Introduction

The walkthrough video is available at https://youtu.be/-JMWR9-lR78

Model

Fine-tuning BART

Run the script in src/run_summarization.py.

Baseline: iTAPE

Please refer to the original repository.

Evaluation

Human Evaluation

1. Sample 30 issues

• The sampled file for evaluation.
• The sampled ground truth file.

2. Analyze the result Run the script in src/analyze_human_eval.py.

iTiger Installation

Pre-requisites:

1. Clone the project at <path_to_directory>
2. Download model from here.
3. Extract and put the model folder under <path_to_directory>/iTiger (same level as src)

Usage

iTiger Backend:

1. Build the image:

   docker build -t itiger .

2. Start a container:

   docker run --name itiger-svc -p 8000:8000 -v <path_to_directory>/iTiger:/app -itd itiger

3. (Optional) Publish local endpoint using ngrok to serve multiple client:

   docker run --rm -it --link itiger-svc wernight/ngrok ngrok http -region=eu itiger-svc:8000

iTiger UI

3. Install Tampermonkey on Chrome / Opera / Safari

4. Add GithubIssueTItleRecommender.user.js to Tampermonkey extension

   (WARNING: you need to adjust the base_url variable in the script, setting it to your deployed server's endpoint)

   If iTiger's backend is deployed in your local machine, change the base_url to localhost:8000.

   Otherwise, use the ngrok host as base_url.