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import os | |
import google.generativeai as generativeai | |
from dotenv import load_dotenv | |
# Load API key from environment | |
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." | |