generate_bot_response.py

import spacy
import random 

urw_replies = [u'Happy to help you :)', u'You are more than Welcome! :)', u'No problem, Anytime! :)']
nonsense_replies = [u"Sorry, I don't understand what you are saying", u"Sorry, I cannot help you on that!",
                    u"That's not my area of expertise"]
break_the_ice_replies = [u"Hello, Anything I can do for you?", u"Hi there! How can I help you today?"]
friendly_replies = [u"Sure! ", u"Sure! Let's see what we have here "]

nlp = spacy.load('xx_ent_wiki_sm')
    doc = nlp(message)
    entities_txts = []
    entities_labels = []
    for ent in doc.ents:
        entities_txts.append(ent.text)
        entities_labels.append(ent.label_)

if intent_confidence >= 0.5:
        if intent_type == "laliga_questions":
            history = ""
            for txt, label in zip(entities_txts, entities_labels):
                if label in ['LOC', 'ORG', 'PER']:
                    # retrieve the history of the mentioned location/ organization in the user's message
                    print(txt, label)
                    history = df[(df['Team'] == txt) | (df['Team_alt'] == txt.encode("utf-8"))]['History'] #df.loc[df['Team'] == txt]['History']
                    if len(history) < 1: 
                        continue
                if len(history) >= 1:
                    return random.choice(friendly_replies).encode("utf-8") + history.to_string(header=False, index=False,dtype=str, max_rows=None) #' '.join([s for s in history.values.tolist()])

                return random.choice(nonsense_replies).encode("utf-8")                     
        if intent_type == "city_questions":
            summary = ""
            for txt, label in zip(entities_txts, entities_labels):
                if label in ['LOC', 'ORG', 'PER']:
                    # retrieve an intro of the mentioned location/ organization in the user's message
                    print(txt, label)
                    summary = df[(df['Team'] == txt) | (df['Team_alt'] == txt.encode("utf-8"))]['Summary'] #df.loc[df['Team'] == txt]['Summary']
                    if len(summary) < 1:
                        continue
                if len(summary) >= 1:
                    return random.choice(friendly_replies).encode("utf-8") + summary.to_string(header=False, index=False,dtype=str, max_rows=None) #' '.join([s for s in summary.values.tolist()])
                return random.choice(nonsense_replies).encode("utf-8")
        elif intent_type == "thankyou":
            return random.choice(urw_replies).encode("utf-8")
        elif intent_type == "great":
            return random.choice(break_the_ice_replies).encode("utf-8")

        return random.choice(nonsense_replies).encode("utf-8")
    else:
        return random.choice(nonsense_replies).encode("utf-8")