PriceScopev2 / app.py
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Update app.py
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import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import gradio as gr
title="PRICESCOPE: THE REAL FUTURE OF THE STOCKS"
def plot_forecast(final_year, companies, noise, show_legend, point_style):
start_year = 2020
x = np.arange(start_year, final_year + 1)
year_count = x.shape[0]
plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[point_style]
fig = plt.figure()
ax = fig.add_subplot(111)
for i, company in enumerate(["Google", "Microsoft", "Netflix", "Apple", "Amazon", "Facebook"]):
if company in companies:
series = np.arange(0, year_count, dtype=float)
series = series**2 * (i + 1)
series += np.random.rand(year_count) * noise
ax.plot(x, series, plt_format, label=company)
if show_legend:
plt.legend()
ax.set_xlabel("Year")
ax.set_ylabel("Revenue")
ax.set_title("Pricescope Forecast")
return fig
demo = gr.Interface(
plot_forecast,
[
gr.Radio([2025, 2030, 2035, 2040], label="Project to:"),
gr.CheckboxGroup(["Google", "Microsoft", "Netflix","Apple", "Amazon", "Facebook"], label="Company Selection"),
gr.Slider(1, 100, label="Noise Level"),
gr.Checkbox(label="Show Legend"),
gr.Dropdown(["cross", "line", "circle"], label="Style"),
],
gr.Plot(label="forecast"),
title = title
)
import gradio as gr
gr.Interface.load("models/mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis")
if __name__ == "__main__":
demo.launch()