dream

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import re
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from random import choice
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from common.fact_retrieval import topic_types
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from common.combined_classes import TOPIC_GROUPS
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from common import utils
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MOVIE_SKILL_CHECK_PHRASE = "the recent movie"
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SWITCH_MOVIE_SKILL_PHRASE = (
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    f"Great idea! " f"I watch a lot of movies online. " f"What is {MOVIE_SKILL_CHECK_PHRASE} you've watched?"
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)
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MOVIE_COMPILED_PATTERN = re.compile(
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    r"(movie|film|picture|series|tv[ -]?show|reality[ -]?show|netflix|\btv\b|"
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    r"comedy|comedies|thriller|animation|anime|talk[ -]?show|cartoon|drama|"
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    r"fantasy|watch\b|watching\b|watched\b|youtube|\byou tube\b)",
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    re.IGNORECASE,
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)
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RECOMMEND_REQUEST_PATTERN = re.compile(
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    r"(recommend|advice|suggest)( me)?[a-z0-9 ]+"
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    r"(movie|series|\bshow\b|\btv\b|\bcomed|\bthriller|animation|cartoon|drama|\bfantas|\bwatch)",
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    re.IGNORECASE,
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)
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RECOMMEND_OFFER_PATTERN = re.compile(
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    r"(\bi\b|\bme\b)( to)? (recommend|advice) you[a-z0-9 ]+"
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    r"(movie|series|\bshow\b|\btv\b|\bcomed|\bthriller|animation|cartoon|drama|\bfantas|\bwatch)",
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    re.IGNORECASE,
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)
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NOT_LIKE_NOT_WATCH_MOVIES_TEMPLATE = re.compile(
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    r"(don't|do not|not) (watch|watching|like) (movie|film|picture|series|"
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    r"tv[ -]?show|reality[ -]?show|netflix|\btv\b|comedy|comedies|thriller|"
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    r"animation|anime|talk[ -]?show|cartoon)",
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    re.IGNORECASE,
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)
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NOT_WATCHED_TEMPLATE = re.compile(r"(have|'ve|did|was|had|were)? ?(never|not|n't) (seen|watch)", re.IGNORECASE)
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RECOMMEND_OFFER_RESPONSE = [
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    "Would you like me to recommend you a MOVIE?",
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    "May I recommend you a MOVIE?",
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    "Can I recommend you a MOVIE?",
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]
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RECOMMENDATION_PHRASES = [
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    "I encourage you to watch MOVIE released in YEAR. It has RATING rating for NUM_VOTES votes. Have you seen it?",
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    "I urge you to go and watch MOVIE released in YEAR. It has RATING rating for NUM_VOTES votes. Have you seen it?",
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    "I highly commend you to watch MOVIE released in YEAR, with RATING rating for NUM_VOTES votes. Have you seen it?",
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]
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REPEAT_RECOMMENDATION_PHRASES = ["Okay. Then don't forget: MOVIE released in YEAR."]
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WOULD_YOU_LIKE_TO_CONTINUE_TALK_ABOUT_MOVIES = [
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    "Would you like to continue our conversation about movies?",
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    "Would you like to continue to chat about movies?",
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    "Do you want to continue to talk about movies?",
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]
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ABOUT_MOVIE_TITLES_PHRASES = [
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    # "What is the name of the last movie you watched?",
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    "What is the best movie you have seen recently?",
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    # "What is the funniest movie you have ever seen?",
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    "What movie you could watch over and over again?",
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    # "What is the most romantic movie you have ever seen?",
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    # "What is the scariest movie you have ever seen?",
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    "What is your favorite TV series?",
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    # "What TV show are you watching these days?",
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    "What TV series did you watch on weekends?",
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    # "What TV show do you watch when you need to escape the real world?",
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    "What movie did you watch on weekends?",
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]
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WHAT_IS_YOUR_FAVORITE_MOMENT_PHRASES = [
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    "Do you remember how 'MOMENT'? Did you like this movie moment?",
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    "Remember how 'MOMENT'? I suppose, you like this moment?",
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    "Do you think that when 'MOMENT' was one of the most impressive moments?",
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]
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WHAT_IS_YOUR_FAVORITE_MOMENT_NO_PLOT_FOUND_PHRASES = [
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    "Did you like how characters developed through?",
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    "Do you think the background of the filming made a significant contribution to the picture?",
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    "Did you like the soundtrack?",
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]
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WHAT_OTHER_MOVIE_TO_DISCUSS = "What other movie you'd like to discuss?"
