Repository: gventuri/pandas-ai
File: pandasai/__init__.py (Python)

Code before:
        new_body = []

        # clear recent optional dependencies
        self._additional_dependencies = []

        for node in tree.body:
            if isinstance(node, (ast.Import, ast.ImportFrom)):
                self._check_imports(node)
                continue
            if self._is_df_overwrite(node) or self._is_jailbreak(node):
                continue
            new_body.append(node)

        new_tree = ast.Module(body=new_body)
        return astor.to_source(new_tree, pretty_source=lambda x: "".join(x)).strip()

    def _get_environment(self) -> dict:
        """
        Returns the environment for the code to be executed.

        Returns (dict): A dictionary of environment variables
        """

        return {
            "pd": pd,
            "plt": matplotlib.pyplot,
            **{
                lib["alias"]: getattr(import_dependency(lib["module"]), lib["name"])
                if hasattr(import_dependency(lib["module"]), lib["name"])
                else import_dependency(lib["module"])
                for lib in self._additional_dependencies
            },
            "__builtins__": {
                **{builtin: __builtins__[builtin] for builtin in WHITELISTED_BUILTINS},
            },
        }

    def _retry_run_code(self, code: str, e: Exception, multiple: bool = False):
        """
        A method to retry the code execution with error correction framework.

        Args:
            code (str): A python code
            e (Exception): An exception
            multiple (bool): A boolean to indicate if the code is for multiple
                             dataframes

        Returns (str): A python code
        """

        if multiple:

Review comment (suggestion):
We don't need this, as we automatically import the relevant dependencies (with the right alias) with `import_dependency` a few lines below.

Code after:

        # clear recent optional dependencies
        self._additional_dependencies = []

        for node in tree.body:
            if isinstance(node, (ast.Import, ast.ImportFrom)):
                self._check_imports(node)
                continue
            if self._is_df_overwrite(node) or self._is_jailbreak(node):
                continue
            new_body.append(node)

        new_tree = ast.Module(body=new_body)
        return astor.to_source(new_tree, pretty_source=lambda x: "".join(x)).strip()

    def _get_environment(self) -> dict:
        """
        Returns the environment for the code to be executed.

        Returns (dict): A dictionary of environment variables
        """

        return {
            "pd": pd,
            **{
                lib["alias"]: getattr(import_dependency(lib["module"]), lib["name"])
                if hasattr(import_dependency(lib["module"]), lib["name"])
                else import_dependency(lib["module"])
                for lib in self._additional_dependencies
            },
            "__builtins__": {
                **{builtin: __builtins__[builtin] for builtin in WHITELISTED_BUILTINS},
            },
        }

    def _retry_run_code(self, code: str, e: Exception, multiple: bool = False):
        """
        A method to retry the code execution with error correction framework.

        Args:
            code (str): A python code
            e (Exception): An exception
            multiple (bool): A boolean to indicate if the code is for multiple
                             dataframes

        Returns (str): A python code
        """

        if multiple:
            correct_multiple_dataframes_error_default_values = {
                "code": code,