dream

1
TOPIC_TO_EVENT_QUESTIONS = [
2
    "So speaking of target_topic, this happened lately: target_event. Have you heard about it?",
3
    "By the way, have you heard the news? target_event. Sounds familiar?",
4
    "Oh, target_topic. You know what, I've heard that: target_event. Have you heard about this?",
5
]
6

7
EVENT_TO_PERSON_QUESTIONS = [
8
    "You have a great taste! Well usually I don't like talking about people but... target_person, you know, "
9
    "is quite an target_judgement target_occupation.",
10
    "You interests are quite sound to me! Now, well, it's not in my habit to talk about people but... "
11
    "this target_person, yeah, is a rather target_judgement target_occupation.",
12
    "We have so much in common! So, huh, usually I'm not that into target_occupations "
13
    "but target_person, well, piqued my interest. "
14
    "target_judgement target_occupation.",
15
]
16

17
AGREEMENT_PROMPTS = [
18
    "Do you agree?",
19
    "Isn't it so?",
20
    "Does it sound right to you?",
21
    "Are you with me on it?",
22
    "Right?",
23
    "You agree right uh?",
24
    "You know?",
25
]
26

27
# Source: https://content.cambly.com/2016/07/31/lesson-22-saying-sorry/
28
NOT_INTERESTED_IN_PERSON_ACKNOWLEDGEMENTS = [
29
    "Oh I see.",
30
    "Yay.",
31
    "Well.",
32
    "Rrright.",
33
    "Sorry.",
34
    "Regret for mentioning that.",
35
    "Please forgive me.",
36
    "Apologies.",
37
    "Pardon me.",
38
    "Excuse me.",
39
    "My fault.",
40
]
41

42
CHANGE_TO_OTHER_PERSON_QUESTIONS = [
43
    "Speaking of target_topic, do you know what's happened about target_person? "
44
    "To me, target_person is an target_judgement target_occupation, too.",
45
    "Anyways, as I was thinking about target_topic, I wondered about someone else... "
46
    "Right, target_person is a target_judgement target_occupation, too.",
47
    "Gotcha... So, speaking of target_topic, it reminded me about target_person. "
48
    "Yeah, target_judgement target_occupation, too.",
49
]
50

51
REACTION_TO_YOUNG_AGE = {
52
    "Liked": [
53
        "Gosh I'd love to achieve so much at such age!",
54
        "Wish I could be such a target_judgement target_occupation at such age.",
55
        "target_gender_is too young for being a target_occupation.",
56
    ],
57
    "Disliked": [
58
        "Gosh not sure if target_gender deserves it! Are you with me on it?",
59
        "Wish it was me, not target_gender_im. I could be a better target_occupation than target_gender_im! "
60
        "Do you think so?",
61
        "For god's sake, why did target_gender even think target_gender can be a target_occupation. "
62
        "Do you think the same?",
63
    ],
64
}
65

66
REACTION_TO_CREATIVE_WORK = {
67
    "Liked": [
68
        "really loved target_gender_eir target_creative_work: target_work_name.",
69
        "enjoyed target_gender_eir target_creative_work: target_work_name.",
70
        "target_gender_eir target_creative_work, target_work_name, touched my heart.",
71
        "target_gender_eir target_creative_work target_work_name made me cry.",
72
    ],
73
    "Disliked": [
74
        "Really didn't like target_gender_eir target_creative_work: target_work_name. Are you with me on it?",
75
        "Dislike target_gender_eir target_creative_work: target_work_name. Do you feel the same I wonder?",
76
        "target_gender_eir target_creative_work, target_work_name, mostly felt like "
77
        "an empty story to me. Sounds familiar?",
78
        "target_gender_eir target_creative_work target_work_name made me sad. What about you?",
79
    ],
80
}
81

82
REACTION_TO_SPORT = {
83
    "Liked": [
84
        "Really love target_sport_name.",
85
        "Enjoy watching target_sport_name.",
86
        "target_sport_name is awesome.",
87
        "target_sport_name is the best sport.",
88
    ],
89
    "Disliked": [
90
        "Really don't like target_sport_name. Are you with me on this?",
91
        "Dislike target_sport_name. Is it the same for you?",
92
        "target_sport_name is boring to me. Sounds similar?",
93
        "Watching target_sport_name makes me sleepy. What about you?",
94
    ],
95
}
96

