path: root/devourer.py

# _*_ coding=utf-8 _*_

import logging
import tika
import nltk
import random
import string
import os
from newspaper import Article, build, Config
from bs4 import BeautifulSoup
from contextlib import closing
from requests import get, Response
from requests.exceptions import RequestException
from re import findall
from readability import Document
from gtts import gTTS
from datetime import datetime as time
from fastapi import FastAPI
from fastapi import Response as APIResponse


# FIXME-maybe actually really do some logging
def logError(err: RequestException) -> None:
    """Logs the errors."""
    logging.exception(err)


def isAGoodResponse(resp: Response) -> bool:
    """Checks whether the get we sent got a 200 response."""
    content_type = resp.headers["Content-Type"].lower()
    return resp.status_code == 200 and content_type is not None


def simpleGet(url: str) -> bytes:
    """Issues a simple get request."""
    try:
        with closing(get(url, stream=True)) as resp:
            if isAGoodResponse(resp):
                return resp.content
            else:
                return None
    except RequestException as e:
        logError("Error during requests to {0} : {1}".format(url, str(e)))
        return None


def getWithParams(url: str, params: dict) -> dict:
    """Issues a get request with params."""
    try:
        with closing(get(url, params=params, stream=True)) as resp:
            if isAGoodResponse(resp):
                return resp.json()
            else:
                return None
    except RequestException as e:
        logError("Error during requests to {0} : {1}".format(url, str(e)))
        return None


def getRandStr(n):
    """Return a random string of the given length."""
    return "".join([random.choice(string.lowercase) for i in range(n)])


def getURLS(source: str) -> dict:
    """Extracts the urls from a website."""
    result = dict()
    raw_ml = simpleGet(source)
    ml = BeautifulSoup(raw_ml, "lxml")

    rand_tmp = "/tmp/" + getRandStr(20)
    ml_str = repr(ml)
    tmp = open(rand_tmp, "w")
    tmp.write(ml_str)
    tmp.close()
    tmp = open(rand_tmp, "r")
    url_list = []
    for line in tmp:
        url = findall(
            "http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*(),]|"
            r"(?:%[0-9a-fA-F][0-9a-fA-F]))+",
            line,
        )
        url_list += url
    for elem in url_list:
        result[elem] = elem
    tmp.close()
    return result


def configNews(config: Config) -> None:
    """Configures newspaper."""
    config.fetch_images = False
    config.keep_article_html = True
    config.memoize_articles = False
    config.browser_user_agent = "Chrome/91.0.4464.5"


# FIXME-have to decide whether to use files or urls
def pdfToVoice() -> str:
    """Main function for converting a pdf to an mp3."""
    outfile = str()
    try:
        rawText = tika.parser.from_file()
        tts = gTTS(rawText["content"])
        outfile = getRandStr(20) + ".mp3"
        tts.save(outfile)
    except Exception as e:
        logging.exception(e)
    finally:
        return outfile


def extractRequirements(textBody: str) -> list:
    """Extract the sentences containing the keywords that denote a requirement.

    the keywords are baed on ISO/IEC directives, part 2:
    https://www.iso.org/sites/directives/current/part2/index.xhtml
    """
    result = []
    REQ_KEYWORDS = [
        "shall",
        "shall not",
        "should",
        "should not",
        "must",
        "may",
        "can",
        "cannot",
    ]
    sentences = nltk.sent_tokenize(textBody)
    for sentence in sentences:
        for keyword in REQ_KEYWORDS:
            if sentence.find(keyword) >= 0:
                result.append(sentence)
    return result


def summarizeText(text: str) -> str:
    """Summarize the given text using bart."""
    import transformers

    model = transformers.BartForConditionalGeneration.from_pretrained(
        "facebook/bart-large-cnn"
    )
    tokenizer = transformers.BartTokenizer.from_pretrained(
        "facebook/bart-large-cnn"
    )
    inputs = tokenizer([text], max_length=1024, return_tensors="pt")
    summary_ids = model.generate(
        inputs["input_ids"], num_beams=4, max_length=5, early_stopping=True
    )
    return [
        tokenizer.decode(
            g, skip_special_tokens=True, clean_up_tokenization_spaces=False
        )
        for g in summary_ids
    ]


def textToAudio(text: str) -> str:
    """Transform the given text into audio."""
    path = str()
    try:
        time_str = time.today().strftime("%b-%d-%Y-%M-%S-%f")
        tts = gTTS(text)
        tts.save(os.environ["AUDIO_DUMP_DIR"] + "/" + time_str + ".mp3")
        path = os.environ["AUDIO_DUMP_DIR"] + "/" + time_str + ".mp3"
    except Exception as e:
        logging.exception(e)
    finally:
        return path


def getRequirements(url: str, sourcetype: str) -> list:
    """Runs the single-link main function."""
    result = str()
    results = list()
    try:
        if sourcetype == "html":
            parser = build(url)
            for article in parser.articles:
                a = Article(article.url)
                a.download()
                a.parse()
                doc = Document(a.html)
                # print(doc.summary())
                results = extractRequirements(doc.summary())
        elif sourcetype == "text":
            bytesText = simpleGet(url)
            results = extractRequirements(bytesText.decode("utf-8"))
    except Exception as e:
        logging.exception(e)
    finally:
        result = "".join(results + "\n")
        return result


