def wrangle_like_data()

in app/app.py [0:0]

• 43 lines of code
• 18 McCabe index (conditional complexity)

def wrangle_like_data(x: gr.LikeData, history) -> DataFrame:
    """Wrangle conversations and liked data into a DataFrame"""

    if isinstance(x.index, int):
        liked_index = x.index
    else:
        liked_index = x.index[0]

    output_data = []
    for idx, message in enumerate(history):
        if isinstance(message, gr.ChatMessage):
            message = message.__dict__
        if idx == liked_index:
            if x.liked is True:
                message["metadata"] = {"title": "liked"}
            elif x.liked is False:
                message["metadata"] = {"title": "disliked"}

        if message["metadata"] is None:
            message["metadata"] = {}
        elif not isinstance(message["metadata"], dict):
            message["metadata"] = message["metadata"].__dict__
            
        rating = message["metadata"].get("title")
        if rating == "liked":
            message["rating"] = 1
        elif rating == "disliked":
            message["rating"] = -1
        else:
            message["rating"] = 0

        message["chosen"] = ""
        message["rejected"] = ""
        if message["options"]:
            for option in message["options"]:
                if not isinstance(option, dict):
                    option = option.__dict__
                message[option["label"]] = option["value"]
        else:
            if message["rating"] == 1:
                message["chosen"] = message["content"]
            elif message["rating"] == -1:
                message["rejected"] = message["content"]

        output_data.append(
            dict(
                [(k, v) for k, v in message.items() if k not in ["metadata", "options"]]
            )
        )

    return history, DataFrame(data=output_data)