97
GENERIC_REACTION_TO_CREATIVE_WORK = {
98
    "Liked": [
99
        "Really loved their target_creative_works. Do you have a favorite one?",
100
        "Enjoyed their target_creative_works. Do you have a favorite one?",
101
        "Their target_creative_works touched my heart. What's your favorite one?",
102
        "Their target_creative_works made me cry. Was there a such one for you?",
103
    ],
104
    "Disliked": [
105
        "Really didn't like their target_creative_work. Anyways... What's your take?",
106
        "Dislike their target_creative_work. What about you?",
107
        "Their target_creative_works mostly felt like an empty story to me. Is it so for you, too?",
108
        "Their target_creative_works made me sad. I don't like to be sad... You?",
109
    ],
110
}
111

112
ASK_ABOUT_DATING = [
113
    "Do you know whom target_gender_is dating? I heard it's target_partner.",
114
    "Have you heard whom target_gender_is dating by the way? target_person."
115
    "Someone told me target_gender_is dating... It's target_partner.",
116
    "Guess you don't know whom target_gender_is dating! target_partner!",
117
]
118

119
TARGET_JUDGEMENTS_FOR_EMOTION = [
120
    {"Emotion": "Liked", "Judgements": ["cool", "awesome", "wonderful", "fantastic", "the best"]},
121
    {"Emotion": "Disliked", "Judgements": ["obnoxious", "terrible", "lousy", "bad", "uninspiring"]},
122
]
123

124
REACTION_TO_SPORT = {
125
    "Liked": [
126
        "target_gender_eir team, target_sport_team, is awesome.",
127
        "Like target_gender_eir team - target_sport_team.",
128
        "Root for target_sport_team - target_gender_eir team.",
129
        "Go target_sport_team!",
130
    ],
131
    "Disliked": [
132
        "Well, target_sport_team used to be good but... Are you with me on this?",
133
        "Not into target_gender_eir team - target_sport_team. What about you?",
134
        "target_sport_team doesn't know how to play well. Do you also think so?",
135
        "Watching target_sport_name makes me sleepy. Is that the same for you?",
136
    ],
137
}
138

139
GENERIC_REACTION_TO_SPORT = {
140
    "Liked": [
141
        "Really love target_sport_name.",
142
        "Enjoy watching target_sport_name.",
143
        "target_sport_name is awesome.",
144
        "target_sport_name is the best sport.",
145
    ],
146
    "Disliked": [
147
        "Really don't like target_sport_name. Are you with me on it?",
148
        "Dislike target_sport_name. Is it the same for you?",
149
        "target_sport_name is boring to me. What about you?",
150
        "Watching target_sport_name makes me sleepy. Sounds similar?",
151
    ],
152
}
153

154
SIMPLE_OPINION_ABOUT_LIKED_PERSON_PREVIOUSLY_MENTIONED_BY_BOT = [
155
    "target_gender_is awesome!",
156
    "target_gender_is cool!",
157
    "target_gender_is wonderful!",
158
]
159

160
SIMPLE_OPINION_ABOUT_DISLIKED_PERSON_PREVIOUSLY_MENTIONED_BY_BOT = [
161
    "target_gender_is uninspiring.",
162
    "target_gender_is boring.",
163
    "target_gender_is unimportant.",
164
]
165

166
SIMPLE_REACTION_TO_PERSON_PREVIOUSLY_MENTIONED_BY_BOT = ["So you say that?", "Hmmm?", "Interesting..."]
167

168
# REACTION_TO_USER_SPEECH_FUNCTION = {
169
#     "React.Respond.Support.Register" : [
170
#         "So you say that?",
171
#         "Hmmm?",
172
#         "Interesting..."
173
#         ],
174
#     "React.Respond.Support.Reply.Agree" : [
175
#         "Oh, keep going!",
176
#         "Please elaborate",
177
#         "Want to know more!"
178
#     ],
179
#     "React.Respond.Support.Reply.Affirm" : [
180
#         "Why do you think so?",
181
#         "Curious what do you mean",
182
#         "Intrigued... Keep going"
183
#     ]
184
# }
185

