import gradio as gr
import pandas as pd
import numpy as np
from scipy.fft import fft, fftfreq
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM, Dense
import matplotlib.pyplot as plt

def load_data(input_source):
    """Handle both uploaded files and URLs"""
    if isinstance(input_source, str) and input_source.startswith("http"):
        # Load from URL
        df = pd.read_csv(
            input_source,
            engine='python',
            on_bad_lines='warn',
            encoding='utf-8'
        )
    else:
        # Load from uploaded file
        df = pd.read_csv(
            input_source.name,
            engine='python',
            on_bad_lines='warn',
            encoding='utf-8'
        )
    
    # Common cleaning steps
    df = df.drop(columns=['Province/State', 'Lat', 'Long'], errors='ignore')
    df = df.groupby('Country/Region').sum().T
    df.index = pd.to_datetime(df.index)
    df['Global'] = df.sum(axis=1)
    return df['Global'].diff().fillna(0)

def analyze_data(input_source):
    try:
        data = load_data(input_source)
        
        # Analysis logic
        N = len(data)
        yf = fft(data.values)
        xf = fftfreq(N, 1)[:N//2]
        cycle_days = int(1/xf[np.argmax(np.abs(yf[0:N//2]))])
        
        # Create plot
        fig, ax = plt.subplots()
        ax.plot(data.index, data.values)
        ax.set_title("COVID-19 Daily New Cases Analysis")
        
        return (
            f"🔮 Analysis Results:\n"
            f"- Cycle: {cycle_days} days\n"
            f"- Latest 30-day average: {data[-30:].mean():.1f} cases/day\n"
            f"- Current trend: {'↑ Rising' if data[-1] > data[-7] else '↓ Falling'}",
            fig
        )
        
    except Exception as e:
        return f"❌ Error: {str(e)}", None

# Create hybrid interface with chat and file upload
with gr.Blocks(theme=gr.themes.Soft()) as app:
    gr.Markdown("# 📊 Data Analysis Bot")
    gr.Markdown("Upload a CSV file or paste a COVID data URL")
    
    with gr.Row():
        with gr.Column():
            file_upload = gr.File(label="Upload CSV", file_count=1)
            url_input = gr.Textbox(label="Or paste URL here")
            submit_btn = gr.Button("Analyze")
        with gr.Column():
            chat = gr.Chatbot(height=400)
            plot_output = gr.Plot()
    
    # Handle both input methods
    submit_btn.click(
        fn=analyze_data,
        inputs=[gr.combine(file_upload, url_input)],
        outputs=[chat, plot_output]
    )
    
    # Example inputs
    gr.Examples(
        examples=[
            ["https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/data/time_series_covid19_confirmed_global.csv"],
            ["sample_data.csv"]  # Upload this via Hugging Face
        ],
        inputs=[url_input]
    )

if __name__ == "__main__":
    app.launch()