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PromptSLR

Instructions to run

Backend

Run the following scripts in the backend directory:

  1. Create a conda environment using the following command:
conda create env -f env.yml

Setup Prisma

  1. Install MySQL or PostgreSQL(currently used in the project) and create a database.
  2. Modfiy the connection string on line 3 in backend/utils/schema/schema.prisma to point to your database.
  3. Run the following commands in the backend directory:
prisma db push --schema utils/schema/schema.prisma

Run the server

  1. Run the following command in the backend directory:
python app.py

It will start the server on http://localhost:8000

Testing

You can follow the UI to test the Application.

Also, you can use the following API endpoints to test the application:

  1. goto http://localhost:8000/docs to test the API endpoints.
  2. Try the /experiment/init endpoint to initialize the experiment from the Swagger UI. Sample configuration to try for random Classifier. 
    {
    "project": {
        "name": "Random RL4SE",
        "topic": {
            "title": "RL4SE"
        }
    },
    "llm": {
        "name": "random",
        "hyperparams": {
            "isTrainable": false,
            "additional": {
                "seed": 123
            }
        }
    },
    "dataset": {
        "name": "rl4se"
    },
    "configurations": {
        "features": [
            "title",
            "abstract"
        ],
        "linient": true,
        "shots": {
            "positive": 3,
            "negative": 1
        },
        "selectionCriteria": {
            "inclusion": {
                "condition": [
                    "any"
                ],
                "criteria": [
                    "Title containing Reinforcement."
                ]
            },
            "exclusion": {
                "condition": [
                    "any"
                ],
                "criteria": [
                    "Papers published before 2006"
                ]
            }
        },
        "output": {
            "classes": 2
        }
    }
}
  3. To get all the results of the experiment, try the /experiment/results endpoint. You need to provide the exp_id parameter which is the experiment id you get from the /experiment/init endpoint in the response.

Note: A sample dataset is already present in the backend/data directory. You can use it to test the application.