| import os |
| import google.generativeai as generativeai |
| from dotenv import load_dotenv |
|
|
| |
| load_dotenv() |
| generativeai.configure(api_key=os.getenv("GOOGLE_GEMINI_KEY")) |
|
|
| def get_correction_and_comments(code_snippet): |
| """ |
| Analyze, correct, and comment on the given Python code. |
| """ |
| prompt = [ |
| "Analyze and correct the following Python code, add comments, and format it:", |
| code_snippet |
| ] |
| response = generativeai.GenerativeModel('gemini-pro').generate_content(prompt) |
| return response.text if response else "No suggestions available." |
|
|
| def generate_questions(code_snippet, question_type): |
| """ |
| Generate questions and answers based on the user's choice of question type. |
| |
| Parameters: |
| - code_snippet: The Python code to generate questions for. |
| - question_type: The type of questions to generate. |
| |
| Returns: |
| - Generated questions and answers as text. |
| """ |
| if question_type == "Logical Questions": |
| prompt = [ |
| "Analyze the following Python code and generate logical reasoning questions and answers:", |
| code_snippet |
| ] |
| elif question_type == "Interview-Based Questions": |
| prompt = [ |
| "Analyze the following Python code and generate interview-style questions and answers for developers:", |
| code_snippet |
| ] |
| elif question_type == "Code Analysis Questions": |
| prompt = [ |
| "Analyze the following Python code and generate in-depth code analysis questions with answers:", |
| code_snippet |
| ] |
| else: |
| prompt = [ |
| "Generate general Python questions and answers based on the given code:", |
| code_snippet |
| ] |
| |
| response = generativeai.GenerativeModel('gemini-pro').generate_content(prompt) |
| return response.text if response else "No answer available." |
|
|