A Python library providing lightweight models designed for analyzing WebRTC statistics. It helps estimate quality of experience, predict network congestion, and perform other related tasks using simple prediction models. Currently at version 0.3.0, it follows a feature-driven release cadence, with updates for new models or API refinements.
pip install webrtc-modelsVerified import paths — ran on the pinned version, not inferred.
Demonstrates how to import a model, initialize it, provide input features as a dictionary, and get a prediction.
Update calls to `predict` to pass a single dictionary of features instead of individual keyword arguments. For example, change `predictor.predict(arg1=val1, arg2=val2)` to `predictor.predict({'arg1': val1, 'arg2': val2})`.Refer to the model's documentation or the library's source code for the exact feature keys required (e.g., `inbound_rtp_packets_lost`, `inbound_rtp_packets_received` for `PacketLossPredictor`).
Ensure your environment is running Python 3.12.0 or higher. Use `python --version` to check and upgrade if necessary, or activate a suitable virtual environment.
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