update: look at todo
parent
5f0faa77a4
commit
5261d734de
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@ -1,4 +1,13 @@
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# type: ignore
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"""
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model naming convention
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# Open-AI models:
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include prefix openai-*
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# HuggingFace
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include prefix hf-*
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"""
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from typing import Any, List, Tuple
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import os
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@ -31,11 +40,6 @@ def answer(
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CHATGPT_CONVERSATION_ID: str = "",
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CHATGPT_PARENT_ID: str = "",
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) -> tuple[Any, list[str]]:
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# if environment keys are not given, assume it is in env
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if GOOGLE_SEARCH_API_KEY == "":
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GOOGLE_SEARCH_API_KEY = str(os.environ.get("GOOGLE_SEARCH_API_KEY"))
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if GOOGLE_SEARCH_ENGINE_ID == "":
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GOOGLE_SEARCH_ENGINE_ID = str(os.environ.get("GOOGLE_SEARCH_ENGINE_ID"))
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if OPENAI_API_KEY == "":
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OPENAI_API_KEY = str(os.environ.get("OPENAI_API_KEY"))
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openai.api_key = OPENAI_API_KEY
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@ -45,25 +49,20 @@ def answer(
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CHATGPT_CONVERSATION_ID = str(os.environ.get("CHATGPT_CONVERSATION_ID"))
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if CHATGPT_PARENT_ID == "":
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CHATGPT_PARENT_ID = str(os.environ.get("CHATGPT_PARENT_ID"))
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"""
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model naming convention
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# Open-AI models:
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include prefix openai-*
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# HuggingFace
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include prefix hf-*
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#
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"""
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if not (model.startswith("openai-") or model.startswith("hf-")):
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model = "openai-chatgpt" # Default
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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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if model.startswith("openai-"):
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if model == "openai-chatgpt":
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# ChatGPT
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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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# print(' '.join(filter(lambda x: isinstance(x, str), results[0]))[:4000])
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prompt = f"Using the context: {' '.join(filter(lambda x: isinstance(x, str), results[0]))[:3000]} and answer the question with the context above and previous knowledge: \"{query}\". Also write long answers or essays if asked."
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print(prompt)
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exit(1)
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chatbot = Chatbot(
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{"session_token": CHATGPT_SESSION_TOKEN},
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conversation_id=None,
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@ -77,14 +76,11 @@ def answer(
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return (response["message"], results[1])
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else:
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if model == "openai-text-davinci-003":
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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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context = " ".join(results[0])
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context[: (4097 - len(query) - 10)]
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# text-davinci-003
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prompt = f"Using the context: {' '.join(filter(lambda x: isinstance(x, str), results[0]))[:3000]} and answer the question with the context above and previous knowledge: \"{query}\". Also write long answers or essays if asked."
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=f"{context} Q: {query}",
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prompt=prompt,
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max_tokens=len(context),
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n=1,
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stop=None,
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@ -94,9 +90,6 @@ def answer(
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# TODO: add suport later
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else:
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model = model.replace("hf-", "", 1)
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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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qa_model = pipeline("question-answering", model=model)
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response = qa_model(question=query, context=" ".join(results[0]))
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return (response["answer"], results[1])
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@ -1,6 +1,142 @@
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from typing import Any, List, Tuple
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# from typing import Any, List, Tuple
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# import os
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# import sys
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# from importlib import reload
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# from pathlib import Path
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# import dotenv
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# import requests
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# HTTP_USERAGENT: dict[str, str] = {
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# "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
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# }
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# sys.path.append(str(Path(__file__).parent.parent.parent.parent) + "/utils/NLP")
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# sys.path.append(str(Path(__file__).parent.parent.parent.parent) + "/utils")
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# sys.path.append(str(Path(__file__).parent.parent))
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# import asyncio
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# import itertools
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# import re
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# import aiohttp
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# import config
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# from bs4 import BeautifulSoup
