dream

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import logging
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import sentry_sdk
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from os import getenv
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from df_engine.core import Context, Actor
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sentry_sdk.init(getenv("SENTRY_DSN"))
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logging.basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO)
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logger = logging.getLogger(__name__)
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def is_sf(sf_name="Open.Give.Opinion"):
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    def is_sf_handler(ctx: Context, actor: Actor, *args, **kwargs):
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        try:
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            last_utterance = ctx.misc.get("agent", {}).get("dialog", {}).get("human_utterances", {})[-1]
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            utterance_sfcs = last_utterance.get("annotations", {}).get("speech_function_classifier", [])
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        except KeyError:
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            utterance_sfcs = []
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        return sf_name in utterance_sfcs
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    return is_sf_handler
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def is_ext_sf(ext_sf_name="React.Respond.Support.Reply.Agree"):
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    def is_ext_sf_handler(ctx: Context, actor: Actor, *args, **kwargs):
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        return ext_sf_name in ctx.misc.get("ext_sf", [[]])[-1]
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    return is_ext_sf_handler
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def is_midas(midas_name="pos_answer", threshold=0.5):
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    def is_midas_handler(ctx: Context, actor: Actor, *args, **kwargs):
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        try:
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            last_utterance = ctx.misc.get("agent", {}).get("dialog", {}).get("human_utterances", {})[-1]
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            midas = last_utterance.get("annotations", {}).get("midas_classification", [{}])[-1]
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            midas_keys = [key for key, val in midas.items() if val > threshold]
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        except KeyError:
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            midas_keys = []
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        return midas_name in midas_keys
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    return is_midas_handler
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speech_functions = is_sf
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