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CLARIFY_WHAT_MOVIE_TO_DISCUSS = "Can you say again what movie you'd like to discuss?"
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CELEB_ACTOR_PHRASES = ["What is your favourite movie with this actor?"]
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WHAT_MOVIE_RECOMMEND = "What movie can you recommend to your friends?"
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def skill_trigger_phrases():
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    return [SWITCH_MOVIE_SKILL_PHRASE] + ABOUT_MOVIE_TITLES_PHRASES + [WHAT_MOVIE_RECOMMEND]
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ABOUT_MOVIE_PERSONS_PHRASES = [
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    "What movie star would you most like to meet?",
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    "Who is your favorite actor or actress?",
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    "Who is your favorite director?",
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    "Which famous person would you like to have for a best friend?",
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]
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PRAISE_ACTOR_TEMPLATES = [
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    "The performance of {name} was outstanding!",
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    "{name}'s acting was so subtle!",
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    "The acting of {name} was exceptionally good!",
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    "I was so impressed by {name}'s performance!",
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]
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PRAISE_VOICE_ACTOR_TEMPLATES = [
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    "I love {name}'s voice! Great performance.",
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    "I reckon {name} is great in voicing!",
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]
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TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS = {
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    "director": "I think the director {director} achieved a perfect chemistry between characters.",
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    "writer": "In my humble opinion the writer {writer} did a brilliant job creating such an intricate plot.",
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    "visuals": "I was particularly impressed by visual part of the movie.",
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}
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DIFFERENT_SCRIPT_TEMPLATES = {
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    "never_heard_about_template": [
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        "I've never heard about SUBJECT before.",
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        "I've never heard about SUBJECT previously.",
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    ],
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    "opinion_request_about_movie": [
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        "What do you think about this TYPE?",
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        "What is your view on this TYPE?",
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        "What is your opinion on this TYPE?",
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    ],
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    "heard_about_template": [
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        "Yeah, I've heard about SUBJECT,",
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        "Yeah, I know SUBJECT,",
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        "I've got what you are talking about.",
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    ],
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    "clarification_template": [
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        "Did I get correctly that you are talking about",
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        "Am I right in thinking that you are talking about",
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        "Did I get correctly that you meant",
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        "Am I right in thinking that you meant",
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    ],
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    "sorry_didnt_get_title": [
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        "Sorry, I could not get what TYPE you are talking about.",
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        "Sorry, I didn't get what TYPE you meant.",
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    ],
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    "lets_talk_about_other_movie": [
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        "Let's talk about some other movie.",
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        "Maybe you want to talk about some other movie.",
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        "Do you want to discuss some other movie.",
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    ],
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    "user_opinion_comment": {
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        "positive": ["Cool!", "Great!", "Nice!"],
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        "neutral": ["Okay.", "Well.", "Hmm.."],
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        "negative": ["I see.", "That's okay.", "Okay."],
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    },
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    "didnt_get_movie_title_at_all": [
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        "Sorry, I didn't get the title, could you, please, repeat it.",
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        "Sorry, I didn't understand the title, could you, please, repeat it.",
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        "Sorry, I didn't catch the title, could you, please, repeat it.",
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        "Sorry, I didn't get the title, can you, please, repeat it.",
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    ],
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    "dont_know_movie_title_at_all": [
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        "Sorry, probably I've never heard about this TYPE.",
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        "Sorry, maybe I just have never heard about this TYPE.",
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        "Well, probably I've never heard about this TYPE.",
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    ],
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    "lets_move_on": ["Let's move on.", "Okay.", "Hmmm.", "Huh.", "Aha.", ""],
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    "can_you_imagine": ["Did you know that", "Can you imagine that", "Have you heard that"],
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}
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ACKNOWLEDGEMENT_LIKES_MOVIE = [
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    "So cool! I like it too! You have a good eye in movies.",
