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e635cf4a4a
Some of the previously fixed things creeped in. I would like to keep the requirements low on the PR authors for now and gradually improve the pep8 compliance without introducing much breakage.
68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
from typing import List, Optional
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import json
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from config import Config
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from call_ai_function import call_ai_function
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from json_parser import fix_and_parse_json
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cfg = Config()
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def evaluate_code(code: str) -> List[str]:
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"""
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A function that takes in a string and returns a response from create chat completion api call.
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Parameters:
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code (str): Code to be evaluated.
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Returns:
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A result string from create chat completion. A list of suggestions to improve the code.
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"""
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function_string = "def analyze_code(code: str) -> List[str]:"
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args = [code]
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description_string = """Analyzes the given code and returns a list of suggestions for improvements."""
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result_string = call_ai_function(function_string, args, description_string)
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return result_string
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def improve_code(suggestions: List[str], code: str) -> str:
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"""
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A function that takes in code and suggestions and returns a response from create chat completion api call.
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Parameters:
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suggestions (List): A list of suggestions around what needs to be improved.
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code (str): Code to be improved.
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Returns:
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A result string from create chat completion. Improved code in response.
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"""
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function_string = (
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"def generate_improved_code(suggestions: List[str], code: str) -> str:"
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)
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args = [json.dumps(suggestions), code]
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description_string = """Improves the provided code based on the suggestions provided, making no other changes."""
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result_string = call_ai_function(function_string, args, description_string)
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return result_string
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def write_tests(code: str, focus: List[str]) -> str:
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"""
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A function that takes in code and focus topics and returns a response from create chat completion api call.
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Parameters:
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focus (List): A list of suggestions around what needs to be improved.
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code (str): Code for test cases to be generated against.
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Returns:
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A result string from create chat completion. Test cases for the submitted code in response.
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"""
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function_string = (
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"def create_test_cases(code: str, focus: Optional[str] = None) -> str:"
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)
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args = [code, json.dumps(focus)]
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description_string = """Generates test cases for the existing code, focusing on specific areas if required."""
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result_string = call_ai_function(function_string, args, description_string)
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return result_string
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