app.py

import gradio as gr
import plotly.graph_objects as go
from gradio.themes.base import Base
from gradio.themes.utils import colors, fonts, sizes
from typing import Iterable

class CustomTheme(Base):
    def __init__(
        self,
        *,
        primary_hue: colors.Color | str = colors.green,
        secondary_hue: colors.Color | str = colors.purple,
        neutral_hue: colors.Color | str = colors.gray,
        spacing_size: sizes.Size | str = sizes.spacing_md,
        radius_size: sizes.Size | str = sizes.radius_md,
        text_size: sizes.Size | str = sizes.text_md,
        font: fonts.Font | str | Iterable[fonts.Font | str] = (
            fonts.GoogleFont("Nunito"),
            "ui-sans-serif",
            "sans-serif",
        ),
        font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
            fonts.GoogleFont("Nunito"),
            "ui-monospace",
            "monospace",
        ),
    ):
        super().__init__(
            primary_hue=primary_hue,
            secondary_hue=secondary_hue,
            neutral_hue=neutral_hue,
            spacing_size=spacing_size,
            radius_size=radius_size,
            text_size=text_size,
            font=font,
            font_mono=font_mono,
        )
        super().set(
            body_background_fill="radial-gradient(#32CD32 2px, transparent 2px), radial-gradient(#8A2BE2 4px, transparent 4px)",
            body_text_color="#282828",
            block_background_fill="#ffffff",
            block_title_text_color="#32CD32",
            block_label_text_color="#32CD32",
            button_primary_background_fill="#32CD32",
            button_primary_text_color="#FFFFFF",
        )

custom_theme = CustomTheme()

def analyze_video(file_path):
    # Dummy sentiment analysis result
    sentiments = {
        "Joy": 12,
        "Trust": 10,
        "Fear": 8,
        "Surprise": 5,
        "Sadness": 7,
        "Disgust": 4,
        "Anger": 6,
        "Anticipation": 9
    }
    
    labels = list(sentiments.keys())
    values = list(sentiments.values())
    
    fig = go.Figure(data=go.Scatterpolar(
      r=values + [values[0]],
      theta=labels + [labels[0]],
      fill='toself'
    ))

    fig.update_layout(
      polar=dict(
        radialaxis=dict(
          visible=True,
          range=[0, max(values) + 2]
        )),
      showlegend=False
    )

    return fig

# Custom CSS for additional styling
css = """
#video_upload {
    background-color: #ffffff;
    color: #282828;
    border: 2px solid #32CD32;
    border-radius: 10px;
    padding: 10px;
    margin: 10px 0;
}
#submit_button {
    background-color: #32CD32;
    color: #FFFFFF;
    border: 2px solid #FFFFFF;
    border-radius: 10px;
    padding: 10px;
    margin: 10px 0;
}
#submit_button:hover {
    background-color: #3BFF3B;
    color: #FFFFFF;
    border: 2px solid #FFFFFF;
}
label[for="video_upload"] {
    color: #32CD32 !important;
}
h1 {
    color: white;
    text-shadow: -1px -1px 0 #32CD32, 1px -1px 0 #32CD32, -1px 1px 0 #32CD32, 1px 1px 0 #32CD32;
    font-size: 3em !important;
    font-weight: bold;
    text-transform: uppercase;
}
h3 {
    color: #32CD32;
}
.centered-markdown {
    text-align: center;
    background-color: #ffffff;
    border: 2px solid #32CD32;
    border-radius: 10px;
    padding: 10px;
}
#zeitgeist-title {
    font-size: 3em !important;
    font-weight: bold;
    text-transform: uppercase;
    background: none !important;
}
"""

with gr.Blocks(theme=custom_theme, css=css) as demo:
    with gr.Column():
        #gr.Markdown("# Zeitgeist AI", elem_classes="centered-markdown", elem_id="zeitgeist-title")
        #gr.Markdown("### Discover the emotional impact of your videos.", elem_classes="centered-markdown")
        #gr.Markdown("**Upload your video file to get started.**", elem_classes="centered-markdown")
        with gr.Row():
            video_upload = gr.File(label="Upload Video File", type="filepath", elem_id="video_upload")
            output = gr.Plot(label="Sentiment Analysis Results", elem_id="output_plot")
        submit_button = gr.Button("Analyze Video", elem_id="submit_button")
        submit_button.click(fn=analyze_video, inputs=video_upload, outputs=output)

demo.launch()