import gradio as gr
import pandas as pd
import os
import gradio as gr


# List of all audio files to annotate
file_list = pd.read_excel(os.path.join('combined_annotations.xlsx'))

# Initialize an empty DataFrame to store annotations
annotations = pd.DataFrame(columns=['sample_id', 'sentence', 'emotion', 'comments'])
current_index = {"index": 0}  # Dictionary to allow modifying inside functions

def load_example(index):
    """Load the example (audio + text) by index."""
    row = file_list.iloc[index]
    audio_path = os.path.join('files_to_annotate_padded_smaller_emotion_set', row["SAMPLE ID"].split('-')[0], row["SAMPLE ID"] + '.wav')
    print(f"Audio path: {audio_path}, Exists: {os.path.exists(audio_path)}")
    sentence = row["SENTENCE"]

    # If the user already made an annotation for this example, gradio will return said annotation
    previous_annotation = (
        annotations.iloc[index].to_dict() if index < len(annotations) else {"sample_id": row["SAMPLE ID"], "emotion": '',
                                                                            "comments": ''}
    )
    return (sentence, audio_path, previous_annotation['emotion'], previous_annotation["comments"])


def save_annotation(emotions, comments):
    """Save the annotation for the current example."""
    idx = current_index["index"]
    row = file_list.iloc[idx]
    sample_id = row["SAMPLE ID"]
    sentence = row["SENTENCE"]

    # Update or append annotation
    if sample_id in annotations["sample_id"].values:
        annotations.loc[annotations["sample_id"] == sample_id, ["emotion", "comments"]] = \
            [emotions, comments]
    else:
        annotations.loc[len(annotations)] = [sample_id, sentence, emotions, comments]

    annotations.to_csv("annotations.csv", index=False)  # Save to a CSV file
    #return f"Saved annotations for example {idx + 1}"

def next_example(emotions, comments):
    if emotions == '':
        raise gr.Error("Please fill out the emotion section")
    else:
        """Move to the next example."""
        save_annotation(emotions, comments)

        if current_index["index"] < len(file_list) - 1:
            current_index["index"] += 1
            return load_example(current_index["index"])
    #return "End of examples", None, 0, 0, 0, 0, ''


def previous_example(emotion, comments):
    """Move to the previous example."""
    save_annotation(emotion, comments)
    if current_index["index"] > 0:
        current_index["index"] -= 1
        return load_example(current_index["index"])
    return load_example(current_index["index"])

# Gradio Interface

audio_path = 'test.mp3'
with (gr.Blocks() as demo):
    
    
    # Row with audio player
    with gr.Row():
        audio_player = gr.Audio(value=audio_path, label="Audio", type="filepath", interactive=False)

    # Hidden row with corresponding sentence
    with gr.Row():
        with gr.Accordion(label="Click to see the sentence", open=False):
            sentence_text = gr.Textbox(label="Sentence", interactive=False)

    # Row for emotion annotation and confidence
    with gr.Row():        
        emotions = gr.Radio(["Joy", "Sad", "Angry", "Neutral"], label="Predominant Emotion")
        
        confidence = gr.Slider(label="Confidence (%)", minimum=0, maximum=100, step=10)

    # Instructions for emotion annotation
    with gr.Sidebar():
        gr.Textbox()
    

    # Next and Previous Buttons
    with gr.Row():
        next_button = gr.Button("Next Example")
        previous_button = gr.Button("Previous Example")

    comments = gr.Textbox(label="Comments", interactive=True)
    # Initial load
    sentence_text.value, audio_player.value, emotions.value, comments.value = load_example(
        current_index["index"]
    )

    next_button.click(
        next_example,
        inputs=[emotions, comments],
        outputs=[sentence_text, audio_player, emotions, comments],
    )
    previous_button.click(
        previous_example,
        inputs=[emotions, comments],
        outputs=[sentence_text, audio_player, emotions, comments],
    )

demo.launch()