# FIXME-summary=bart doesnt work
def summarizeLinkToAudio(url, summary) -> str:
    """Summarizes the text inside a given url into audio."""
    result = str()
    try:
        article = Article(url)
        article.download()
        article.parse()
        if summary == "newspaper":
            article.nlp()
            result = article.summary
        elif summary == "none":
            result = article.text
        elif summary == "bart":
            result = article.text
        else:
            print("invalid option for summary type.")
    except Exception as e:
        logging.exception(e)
    finally:
        return result


# FIXME-change my name
def summarizeLinksToAudio(url, summary) -> None:
    """Summarize a list of urls into audio files."""
    results = list()
    result = str()
    try:
        config = Config()
        configNews(config)
        urls = getURLS(url, summary)
        for url in urls:
            results.append(summarizeLinkToAudio(url))
    except Exception as e:
        logging.exception(e)
    finally:
        result = "".join(results)
        return result


def searchWikipedia(search_term: str) -> str:
    """Search wikipedia for a string and return the url.

    reference: https://www.mediawiki.org/wiki/API:Opensearch
    """
    result = str()
    try:
        searchParmas = {
            "action": "opensearch",
            "namespace": "0",
            "search": search_term,
            "limit": "10",
            "format": "json",
        }
        res = getWithParams(os.environ["WIKI_SEARCH_URL"], searchParmas)
        # FIXME-handle wiki redirects/disambiguations
        source = res[3][0]
        result = summarizeLinkToAudio(source, "none")
    except Exception as e:
        logging.exception(e)
    finally:
        return result


def getAudioFromFile(audio_path: str) -> str:
    """Returns the contents of a file in binary format"""
    with open(audio_path, "rb") as audio:
        return audio.read()


app = FastAPI()
nltk.download("punkt")


@app.get("/mila/tika")
def pdf_to_audio_ep(url: str):
    """turns a pdf into an audiofile"""
    audio_path = pdfToVoice()
    return APIResponse(
        getAudioFromFile(audio_path) if audio_path != "" else "",
        media_type="audio/mpeg",
    )


@app.get("/mila/reqs")
def extract_reqs_ep(url: str, sourcetype: str = "html"):
    """extracts the requirements from a given url"""
    result = getRequirements()
    return {
        "Content-Type": "application/json",
        "isOK": True if result != "" else False,
        "reqs": result,
    }


@app.get("/mila/wiki")
def wiki_search_ep(term: str, audio: bool = False):
    """search and summarizes from wikipedia"""
    text = searchWikipedia(term)
    if audio:
        audio_path = textToAudio(text)
        return FastAPI(
            getAudioFromFile(audio_path) if audio_path != "" else "",
            media_type="audio/mpeg",
        )
    else:
        return {
            "Content-Type": "application/json",
            "isOK": True if text != "" else False,
            "audio": "",
            "text": text,
        }


@app.get("/mila/summ")
def summarize_ep(url: str, summary: str = "none", audio: bool = False):
    """summarize and turn the summary into audio"""
    text = summarizeLinkToAudio(url, summary)
    if audio:
        audio_path = textToAudio(text)
        print(audio_path)
        return APIResponse(
            getAudioFromFile(audio_path) if audio_path != "" else "",
            media_type="audio/mpeg",
        )
    else:
        return {
            "Content-Type": "application/json",
            "isOK": True if text != "" else False,
            # "audio": "",
            "text": text,
        }


@app.get("/mila/mila")
def mila_ep(url: str, summary: str = "newspaper", audio: bool = False):
    """extract all the urls and then summarize and turn into audio"""
    text = summarizeLinksToAudio(url, summary)
    if audio:
        audio_path = textToAudio(text)
        print(audio_path)
        return APIResponse(
            getAudioFromFile(audio_path) if audio_path != "" else "",
            media_type="audio/mpeg",
        )
    else:
        return {
            "Content-Type": "application/json",
            "isOK": True if text != "" else False,
            "audio": "",
            "text": text,
        }


@app.get("/mila/health")
def health_ep():
    return {"isOK": True}


@app.get("/mila/robots.txt")
def robots_ep():
    return {
        "Content-Type": "apllication/json",
        "User-Agents": "*",
        "Disallow": "/",
    }