Custom whitelisted dependencies

By default, PandasAI only allows to run code that uses some whitelisted modules. This is to prevent malicious code from being executed on the server or locally. However, it is possible to add custom modules to the whitelist. This can be done by passing a list of modules to the custom_whitelisted_dependencies parameter when instantiating the SmartDataframe or SmartDatalake class.

from pandasai import SmartDataframe
df = SmartDataframe("data.csv", config={
    "custom_whitelisted_dependencies": ["any_module"]

The custom_whitelisted_dependencies parameter accepts a list of strings, where each string is the name of a module. The module must be installed in the environment where PandasAI is running.

Please, make sure you have installed the module in the environment where PandasAI is running. Otherwise, you will get an error when trying to run the code.