def utt_non_punct_dialog(dialog: Dict):
"""
Used by: book_skill
"""
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
return [{"dialogs": [dialog]}]
def alice_formatter_dialog(dialog: Dict) -> List:
# Used by: alice
dialog = utils.get_last_n_turns(dialog, bot_last_turns=4)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
return utils.last_n_human_utt_dialog_formatter(dialog,
last_n_utts=2,
only_last_sentence=True)
def utt_sentseg_punct_dialog(dialog: Dict):
"""
Used by: skill_with_attributes_formatter; punct_dialogs_formatter,
dummy_skill_formatter, base_response_selector_formatter
"""
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="punct_sent")
return [{"dialogs": [dialog]}]
def cobot_formatter_dialog(dialog: Dict):
# Used by: cobot_dialogact_formatter, cobot_classifiers_formatter
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="segments")
utterances_histories = []
for utt in dialog["utterances"]:
utterances_histories.append(utt["text"])
return [{"utterances_histories": [utterances_histories]}]
def topic_recommendation_formatter(dialog: Dict):
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
active_skills, topics = [], []
for utt in dialog["utterances"]:
active_skills.append(utt.get("active_skill", ""))
topics += utt.get("annotations", {}).get("cobot_topics",
{}).get("text", [])
active_skills = [skill for skill in active_skills if skill]
return [{"active_skills": [active_skills], "cobot_topics": [topics]}]
def game_cooperative_skill_formatter(dialog: Dict):
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="punct_sent")
dialog["human"]["attributes"] = {
"game_cooperative_skill":
dialog["human"]["attributes"].get("game_cooperative_skill", {}),
"used_links":
dialog["human"]["attributes"].get("used_links", {}),
}
return [{"dialogs": [dialog]}]
def last_utt_and_history_dialog(dialog: Dict) -> List:
# Used by: topicalchat retrieval skills
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="punct_sent")
sent = dialog["human_utterances"][-1]["annotations"].get(
"spelling_preprocessing", dialog["human_utterances"][-1]["text"])
return [{
"sentences": [sent],
"utterances_histories": [[utt["text"] for utt in dialog["utterances"]]]
}]
def sent_rewrite_formatter_w_o_last_dialog(dialog: Dict) -> List[Dict]:
dialog = utils.get_last_n_turns(dialog, utils.LAST_N_TURNS + 1)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="segments")
utterances_histories = []
annotation_histories = []
for utt in dialog["utterances"][:-1]:
annotation_histories.append(deepcopy(utt["annotations"]))
utterances_histories.append(utt["text"])
return [{
"utterances_histories": [utterances_histories],
"annotation_histories": [annotation_histories]
}]
def convers_evaluator_annotator_formatter(dialog: Dict) -> List[Dict]:
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
conv = dict()
hypotheses = dialog["human_utterances"][-1]["hypotheses"]
conv["hypotheses"] = [h["text"] for h in hypotheses]
conv["currentUtterance"] = dialog["utterances"][-1]["text"]
# cobot recommends to take 2 last utt for conversation evaluation service
conv["pastUtterances"] = [
uttr["text"] for uttr in dialog["human_utterances"]
][-3:-1]
conv["pastResponses"] = [
uttr["text"] for uttr in dialog["bot_utterances"]
][-2:]
return [conv]
def convert_formatter_dialog(dialog: Dict) -> List[Dict]:
# Used by: convert
dialog_20 = utils.get_last_n_turns(dialog, bot_last_turns=20)
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="punct_sent")
return [{
"utterances_histories":
[[utt["text"] for utt in dialog_20["utterances"]]],
"personality": [dialog["bot"]["persona"]],
"num_ongoing_utt": [
utils.count_ongoing_skill_utterances(dialog["bot_utterances"],
"convert_reddit")
],
"human_attributes": [dialog["human"]["attributes"]],
}]
def utt_sentrewrite_modified_last_dialog(dialog: Dict):
# Used by: book_skill_formatter; misheard_asr_formatter, cobot_qa_formatter
all_prev_active_skills = [
uttr.get("active_skill", "") for uttr in dialog["bot_utterances"]
]
all_prev_active_skills = [
skill_name for skill_name in all_prev_active_skills if skill_name
]
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog,
mode="modified_sents")
return [{
"dialogs": [dialog],
"all_prev_active_skills": [all_prev_active_skills]
}]
def hypothesis_histories_list(dialog: Dict):
hypotheses = dialog["human_utterances"][-1]["hypotheses"]
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="segments")
utterances_histories_batch = []
for hyp in hypotheses:
utterances_histories = []
for utt in dialog["utterances"]:
utt_text = utt["text"]
if isinstance(utt_text, list):
utt_text = " ".join(utt_text)
utterances_histories.append(utt_text)
# hyp["text"] is a string. We need to pass here list of strings.
utterances_histories.append(hyp["text"])
utterances_histories_batch.append(utterances_histories)
return [{"utterances_with_histories": utterances_histories_batch}]
def eliza_formatter_dialog(dialog: Dict) -> List[Dict]:
# Used by: eliza_formatter
dialog = utils.get_last_n_turns(dialog)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
history = []
prev_human_utterance = None
for utt in dialog["utterances"]:
if utt["user"]["user_type"] == "human":
prev_human_utterance = utt["annotations"].get(
"spelling_preprocessing", utt["text"])
elif utt["user"]["user_type"] == "bot" and utt[
"active_skill"] == "eliza" and prev_human_utterance is not None:
history.append(prev_human_utterance)
last_utterance = dialog["human_utterances"][-1]["annotations"].get(
"spelling_preprocessing", dialog["human_utterances"][-1]["text"])
return [{
"last_utterance_batch": [last_utterance],
"human_utterance_history_batch": [history],
}]
def base_skill_selector_formatter_dialog(dialog: Dict) -> List[Dict]:
# Used by: base_skill_selector_formatter
dialog = utils.get_last_n_turns(dialog, bot_last_turns=5)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog, mode="punct_sent")
return [{"states_batch": [dialog]}]
def utt_sentrewrite_modified_last_dialog_emotion_skill(dialog: Dict):
dialog = utils.get_last_n_turns(dialog, bot_last_turns=2)
dialog = utils.remove_clarification_turns_from_dialog(dialog)
dialog = utils.replace_with_annotated_utterances(dialog,
mode="modified_sents")
return [{"dialogs": [dialog]}]
