import gradio as gr
from transformers import pipeline
import pandas as pd

# Cargar modelo TimesFM pre-entrenado
model = pipeline("time-series-forecasting", 
                 model="google/timesfm-1.0-200m")

def forecast_prices(csv_data, forecast_days):
    # Parsear datos CSV
    df = pd.read_csv(csv_data.name)
    
    # Ejecutar forecasting
    predictions = model(df['price'].tolist(), 
                       num_patches=forecast_days)
    
    return pd.DataFrame(predictions)

interface = gr.Interface(
    fn=forecast_prices,
    inputs=[gr.File(label="CSV histórico"), 
            gr.Number(label="Días a predecir")],
    outputs="dataframe"
)

interface.launch()
transformers>=4.35
gradio
pandas
torch