47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
from typing import Any, List, Tuple
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import logging
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import os
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import sys
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from pathlib import Path
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import dotenv
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from transformers import pipeline
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dotenv.load_dotenv()
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logging.basicConfig(
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filename="QA.log",
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filemode="w",
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level=logging.INFO,
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format="%(name)s - %(levelname)s - %(message)s",
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)
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sys.path.append(str(Path(__file__).parent.parent.parent) + "/tools/NLP/data")
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sys.path.append(str(Path(__file__).parent.parent.parent) + "/utils")
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import config
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import internet
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def answer(
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query: str, GOOGLE_SEARCH_API_KEY: str, GOOGLE_SEARCH_ENGINE_ID: str
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) -> tuple[Any, list[str]]:
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QA_MODEL: Any = pipeline("question-answering")
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# GOOGLE_SEARCH_API_KEY = str(os.getenv("INTERNET_ML_GOOGLE_API"))
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# GOOGLE_SEARCH_ENGINE_ID = str(os.getenv("INTERNET_ML_GOOGLE_SEARCH_ENGINE_ID"))
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results: tuple[list[str], list[str]] = internet.Google(
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query, GOOGLE_SEARCH_API_KEY, GOOGLE_SEARCH_ENGINE_ID
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).google()
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answer: tuple[Any, list[str]] = (
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QA_MODEL(question=query, context=str(results[0])),
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results[1],
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)
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if config.CONF_DEBUG:
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logging.info(f"Answer: {answer}")
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return answer
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# print(answer("Who is the author of TinTin?"))
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# def custom_answer
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