186

187
REACTION_TO_USER_OPINION_ABOUT_PERSON = {
188
    "Other": ["So you say that?", "Hmmm?", "Interesting..."],
189
    "Liked": ["Oh, keep going!", "Please elaborate.", "Want to know more!"],
190
    "Disliked": ["Why do you think so?", "Curious what do you mean?", "Intrigued... Keep going."],
191
}
192

193
SIMPLE_OPINION_ABOUT_PERSON_PREVIOUSLY_MENTIONED_BY_USER = ["No idea?", "What do you think?", "I guess?"]
194

195
SIMPLE_REACTION_TO_PERSON_PREVIOUSLY_MENTIONED_BY_USER = ["Right... So?", "Aha...?", "And...?"]
196

197
REACTION_TO_USER_MENTIONING_SOMEONE_RELATED_TO_WHO_USER_MENTIONED_BEFORE = ["yes yes", "aha aha", "huh yeah...", "hmm"]
198

199
OPINION_TO_USER_MENTIONING_SOMEONE_RELATION_TO_WHO_USER_MENTIONED_BEFORE = [
200
    "target_gender_is a rather interesting person.",
201
    "target_gender_is, huh..., fascinating.",
202
    "target_gender_is, hmm, intriguing.",
203
    "target_gender_is, well, impressive.",
204
]
205

206
REACTION_TO_USER_MENTIONING_SOMEONE_RELATED_TO_WHO_BOT_MENTIONED_BEFORE = [
207
    "Aha, what a jump.",
208
    "Interesting... keep going.",
209
    "Rather interesting... and?",
210
    "Huh, quite interesting.",
211
]
212

213
OPINION_TO_USER_MENTIONING_SOMEONE_RELATION_TO_WHO_BOT_MENTIONED_BEFORE = [
214
    "target_gender_is a rather interesting person.",
215
    "target_gender_is, huh..., fascinating.",
216
    "target_gender_is, hmm, intriguing.",
217
    "target_gender_is, well, impressive.",
218
]
219

220
CONFUSED_WHY_USER_MENTIONED_PERSON = [
221
    "Hmm, I'm confused... Why did you mention this person?",
222
    "I'm lost. Why did you mention this person?",
223
    "Afraid I don't know why you mentioned this person?",
224
]
225

226
CONFUSED_WHY_USER_MENTIONED_PEOPLE = [
227
    "Whoa whoa whoa. Who are all of these people?",
228
    "Ok that's too many people to think of. Can't keep them all in my mind!",
229
    "Hey keep it easy I can't remember all of these people in my mind!",
230
]
231

232
OPINION_TO_USER_MENTIONING_SOMEONE_NEW = [
233
    "target_gender_is a rather interesting person.",
234
    "target_gender_is, huh..., fascinating.",
235
    "target_gender_is, hmm, intriguing.",
236
    "target_gender_is, well, impressive.",
237
]
238

239
WANT_TO_HEAR_ANOTHER_FACT = [
240
    "Would you want to hear an interesting fact about target_gender_im?",
241
    "One more fact about target_gender_im?",
242
    "Wanna know another interesting thing about target_gender_im?",
243
    "Wanna know more about target_gender_im?",
244
]
245

246
WAIT_BUT_WHY_QUESTIONS = ["Wait but why?", "Oh... Why, I wonder?", "Hmmm, but why?"]
247

248
# CoBot Topics: Entertainment_Movies, Entertainment_Music, Entertainment_Books, Entertainment_General, Sports, Politics,
249
# Science_and_Technology, Phatic, Interactive, Inappropriate_Content, Other
250

251
# Entertainment_Movies
252
# Men: https://epiloguers.com/best-actors-of-the-decade/
253
# Women: https://epiloguers.com/best-actresses-of-the-2010s-top-10/
254

255
# Entertainment_Music
256
# Source: https://www.billboard.com/charts/decade-end/top-artists
257

258
# Entertainment_Books
259
# Source:
260
# https://www.pastemagazine.com/books/best-of-the-decade/best-novels-of-the-decade-2010s-books-list/#8-the-leavers
261