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    "Great! Seems like you're well versed in movies.",
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    "You've got a pretty sophisticated knowledge of movies.",
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    "I'm glad you like it, it's a really nice film.",
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    "Amazing! Agree with you! You have a excellent eye in movies.",
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    "Wow! I see you're perfectly versed in movies.",
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    "Yeah, it's a really amazing film.",
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]
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def get_movie_template(category, subcategory=None, movie_type="movie"):
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    if subcategory is not None:
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        return (
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            choice(DIFFERENT_SCRIPT_TEMPLATES[category].get(subcategory, ""))
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            .replace("TYPE", movie_type)
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            .replace("SUBJECT", choice(["it", f"this {movie_type}"]))
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        )
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    else:
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        return (
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            choice(DIFFERENT_SCRIPT_TEMPLATES[category])
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            .replace("TYPE", movie_type)
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            .replace("SUBJECT", choice(["it", f"this {movie_type}"]))
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        )
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def praise_actor(name, animation):
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    tmpl = choice(PRAISE_VOICE_ACTOR_TEMPLATES if animation else PRAISE_ACTOR_TEMPLATES)
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    return tmpl.format(name=name)
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def praise_director_or_writer_or_visuals(director, writer):
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    if director is None:
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        if writer is None:
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            phrase = TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS["visuals"]
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        else:
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            phrase = TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS["writer"].format(writer=writer)
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    else:
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        if writer is None:
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            phrase = TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS["director"].format(director=director)
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        else:
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            praise_director = choice([True, False])
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            if praise_director:
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                phrase = TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS["director"].format(director=director)
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            else:
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                phrase = TRY_PRAISE_DIRECTOR_OR_WRITER_OR_VISUALS["writer"].format(writer=writer)
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    return phrase
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def extract_movies_names_from_annotations(annotated_uttr, check_full_utterance=False):
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    movies_titles = None
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    if "entity_detection" in annotated_uttr["annotations"]:
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        movies_titles = []
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        entities = utils.get_entities(annotated_uttr, only_named=False, with_labels=True)
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        for ent in entities:
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            if ent.get("label", "") == "videoname":
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                movies_titles += [ent["text"]]
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    # for now let's remove full utterance check but add entity_linking usage!
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    if not movies_titles:
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        # either None or empty list
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        if "wiki_parser" in annotated_uttr["annotations"]:
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            movies_titles = []
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            for ent_name, ent_dict in annotated_uttr["annotations"]["wiki_parser"].get("entities_info", {}).items():
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                instance_of_types = [el[0] for el in ent_dict.get("instance of", [])]
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                instance_of_types += [el[0] for el in ent_dict.get("types_2hop", [])]
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                if (
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                    len(set(instance_of_types).intersection(set(topic_types["film"]))) > 0
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                    and ent_dict.get("token_conf", 0.0) >= 0.5
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                    and ent_dict.get("conf", 0.0) >= 0.5
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                ):
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                    movies_titles += [ent_dict.get("entity_label", ent_name).lower()]
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    # if check_full_utterance:
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    #     movies_titles += [re.sub(r"[\.\?,!]", "", annotated_uttr["text"]).strip()]
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    return movies_titles
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def about_movies(annotated_utterance):
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    found_topics = utils.get_topics(annotated_utterance, probs=False, which="all")
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    if any([topic in found_topics for topic in TOPIC_GROUPS["movies"]]):
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        return True
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    elif re.findall(MOVIE_COMPILED_PATTERN, annotated_utterance["text"]):
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        return True
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    else:
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        return False
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