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# from normalize import normalizer
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# # from relevancy import filter_irrelevant
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# from sentencize import sentencizer
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# from urlextract import URLExtract
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# from adremover import AdRemover
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# class Google:
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# def __init__(
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# self: "Google",
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# query: str,
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# GOOGLE_SEARCH_API_KEY: str,
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# GOOGLE_SEARCH_ENGINE_ID: str,
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# ) -> None:
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# self.__GOOGLE_SEARCH_API_KEY: str = GOOGLE_SEARCH_API_KEY
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# self.__GOOGLE_SEARCH_ENGINE_ID: str = GOOGLE_SEARCH_ENGINE_ID
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# # if environment keys are not given, assume it is in env
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# if GOOGLE_SEARCH_API_KEY == "":
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# self.__GOOGLE_SEARCH_API_KEY = str(os.environ.get("GOOGLE_SEARCH_API_KEY"))
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# if GOOGLE_SEARCH_ENGINE_ID == "":
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# self.__GOOGLE_SEARCH_ENGINE_ID = str(os.environ.get("GOOGLE_SEARCH_ENGINE_ID"))
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# self.__num_res: int = 10
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# self.__query = query
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# self.__URL_EXTRACTOR: URLExtract = URLExtract()
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# self.__urls: list[str] = self.__URL_EXTRACTOR.find_urls(query)
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# self.__query = str(
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# re.sub(
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# r"\w+:\/{2}[\d\w-]+(\.[\d\w-]+)*(?:(?:\/[^\s/]*))*",
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# "",
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# str(self.__query),
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# )
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# )
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# def __get_urls(self: "Google") -> None:
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# if self.__GOOGLE_SEARCH_API_KEY == "":
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# exit("ERROR: Google API Key not found")
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# if self.__GOOGLE_SEARCH_ENGINE_ID == "":
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# exit("ERROR: Google Search Engine Id not found")
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# response = requests.get(
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# "https://www.googleapis.com/customsearch/v1",
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# params={
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# "key": self.__GOOGLE_SEARCH_API_KEY,
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# "q": self.__query,
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# "cx": self.__GOOGLE_SEARCH_ENGINE_ID,
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# },
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# )
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# results = response.json()["items"]
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# for result in results:
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# self.__urls.append(result["link"])
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# if len(self.__urls) == self.__num_res:
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# break
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# async def __fetch_url(self: "Google", session: Any, url: str) -> list[str]:
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# try:
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# async with session.get(url, headers=HTTP_USERAGENT) as response:
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# html = await response.text()
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# soup = BeautifulSoup(html, "html.parser")
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# text = soup.get_text()
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# normalized_text = normalizer(text)
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# sentences: list[str] = sentencizer(normalized_text)
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# return sentences
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# except aiohttp.ClientConnectorError:
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# return [""]
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# except Exception:
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# return [""]
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# async def __fetch_urls(self: "Google", urls: list[str]) -> Any:
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# async with aiohttp.ClientSession() as session:
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# tasks = [
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# asyncio.create_task(self.__fetch_url(session, url)) for url in urls
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# ]
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# results = await asyncio.gather(*tasks)
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# return results
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# def __flatten(self: Any, a: list[list[Any]]) -> list[Any]:
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# return list(itertools.chain(*a))
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# def __get_urls_contents(self: "Google") -> None:
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# loop = asyncio.new_event_loop()
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# asyncio.set_event_loop(loop)
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# contents = loop.run_until_complete(self.__fetch_urls(self.__urls))
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# loop.close()
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# self.__content = self.__flatten(contents)
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# def google(self: "Google") -> tuple[list[str], list[str]]:
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# self.__get_urls()
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# self.__get_urls_contents()
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# return (self.__content, self.__urls)
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# """
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# Timing:
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# import time
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# start_time = time.time()
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# google("Who is Elon Musk")
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# print("--- %s seconds ---" % (time.time() - start_time))
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# # Results:
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# # --- 2.2230100631713867 seconds ---
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# # ________________________________________________________
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# # Executed in 4.73 secs fish external
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# # usr time 3.35 secs 85.00 micros 3.35 secs
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# # sys time 1.86 secs 956.00 micros 1.86 secs
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# """
