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26bead7 cc7a977 26bead7 cc7a977 26bead7 cc7a977 26bead7 cc7a977 26bead7 cc7a977 26bead7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | """Optimizer module for the AI Python C Extensions Generator application."""
from logging import getLogger
from dotenv import load_dotenv
from openai import OpenAI
from pydantic import BaseModel, Field
from .prompts import messages_for
_logger = getLogger(__name__)
# Environment initialization.
load_dotenv(override=True)
# Initialize client and set the default LLM model to use.
openai = OpenAI()
OPENAI_MODEL = "gpt-5"
_logger.info(f'INITIALIZED OPTIMIZER MODULE')
# Define Pydantic model class for GPT response parsing.
class _extension_codes(BaseModel):
c_code: str = Field(...,
description="Generated C extension source "
"code for the Python module.")
setup: str = Field(...,
description="The generated setup.py build script "
"used to compile the C extension module."
"It must assume the module is in the current folder "
"and not in any subfolder.")
usage: str = Field(...,
description="A Python usage example that imports the compiled "
"extension and compares its execution time with the "
"original Python implementation.")
def __str__(self):
"""Return a string representation of the optimization codes."""
return (f"C CODE:\n{self.c_code}\n"
f"---------------------------\n"
f"setup.py:\n{self.setup}\n"
f"---------------------------\n"
f"USAGE:\n{self.usage}")
# Define optimization function using OpenAI's GPT model.
def optimize_gpt(python_code, module_name, platform, compile_path, model=OPENAI_MODEL):
"""Generate an optimized C extension for Python."""
schema = _extension_codes.model_json_schema()
_logger.info('SENDING OPTIMIZATION REQUEST TO OPENAI... '
f'(MODEL: {model}, PLATFORM: {platform}, '
f'MODULE: {module_name}, COMPILE PATH: {compile_path})')
response = openai.responses.parse(
model=model, text_format=_extension_codes,
input=messages_for(python_code, module_name, schema, platform, compile_path)
).output_parsed
_logger.info('RECEIVED OPTIMIZATION RESPONSE FROM OPENAI')
return response.c_code, response.setup, response.usage
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