262
# Entertainment_General
263
# Source:
264
# https://www.yardbarker.com/entertainment/articles/25_celebrities_who_emerged_as_superstars_in_the_2010s/s1__30402335
265

266
# Sports
267
# Source:
268
# https://www.usatoday.com/story/sports/2019/12/19/decade-best-ranking-top-50-athletes-over-last-10-years/4399929002/
269

270
# Politics
271
# Source: https://thefuelonline.com/most-influential-politicians-of-the-decade/
272

273
# Science & Technology
274
# Source: https://www.sydney.edu.au/news-opinion/news/2019/12/17/10-of-our-biggest-stories-from-the-last-decade.html
275

276
TOPICS_TO_OCCUPATIONS = [
277
    {"Topic": "Entertainment_Movies", "Occupation": "actor"},
278
    {"Topic": "Entertainment_Music", "Occupation": "musician"},
279
    {"Topic": "Entertainment_Books", "Occupation": "writer"},
280
    {"Topic": "Entertainment_General", "Occupation": "celebrity"},
281
    {"Topic": "Sports", "Occupation": "sportsperson"},
282
    {"Topic": "Politics", "Occupation": "politician"},
283
    {"Topic": "Science_and_Technology", "Occupation": "technologist"},
284
    {"Topic": "Phatic", "Occupation": None},
285
    {"Topic": "Interactive", "Occupation": None},
286
    {"Topic": "Inappropriate_Content", "Occupation": None},
287
    {"Topic": "Other", "Occupation": None},
288
]
289

290
# Science and Technology: removing scientists for the time being
291
# "Dr Anthony Weiss",
292
# "Dr Rick Shine",
293
# "Dr Michael Anderson",
294
# "Dr Greg Neely",
295
# "Dr Raymond Man-Tat Lau",
296
# "Dr Ruth Coiagiuri",
297
# "Dr Kate Edwards",
298
# "Dr Robert Booy",
299
# "Dr James Gillespie",
300
# "Dr Anne-Marie Boxall",
301
# "Dr Muireann Irish",
302
# "Dr Stephen Simpson",
303
# "Dr Samantha Solon-Biet"
304

