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import torch
import numpy as np
import pandas as pd
from datetime import datetime
from newsapi import NewsApiClient
from transformers import pipeline
import plotly.graph_objects as go
import gradio as gr
# Initialize News API client with your API key
newsapi = NewsApiClient(api_key='381793b3d6834758918838bca0cf52ee')
# Define sentiment analyzer using FinBERT
sentiment_analyzer = pipeline("text-classification", model="ProsusAI/finbert")
# Function to fetch news, analyze sentiment, and create an interactive Plotly plot
def analyze_news_sentiment(company_name):
# Fetch news articles related to the company
news = newsapi.get_everything(q=company_name, language='en', sort_by='publishedAt')
# Extract headlines from news articles
headlines = [article['title'] for article in news['articles']]
# Perform sentiment analysis on the headlines
result = sentiment_analyzer(headlines)
df = pd.DataFrame(result)
# Map labels to numeric values
label_mapping = {'positive': 1, 'neutral': 0, 'negative': -1}
df['sentiment'] = df['label'].map(label_mapping)
# Drop the 'label' column
df.drop(columns=['label'], inplace=True)
# Filter out neutral sentiment values
positive_sentiment = df[df['sentiment'] == 1]['sentiment']
negative_sentiment = df[df['sentiment'] == -1]['sentiment']
# Create the interactive Plotly histogram
fig = go.Figure()
# Add Positive sentiment histogram
fig.add_trace(go.Histogram(
x=positive_sentiment,
nbinsx=1,
name='Positive',
marker_color='purple',
opacity=0.75
))
# Add Negative sentiment histogram
fig.add_trace(go.Histogram(
x=negative_sentiment,
nbinsx=1,
name='Negative',
marker_color='skyblue',
opacity=0.75
))
# Update layout for better visualization
fig.update_layout(
title=f'Sentiment Distribution for {company_name}',
xaxis_title='Sentiment',
yaxis_title='Count',
barmode='overlay',
plot_bgcolor='black',
paper_bgcolor='black',
font=dict(color='white'),
xaxis=dict(tickvals=[-1, 1], ticktext=['Negative', 'Positive']),
bargap=0.2,
)
return fig
# %%
# Create a Gradio interface
interface = gr.Interface(
fn=analyze_news_sentiment, # Function to run
inputs=gr.Textbox(label="Enter Company Name"), # Input: company name
outputs=gr.Plot(label="Sentiment Distribution"), # Output: Interactive Plotly chart
title="Sentiment Analysis on News Headlines",
description="Enter a company name to analyze the sentiment of the latest news related to that company."
)
# Launch the Gradio app
interface.launch()
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