values to dBov format as used in WebRTC audio streams.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Package integration",
"description": "Correctly imports and uses aiortc package or its utility modules (e.g., from aiortc import ..., from aiortc.utils import ...) for audio level computation",
"max_score": 20
},
{
"name": "RMS computation",
"description": "Implements or uses correct RMS (Root Mean Square) calculation from audio samples using the formula: sqrt(sum(sample^2) / count), leveraging aiortc's audio processing approach",
"max_score": 25
},
{
"name": "dBov conversion formula",
"description": "Applies the correct dBov conversion formula: 20 * log10(rms), matching aiortc's audio level computation standard for WebRTC",
"max_score": 30
},
{
"name": "Silent audio handling",
"description": "Properly handles edge case where RMS is zero (silent audio) by returning -127.0 dBov, consistent with aiortc's minimum audio level representation",
"max_score": 15
},
{
"name": "Correct value range",
"description": "Returns audio levels in the correct dBov range (-127.0 to 0.0), where 0.0 represents maximum signal level (no attenuation) and negative values represent lower levels",
"max_score": 10
}
]
}Install with Tessl CLI
npx tessl i tessl/pypi-aiortcdocs
evals
scenario-1
scenario-2
scenario-3
scenario-4
scenario-5
scenario-6
scenario-7
scenario-8
scenario-9
scenario-10