This README provides a guide to setup and run the ITM application.
- Simplify API error code responses
Ensure you have Python 3.10 installed on your system. If you don't have it installed, you can download it from the official Python website.
- First, we need to setup a Python virtual environment. Navigate to the directory where you cloned the repository and run the following command to create a new virtual environment:
python3.10 -m venv venv
- Activate the newly created virtual environment with:
source venv/bin/activate
Once you're in the virtual environment, you're ready to install the necessary Python packages for the project. From the itm_server directory, run:
pip install -r requirements.txt
After the installation is complete, you can start the server. From the itm_server directory, start the server by running:
python3 -m swagger_server
To interact with the server, you will need to run a client. Please ensure that the server is running before you start a client. To see additional details regarding modifying this minimal runner to be a TA2 client, see the comments at the top of itm_minimal_runner.py. To run it, open a new terminal, activate your virtual environment and inside the itm_client directory run itm_minimal_runner.py:
usage: itm_minimal_runner.py [-h] --adm_name ADM_NAME [--session [session_type [scenario_count ...]]] [--eval]
Runs ADM scenarios.
options:
-h, --help show this help message and exit
--adm_name ADM_NAME Specify the ADM name
--session [session_type [scenario_count ...]]
Specify session type and scenario count. Session type can be test, adept, or soartech. If you want to run through all available scenarios without repeating do not use the scenario_count argument
--eval Run an evaluation session. Supercedes --session and is the default if nothing is specified. Implies --db.
To interact with the server, you will need to run a client. Please ensure that the server is running before you start a client. Open a new terminal, activate your virtual environment and inside the itm_client directory run itm_human_input.py:
usage: itm_human_input.py [-h] [--db] [--session [session_type [scenario_count ...]]] [--eval]
Runs Human input simulator.
options:
-h, --help show this help message and exit
--db Put the output in the MongoDB (ensure that the itm_dashboard docker container is running) and save a json output file locally inside itm_server/itm_mvp_local_output/
--session [session_type [scenario_count ...]]
Specify session type and scenario count. Session type can be test, adept, or soartech. If you want to run through all available scenarios without repeating do not use the scenario_count argument
--eval Run an evaluation session. Supercedes --session and is the default if nothing is specified. Implies --db.
If you've followed these steps, you should now have the ITM server and at least one client running.