_{AI-based interview studies...
...as smooth as butter}

boterview is a Python package that enables social science researchers to easily deploy chatbot-based interviews with customizable protocols and randomized condition assignment.

Installation

You can install the package from the PyPI repository using pip as follows:

```bash

Install using pip.

pip install boterview ```

Depending on your setup, you may consider using a Python virtual environment before running the command above. For instance, you can create a new virtual environment called .venv and activate it as follows:

```bash

Create a new directory for your study.

mkdir my-study

Move into the directory.

cd my-study

Create a new Python virtual environment called .venv.

python -m venv .venv

Activate the virtual environment.

source .venv/bin/activate ```

Development Version

You may also install the development version of the package directly from the GitHub repository using pip as follows:

```bash

Install using pip.

pip install boterview@git+https://github.com/mihaiconstantin/boterview ```

Usage

To use boterview, you need to specify a TOML configuration file for your study, and provide several text files containing the interview-related content, as well as the user interface content (e.g., the study instruction, consent information and more). While all these things can be done manually, boterview provides a command line interface (CLI) to help you with the process.

Commands

To get started, you can run the command below to see all the available command available in the boterview CLI.

```bash

Show all available commands.

boterview --help ```

Boterview provides four main command groups: generate, parse, preview, and run. For each command, please check the help message (i.e., via --help) to see the available options and arguments.

Content Generation

The boterview generate command can be used to generate various things related to your study. It contains three main subcommands:

• codes: Used to generate participation codes for your study.
• secret: Used to generate a random secret required to run the study.
• study: Used to scaffold an example study setup.

Data Parsing

The boterview parse command can be used to parse the study database. It is used to extract the study data from the sqlite database and save it as a markdown file.

Condition Previewing

The boterview preview command can be used to preview a study condition given a configuration file. This command prints to the console the content that constitutes the system prompt for the bot for a given study condition.

Running the Study

The boterview run command can be used to start a study based on a configuration file. This command starts a web server that serves the study interface and handles the chatbot interactions.

Example

Below you can find a minimal example to get you started with boterview. The commands below assume you have already installed the package.

```bash

Scaffold a study in the current working directory with 100 participation codes, and include a secret.

boterview generate study --path . --quantity 100 --config study.toml --secret

Preview the default condition setup.

boterview preview --config study.toml --condition "Condition 1"

Run the study and save the data in the boterview.db database file.

boterview run --config study.toml --database boterview.db ```

At this point, you can access the study at http://localhost:8080.

Suppose several participants have went through the study and you want to download the data. You can do so by navigating to the /download endpoint. The secret required to download the data is stored in the study.toml file (i.e., it was automatically included by the --secret flag used when scaffolding the study).

Alternatively, use the boterview parse command against the database file, which will extract the data and save it as a markdown file in the current working directory. For example:

```bash

Parse the study data.

boterview parse --config study.toml --database boterview.db ```

Note. We are working on expanding the documentation and adding more examples. For the time being, the instructions above should suffice to get you started with boterview. We also recommend reading the comments in the study configuration file, as well as the application interface default content. See the Contributing section below for more information on how you can help.

Contributing

• Any contributions are welcome and greatly appreciated. Please open a pull request on GitHub.
• To report bugs, or request new features, please open an issue on GitHub.

License

• The package source code in this repository is licensed under the MIT license.

• The documentation and other website materials by Mihai Constantin are licensed under CC BY 4.0.