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94 lines
2.3 KiB
Python
94 lines
2.3 KiB
Python
import ast
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import os
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from dotenv import load_dotenv
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from openai import AzureOpenAI
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from promptflow.tracing import start_trace, trace
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@trace
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def infinite_loop_check(code_snippet):
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tree = ast.parse(code_snippet)
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for node in ast.walk(tree):
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if isinstance(node, ast.While):
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if not node.orelse:
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return True
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return False
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@trace
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def syntax_error_check(code_snippet):
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try:
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ast.parse(code_snippet)
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except SyntaxError:
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return True
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return False
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@trace
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def error_fix(code_snippet):
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tree = ast.parse(code_snippet)
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for node in ast.walk(tree):
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if isinstance(node, ast.While):
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if not node.orelse:
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node.orelse = [ast.Pass()]
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return ast.unparse(tree)
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@trace
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def code_refine(original_code: str) -> str:
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original_code = original_code.replace("python", "").replace("`", "").strip()
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fixed_code = None
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if infinite_loop_check(original_code):
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fixed_code = error_fix(original_code)
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else:
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fixed_code = original_code
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if syntax_error_check(fixed_code):
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fixed_code = error_fix(fixed_code)
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return fixed_code
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@trace
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def code_gen(client: AzureOpenAI, question: str) -> str:
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sys_prompt = (
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"I want you to act as a math expert specializing in Algebra, Geometry, and Calculus. "
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"Given the question, develop python code to model the user's question. "
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"Make sure only reply the executable code, no other words."
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)
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completion = client.chat.completions.create(
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model=os.getenv("CHAT_DEPLOYMENT_NAME", "gpt-35-turbo"),
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messages=[
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{
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"role": "system",
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"content": sys_prompt,
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},
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{"role": "user", "content": question},
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],
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)
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raw_code = completion.choices[0].message.content
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result = code_refine(raw_code)
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return result
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if __name__ == "__main__":
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start_trace()
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if "AZURE_OPENAI_API_KEY" not in os.environ:
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# load environment variables from .env file
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load_dotenv()
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client = AzureOpenAI(
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_version="2023-12-01-preview",
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)
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question = "What is 37593 * 67?"
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code = code_gen(client, question)
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print(code)
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