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import os
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from transformers import pipeline
# ✅ Load Sentiment Analysis Model
sentiment_analyzer = pipeline("sentiment-analysis")
def analyze_sentiment(text):
"""Analyzes sentiment and returns sentiment label with confidence."""
result = sentiment_analyzer(text)[0]
return result['label'], result['score']
def generate_sentiment_graph(sentiments):
"""Creates a bar chart for sentiment analysis results."""
assets_dir = "assets"
# ✅ Ensure 'assets/' is a folder
if os.path.exists(assets_dir) and not os.path.isdir(assets_dir):
os.remove(assets_dir) # Delete if it's a file
os.makedirs(assets_dir) # Recreate as a folder
elif not os.path.exists(assets_dir):
os.makedirs(assets_dir)
# ✅ Extract sentiment data
labels = [s[0] for s in sentiments]
scores = [s[1] for s in sentiments]
# ✅ Create bar chart
plt.figure(figsize=(6, 3))
plt.bar(labels, scores, color=["green" if lbl == "POSITIVE" else "red" for lbl in labels])
plt.xlabel("Sentiment")
plt.ylabel("Confidence Score")
plt.title("Sentiment Analysis Results")
# ✅ Save the graph inside 'assets/' folder
graph_path = os.path.join(assets_dir, "sentiment_graph.png")
plt.savefig(graph_path)
plt.close()
return graph_path
def generate_wordcloud(text):
"""Generates a word cloud and ensures 'assets/' is always a folder."""
assets_dir = "assets"
# ✅ Ensure 'assets/' is a folder
if os.path.exists(assets_dir) and not os.path.isdir(assets_dir):
os.remove(assets_dir) # Delete if it's a file
os.makedirs(assets_dir) # Recreate as a folder
elif not os.path.exists(assets_dir):
os.makedirs(assets_dir)
# ✅ Generate and save Word Cloud
wordcloud = WordCloud(width=800, height=400, background_color="white").generate(text)
wordcloud_path = os.path.join(assets_dir, "wordcloud.png")
wordcloud.to_file(wordcloud_path)
return wordcloud_path
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