feat: add sentiment analysis module using VADER with classify and score functions

Implement a new sentiment.py module that provides VADER-based sentiment analysis. The module includes an `analyze_sentiment_vader` function that classifies text as Positive, Negative, or Neutral based on compound score thresholds (>=0.05, <=-0.05), and a convenience `analyze` function wrapping the analyzer instance. Returns compound score and detailed polarity scores alongside classification.

sentiment.py

@@ -0,0 +1,35 @@
+import json
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+
+def analyze_sentiment_vader(text, analyzer):
+    """
+    Analyzes text using VADER and returns a dictionary with the results.
+
+    Args:
+        text (str): The text content to analyze.
+        analyzer (SentimentIntensityAnalyzer): An instantiated VADER analyzer.
+
+    Returns:
+        dict: A dictionary containing the sentiment classification, compound score,
+              and detailed scores (positive, neutral, negative).
+    """
+    scores = analyzer.polarity_scores(text)
+    compound_score = scores['compound']
+
+    if compound_score >= 0.05:
+        sentiment = 'Positive'
+    elif compound_score <= -0.05:
+        sentiment = 'Negative'
+    else:
+        sentiment = 'Neutral'
+
+    return {
+        'sentiment': sentiment,
+        'score': compound_score,
+        'details': scores  
+    }
+
+vader_analyzer = SentimentIntensityAnalyzer()
+
+def analyze(content):
+    return analyze_sentiment_vader(content, vader_analyzer)