chatbot.py

import utilities
import databaseconnect
import googleMapsApiModule
from enum import Enum, auto
import logging
import logger_config

location_dict = {"origin": "null", "destination": "null"}

log = logging.getLogger(__name__)
log.info("Entered module: %s" % __name__)


class LearnResponse(Enum):
    MESSAGE = auto()
    TRAIN_ME = auto()
    ORIGIN = auto()
    DESTINATION = auto()


@logger_config.logger
def setup():
    utilities.setup_nltk()
    logging.debug("NLTK setup completed")
    clf = utilities.classify_model_adv(model="rf")
    logging.debug("Classification model ready")
    databaseconnect.setup_database()
    logging.debug("Database setup completed, database connected")
    learn_response = LearnResponse.MESSAGE.name
    return clf, learn_response


@logger_config.logger
def message_to_bot(H, clf, learn_response):
    if learn_response == LearnResponse.ORIGIN.name:
        location_dict["origin"] = H
        B = "Can you help me with the destination location?"
        learn_response = LearnResponse.DESTINATION.name
        return B, learn_response
    if learn_response == LearnResponse.DESTINATION.name:
        location_dict["destination"] = H
        origin, destination = (
            location_dict["origin"],
            location_dict["destination"],
        )
        googleMapsApiModule.direction(origin, destination)
        B = "I will certainly help you with that."
        learn_response = LearnResponse.MESSAGE.name
        return B, learn_response
    if "bye" in H.lower().split(" "):  # check in words within H
        B = "Bye! I'll miss you!"
        return B, learn_response  # exit loop
    if not H:
        B = "Please say something!"
        return B, learn_response  # empty input
    # grammar parsing
    subj = set()
    obj = set()
    verb = set()
    triples, root = utilities.parse_sentence(H)
    triples = list(triples)
    for t in triples:
        if t[0][1][:2] == "VB":
            verb.add(t[0][0])
        relation = t[1]
        if relation[-4:] == "subj":
            subj.add(t[2][0])
        if relation[-3:] == "obj":
            obj.add(t[2][0])
    logging.debug(
        "\t"
        + "Subject: "
        + str(subj)
        + "\n"
        + "\t"
        + "Object: "
        + str(obj)
        + "\n"
        + "\t"
        + "Topic: "
        + str(root)
        + "\n"
        + "\t"
        + "Verb: "
        + str(verb)
    )
    subj = list(subj)
    obj = list(obj)
    verb = list(verb)
    proper_nouns = set()
    for t in triples:
        if t[0][1] == "NNP":
            proper_nouns.add(t[0][0])
        if t[2][1] == "NNP":
            proper_nouns.add(t[2][0])
    proper_nouns == list(proper_nouns)
    logging.debug("\t" + "Proper Nouns: " + str(proper_nouns))
    # classification
    classification = utilities.classify_sentence(clf, H)
    # logging.debug(classification)
    if learn_response == LearnResponse.MESSAGE.name:
        databaseconnect.add_to_database(classification, subj, root, verb, H)
        if classification == "C":
            B = databaseconnect.get_chat_response()
        elif classification == "Q":
            B, learn_response = databaseconnect.get_question_response(subj, root, verb)
            if learn_response == LearnResponse.TRAIN_ME.name and (
                len(proper_nouns) == 0
                or (len(proper_nouns) == 1 and H.split(" ", 1)[0] != "Where")
            ):
                databaseconnect.add_learnt_statement_to_database(subj, root, verb)
            if learn_response == LearnResponse.TRAIN_ME.name and (
                len(proper_nouns) >= 2
                or (len(proper_nouns) == 1 and H.split(" ", 1)[0] == "Where")
            ):
                learn_response = LearnResponse.MESSAGE.name
                B = "I will certainly help you with that."
        else:
            B = "Oops! I'm not trained for this yet."
    else:
        B, learn_response = databaseconnect.learn_question_response(H)
    if (
        len(proper_nouns) >= 2
        or (len(proper_nouns) >= 1 and H.split(" ", 1)[0] == "Where")
    ) and len(subj) != 0:
        if subj[0] == "distance":
            if len(proper_nouns) == 2:
                location_dict["origin"] = proper_nouns.pop()
                location_dict["destination"] = proper_nouns.pop()
                origin, destination = (
                    location_dict["origin"],
                    location_dict["destination"],
                )
                googleMapsApiModule.direction(origin, destination)
            else:
                B = "I didn't get that. Can you please give me the origin location?"
                learn_response = LearnResponse.ORIGIN.name
        if len(proper_nouns) == 1:
            location = proper_nouns.pop()
            if subj[0] == "geocoding" or subj[0] == location:
                googleMapsApiModule.geocoding(location)
                learn_response = LearnResponse.MESSAGE.name
                B = "I will certainly help you with that."
    return B, learn_response