305
# TOPICS_TO_PEOPLE_MAPPINGS = [
306
#     {
307
#         "Topic": "Entertainment_Movies",
308
#         "People": [
309
#             "Christian Bale",
310
#             "Jake Gyllenhaal",
311
#             "Leonardo DiCaprio",
312
#             "Tom Hardy",
313
#             "Joaquin Phoenix",
314
#             "Hugh Jackman",
315
#             "Brad Pitt",
316
#             "Ryan Gosling",
317
#             "Tom Cruise",
318
#             "Bradley Cooper",
319
#             "Amy Adams",
320
#             "Scarlett Johansson",
321
#             "Emma Stone",
322
#             "Anne Hathaway",
323
#             "Emily Blunt",
324
#             "Margot Robbie",
325
#             "Jennifer Lawrence",
326
#             "Rachel McAdams",
327
#             "Saoirse Ronan",
328
#             "Amanda Seyfried",
329
#         ],
330
#     },
331
#     {
332
#         "Topic": "Entertainment_Music",
333
#         "People": [
334
#             "Ed Sheeran",
335
#             "Justin Bieber",
336
#             "Katy Perry",
337
#             "Maroon 5",
338
#             "Post Malone",
339
#             "Lady Gaga",
340
#             "Ariana Grande",
341
#             "Imagine Dragons",
342
#             "The Weeknd",
343
#             "Nicki Minaj",
344
#             "Eminem",
345
#             "Luke Bryan",
346
#             "P!nk",
347
#             "One Direction",
348
#             "Justin Timberlake",
349
#             "Kendrick Lamar",
350
#             "Lady A",
351
#             "Beyonce",
352
#             "Jason Aldean",
353
#             "Sam Smith",
354
#         ],
355
#     },
356
#     {
357
#         "Topic": "Entertainment_Books",
358
#         "People": [
359
#             "Colson Whitehead",
360
#             "Madeline Miller",
361
#             "Yaa Gyasi",
362
#             "Lauren Groff",
363
#             "George Saunders",
364
#             "Karen Russell",
365
#             "Jemisin",
366
#             "Lisa Ko",
367
#             "Emily St. John Mandel",
368
#             "Jesmyn Ward",
369
#             "Brandon Sanderson",
370
#             "John Darnielle",
371
#             "Celeste Ng",
372
#             "Ta-Nehisi Coates",
373
#             "Donna Tartt",
374
#             "Erin Morgenstern",
375
#             "Akhil Sharma",
376
#             "Zadie Smith",
377
#             "Patrick Rothfuss",
378
#             "Kate Atkinson",
379
#         ],
380
#     },
381
#     {
382
#         "Topic": "Entertainment_General",
383
#         "People": [
384
#             "Jennifer Lawrence",
385
#             "Chris Pratt",
386
#             "Brie Larson",
387
#             "Benedict Cumberbatch",
388
#             "Phoebe Waller-Bridge",
389
#             "Oscar Isaac",
390
#             "Emma Stone",
391
#             "Adam Driver",
392
#             "Sophie Turner",
393
#             "Donald Glover",
394
#             "Melissa McCarthy",
395
#             "Eddie Redmayne",
396
#             "Amy Schumer",
397
#             "Rami Malek",
398
#             "Margot Robbie",
399
#             "Andrew Garfield",
400
#             "Karen Gillan",
401
#             "Chris Hemsworth",
402
#             "Millie Bobbie Brown",
403
#             "Finn Wolfhard",
404
#         ],
405
#     },
406
#     {
407
#         "Topic": "Sports",
408
#         "People": [
409
#             "LeBron James",
410
#             "Serena Williams",
411
#             "Tom Brady",
412
#             "Simone Biles",
413
#             "Usain Bolt",
414
#             "Mike Trout",
415
#             "Steph Curry",
416
#             "Lionel Messi",
417
#             "Michael Phelps",
418
#             "Novak Djokovic",
419
#             "Katie Ledecky",
420
#             "Kevin Durant",
421
#             "Rafel Nadal",
422
#             "Cristiano Ronaldo",
423
#             "Aaron Rodgers",
424
#             "Roger Federer",
425
#             "Sidney Crosby",
426
#             "Clayton Kershaw",
427
#             "Alex Ovechkin",
428
#             "Carli Lloyd",
429
#         ],
430
#     },
431
#     {
432
#         "Topic": "Politics",
433
#         "People": [
434
#             # "Donald Trump",
435
#             # "Barack Obama",
436
#             # "Hillary Clinton",
437
#             # "Brett Kavanaugh",
438
#             # "Nancy Pelosi",
439
#             # "Ted Cruz",
440
#             # "Marco Rubio",
441
#             # "Beto O'Rourke",
442
#             # "Alexandria Ocasio-Cortez",
443
#             # "Arnold Schwarzenegger",
444
#             # "Joe Biden"
445
#         ],
446
#     },
447
#     {
448
#         "Topic": "Science_and_Technology",
449
#         "People": [
450
#             "Elon Musk",
451
#             "Jeff Bezos",
452
#             "Bill Gates",
453
#             "Tim Timberlake",
454

455
#             # "Philip Scheinfeld",
456
#             # "Jayson Waller",
457
#             # "Alfredo Delgado",
458
#             # "Katie Hamilton",
459
#             # "Billionaire Barbie",
460
#             # "Alan Belcher",
461
#             # "Los Silva",
462
#             # "Van Taylor",
463
#             # "David Granados",
464
#             # "Randall Emmett",
465
#             # "Rob Deutsch",
466
#             # "Adam Weitsman",
467
#             # "David Meltzer",
468
#             # "Brady Bell",
469
#             # "Andrew Andrawes",
470
#             # "Jordan Montgomery",
471
#             # "Eric Marcus",
472
#             # "Ben Newman",
473
#             # "Tai Lopez",
474
#             # "Grant Cardone",
475
#             # "Rudy Mawer",
476
#             # "Paul Vigario",
477
#             # "Amber Voight",
478
#             # "Cesar Gomez",
479
#         ],
480
#     },
481
#     {"Topic": "Phatic", "People": []},
482
#     {"Topic": "Interactive", "People": []},
483
#     {"Topic": "Inappropriate_Content", "People": []},
484
#     {"Topic": "Other", "People": []},
485
# ]
486