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Natural Language-driven Controller Personalization Framework πŸ“£

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Mya-Mya/ChatMPC

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ChatMPC

Reproduce the Numerical Experiment

1. Download Sentence BERT Pre-trained Weights

Sentence BERT model is used in the intent extractor $f_\mathrm{int}$ in the interpreter $\mathcal{A}$. In the numerical experiment, we used deepset/sentence_bert as the pre-trained weights.

Clone it from the HuggingFace Model page.

2. Launch the IntentExtractor Python Server

Most of ChatMPC is implemented in MATLAB, but only the intent extractor $f_\mathrm{int}$ is implemented in Python. MATLAB code and the Python code communicate via HTTP.

Recall the path to the Sentence BERT folder, and execute the following:

>> cd IntentExtractor
>> python3 main.py --sbert_path <path to the Sentence BERT folder>

Check that the server is running on http://127.0.0.1:3838.

3. Work in MATLAB

The code for the numerical experiment is main.m.

Please run it SECTION BY SECTION because I'll need you to type/run some commands yourself in the middle of running.

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