Run Python

If you thought allowing an LLM to write files was a bad idea...

You ain't seen nothin' yet! (praise the basilisk)

It's time to build the functionality for our agent to run arbitrary Python code.

Now, it's worth pausing to point out the inherent security risks here. We have a few things going for us:

We'll only allow the LLM to run code in a specific directory (the working_directory).
We'll use a 30-second timeout to prevent it from running indefinitely.

But aside from that... yes, the LLM can run arbitrary code that we place (or it places) in the working directory... so be careful. As long as you use this AI agent only for the simple tasks we're doing in this course, you should be just fine.

Do not give this program to others for them to use! It doesn't have all the security and safety features that a production AI agent would have. This is for learning purposes only.

Assignment

Create a new function in your functions directory called run_python_file. Here's the signature to use:
```
def run_python_file(working_directory, file_path, args=[]):
```

If the file_path is outside the working directory, return an error string:

f'Error: Cannot execute "{file_path}" as it is outside the permitted working directory'

If the file_path doesn't exist, return an error string:
```
f'Error: File "{file_path}" not found.'
```
If the file name doesn't end with .py, return an error string:
```
f'Error: "{file_path}" is not a Python file.'
```
Use the subprocess.run function to execute the Python file with the python command and get back a completed_process object. Make sure to:
1. Set a timeout of 30 seconds to prevent infinite execution.
2. Capture both stdout and stderr.
3. Set the working directory properly.
4. Pass along the additional args if provided.
Return a string with the output formatted to include:
1. The stdout prefixed with STDOUT:, and stderr prefixed with STDERR:. The completed_process object has a stdout and stderr attribute.
2. If the process exits with a non-zero code, include "Process exited with code X".
3. If no output is produced, return "No output produced".
If any exceptions occur during execution, catch them and return an error string:
```
f"Error: executing Python file: {e}"
```
Create a new test module at the root of your project, test_run_python_file.py. It should be similar in structure to the test modules that you've written for other functions. Include the following test cases, printing each result:
1. run_python_file("calculator", "main.py") (should print the calculator's usage instructions)
2. run_python_file("calculator", "main.py", ["3 + 5"]) (should run the calculator... which gives a kinda nasty rendered result)
3. run_python_file("calculator", "tests.py") (should run the calculator's tests successfully)
4. run_python_file("calculator", "../main.py") (this should return an error)
5. run_python_file("calculator", "nonexistent.py") (this should return an error)
6. run_python_file("calculator", "lorem.txt") (this should return an error)

Run and submit the CLI tests.