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from typing import Any, Dict, List, Tuple
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import os
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import pickle
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import sys
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from importlib import reload
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from pathlib import Path
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@ -17,18 +153,22 @@ sys.path.append(str(Path(__file__).parent.parent.parent.parent) + "/utils")
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sys.path.append(str(Path(__file__).parent.parent))
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import asyncio
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import concurrent.futures
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import itertools
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import re
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import aiohttp
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import config
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from adremover import AdRemover
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from bs4 import BeautifulSoup
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from keywords import get_keywords
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from normalize import normalizer
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# from relevancy import filter_irrelevant
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from relevancy import filter_relevant
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from sentencize import sentencizer
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from urlextract import URLExtract
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dotenv.load_dotenv()
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class Google:
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def __init__(
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@ -37,9 +177,18 @@ class Google:
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GOOGLE_SEARCH_API_KEY: str,
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GOOGLE_SEARCH_ENGINE_ID: str,
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) -> None:
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self.__GOOGLE_SEARCH_API_KEY: str = GOOGLE_SEARCH_API_KEY
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self.__GOOGLE_SEARCH_ENGINE_ID: str = GOOGLE_SEARCH_ENGINE_ID
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self.__num_res: int = 10
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# if environment keys are not given, assume it is in env
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if GOOGLE_SEARCH_API_KEY == "":
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self.__GOOGLE_SEARCH_API_KEY = str(os.environ.get("GOOGLE_SEARCH_API_KEY"))
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if GOOGLE_SEARCH_ENGINE_ID == "":
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self.__GOOGLE_SEARCH_ENGINE_ID = str(
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os.environ.get("GOOGLE_SEARCH_ENGINE_ID")
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)
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self.__num_res: int = (
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5
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if config.NLP_CONF_MODE == "speed"
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else (20 if config.NLP_CONF_MODE else 10)
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)
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self.__query = query
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self.__URL_EXTRACTOR: URLExtract = URLExtract()
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self.__urls: list[str] = self.__URL_EXTRACTOR.find_urls(query)
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@ -50,8 +199,15 @@ class Google:
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str(self.__query),
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)
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)
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self.__content: list[str] = []
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ADBLOCK_RULES = [
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"https://easylist-downloads.adblockplus.org/ruadlist+easylist.txt",
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"https://filters.adtidy.org/extension/chromium/filters/1.txt",
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]
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self.__ad_remover = AdRemover(ADBLOCK_RULES)
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def __get_urls(self: "Google") -> None:
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# Send the request to the Google Search API
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if self.__GOOGLE_SEARCH_API_KEY == "":
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exit("ERROR: Google API Key not found")
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if self.__GOOGLE_SEARCH_ENGINE_ID == "":
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@ -74,6 +230,7 @@ class Google:
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try:
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async with session.get(url, headers=HTTP_USERAGENT) as response:
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html = await response.text()
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html = self.__ad_remover.remove_ads(html)
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soup = BeautifulSoup(html, "html.parser")
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text = soup.get_text()
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normalized_text = normalizer(text)
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contents = loop.run_until_complete(self.__fetch_urls(self.__urls))
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loop.close()
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self.__content = self.__flatten(contents)
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self.__content = [str(x) for x in self.__content]
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def google(self: "Google") -> tuple[list[str], list[str]]:
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def __filter_irrelevant_processing(self: "Google") -> None:
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with concurrent.futures.ThreadPoolExecutor(max_workers=500) as executor:
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futures = [executor.submit(filter_relevant, self.__content, self.__query)]
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concurrent.futures.wait(futures)
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content: list[str] = []
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for future in futures:
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content.append(future.result())
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self.__content = content
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def google(
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self: "Google", filter_irrelevant: bool = True
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) -> tuple[list[str], list[str]]:
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self.__get_urls()
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self.__get_urls_contents()
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return (self.__content, self.__urls)
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if filter_irrelevant:
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self.__filter_irrelevant_processing()
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results: tuple[list[str], list[str]] = (self.__content, self.__urls)
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return results
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"""
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