Modularizes Python Files and Introduce .env File for Improved Security

.gitignore

@@ -1 +1,8 @@
+__pycache__/
 *.pyc
+*.pyo
+*.egg-info/
+dist/
+build/
+.env
+venv/

ai/__init__.py

@@ -0,0 +1 @@
+from .functions import ai_function

ai_functions.py → ai/functions.py

@@ -1,7 +1,7 @@
 import openai
 
 def ai_function(function, args, description, model = "gpt-4"):
-    # parse args to comma separated string
+    """Takes a function, arguments, and a description and returns the result of the function with the given arguments."""
     args = ", ".join(args)
     messages = [{"role": "system", "content": f"You are now the following python function: ```# {description}\n{function}```\n\nOnly respond with your `return` value. Do not include any other explanatory text in your response."},{"role": "user", "content": args}]
 

requirements.txt

@@ -1,2 +1,3 @@
 openai==0.27.0
 pytest==7.2.2
+python-dotenv==0.19.1

tests/__init__.py

@@ -0,0 +1 @@
+from .test_ai_function import test_1, test_2, test_3, test_4

test_ai_function.py → tests/test_ai_function.py

@@ -1,16 +1,19 @@
 import ast
 import json
 import time
-import ai_functions
+import ai.functions as functions
 import pytest
 import openai
-import keys
+from dotenv import load_dotenv
+from os import environ
+load_dotenv()
 
 # Initialize the OpenAI API client
-openai.api_key = keys.OPENAI_API_KEY
+openai.api_key = environ.get("OPENAI_API_KEY")
 
 # Run all tests, print the results, and return the number of failed tests
 def run_tests(model):
+    """Runs all tests and prints the results. Returns the number of failed tests."""
     test_functions = [test_1, test_2, test_3, test_4, test_5, test_6]
     test_names = [
         "Generate fake people",
@@ -43,12 +46,13 @@ def run_tests(model):
 
 # Ai function test 1
 def test_1(model):
+    """Generates n examples of fake data representing people, each with a name and an age."""
     function_string = "def fake_people(n: int) -> list[dict]:"
     args = ["4"]
     description_string = """Generates n examples of fake data representing people, 
             each with a name and an age."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
 
     print(f"Output: {result_string}")
     # Assert the result can be parsed as is a list of dictionaries
@@ -72,11 +76,12 @@ def test_1(model):
 
 # Ai function test 2
 def test_2(model):
+    """Generates a random password of given length with or without special characters."""
     function_string = "def random_password_generator(length: int, special_chars: bool) -> str:"
     args = ["12", "True"]
     description_string = """Generates a random password of given length with or without special characters."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
 
     print(f"Output: {result_string}")
 
@@ -86,11 +91,12 @@ def test_2(model):
 
 # Ai function test 3
 def test_3(model):
+    """Calculates the area of a triangle given its base and height."""
     function_string = "def calculate_area_of_triangle(base: float, height: float) -> float:"
     args = ["15", "6.5"]
     description_string = """Calculates the area of a triangle given its base and height."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
     print(f"Output: {result_string}")
 
     # Assert the result can be parsed as a float
@@ -108,11 +114,12 @@ def test_3(model):
 
 # Ai function test 4
 def test_4(model):
+    """Finds and returns the nth prime number."""
     function_string = "def get_nth_prime_number(n: int) -> int:"
     args = ["10"]
     description_string = """Finds and returns the nth prime number."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
 
     print(f"Output: {result_string}")
 
@@ -131,11 +138,12 @@ def test_4(model):
 
 # Ai function test 5
 def test_5(model):
+    """Encrypts the given text using a simple character substitution based on the provided key."""
     function_string = "def encrypt_text(text: str, key: str) -> str:"
     args = ["'Hello, World!'", "'abc123'"]
     description_string = """Encrypts the given text using a simple character substitution based on the provided key."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
 
     print(f"Output: {result_string}")
 
@@ -145,11 +153,12 @@ def test_5(model):
 
 # Ai function test 6
 def test_6(model):
+    """Finds and returns a list of missing numbers in a given sorted list."""
     function_string = "def find_missing_numbers_in_list(numbers: list[int]) -> list[int]:"
     args = ["[3, 5, 8, 15, 16]"]
     description_string = """Finds and returns a list of missing numbers in a given sorted list."""
 
-    result_string = ai_functions.ai_function(function_string, args, description_string, model)
+    result_string = functions.ai_function(function_string, args, description_string, model)
 
     print(f"Output: {result_string}")