emotion detection

EmotionDetection/__init__.py

@@ -0,0 +1 @@
+from .emotion_detection import emotion_detector

EmotionDetection/emotion_detection.py

@@ -0,0 +1,47 @@
+import nltk
+from nltk.sentiment import SentimentIntensityAnalyzer
+
+nltk.download("vader_lexicon", quiet=True)  # Descarga el léxico si no está disponible
+
+
+def emotion_detector(text_to_analize):
+    """
+    Detecta emociones en un texto utilizando NLTK VADER.
+
+    Args:
+        text_to_analize (str): El texto para analizar.
+
+    Returns:
+        dict: Un diccionario con las puntuaciones de emoción y la emoción dominante.
+    """
+    if not text_to_analize:
+        return {
+            "anger": None,
+            "disgust": None,
+            "fear": None,
+            "joy": None,
+            "sadness": None,
+            "dominant_emotion": None,
+        }
+
+    analyzer = SentimentIntensityAnalyzer()
+    scores = analyzer.polarity_scores(text_to_analize)
+
+    emotion_scores = {
+        "anger": scores["neg"],
+        "disgust": scores["neg"] / 2,
+        "fear": scores["neg"] / 2,
+        "joy": scores["pos"],
+        "sadness": scores["neg"],
+    }
+
+    dominant_emotion = max(emotion_scores, key=emotion_scores.get)
+
+    return {
+        "anger": emotion_scores["anger"],
+        "disgust": emotion_scores["disgust"],
+        "fear": emotion_scores["fear"],
+        "joy": emotion_scores["joy"],
+        "sadness": emotion_scores["sadness"],
+        "dominant_emotion": dominant_emotion,
+    }

config.py

@@ -0,0 +1,4 @@
+# config.py
+IBM_API_KEY = "tu_clave_api"
+IBM_SERVICE_URL = "tu_url_servicio"
+ OTHER_VAR = "otro_valor"

pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "oaqjp-final-project-emb-ai"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "flask>=3.1.0",
+    "ibm-watson>=9.0.0",
+    "nltk>=3.9.1",
+    "pylint>=3.3.6",
+    "requests>=2.32.3",
+]

server.py

@@ -0,0 +1,46 @@
+"""
+Flask application for emotion detection.
+"""
+
+from flask import Flask, jsonify, render_template, request
+
+from EmotionDetection import emotion_detector
+
+app = Flask(__name__)
+
+
+@app.route("/")
+def index():
+    """Renders the index.html template."""
+    return render_template("index.html")
+
+
+@app.route("/emotionDetector", methods=["POST"])
+def emotion_detector_endpoint():
+    """
+    Handles emotion detection requests and returns the result.
+
+    Returns:
+        str: The emotion detection result as a string.
+    """
+    text_to_analyze = request.form["text"]
+    result = emotion_detector(text_to_analyze)
+
+    if result["dominant_emotion"] is None:
+        return "Invalid text! Please try again."
+
+    if "error" in result:
+        return jsonify({"error": result["error"]}), 500
+
+    response_text = (
+        f"For the given statement, the system response is 'anger': {result['anger']}, "
+        f"'disgust': {result['disgust']}, 'fear': {result['fear']}, "
+        f"'joy': {result['joy']} and 'sadness': {result['sadness']}. "
+        f"The dominant emotion is {result['dominant_emotion']}."
+    )
+
+    return response_text
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

static/mywebscript.js

@@ -1,12 +1,13 @@
-let RunSentimentAnalysis = ()=>{
-    textToAnalyze = document.getElementById("textToAnalyze").value;
+let RunSentimentAnalysis = () => {
+    let textToAnalyze = document.getElementById("textToAnalyze").value;
 
     let xhttp = new XMLHttpRequest();
     xhttp.onreadystatechange = function() {
         if (this.readyState == 4 && this.status == 200) {
-            document.getElementById("system_response").innerHTML = xhttp.responseText;
+            document.getElementById("system_response").innerHTML = this.responseText;
         }
     };
-    xhttp.open("GET", "emotionDetector?textToAnalyze"+"="+textToAnalyze, true);
-    xhttp.send();
+    xhttp.open("POST", "/emotionDetector", true);
+    xhttp.setRequestHeader("Content-Type", "application/x-www-form-urlencoded");
+    xhttp.send("text=" + encodeURIComponent(textToAnalyze));
 }

templates/index.html

@@ -11,7 +11,7 @@
 <body>
     <div class="card">
         <div class="card-body">
-            <h1 class="center-heading">NLP - Emotion Detection</h1> 
+            <h1 class="center-heading">NLP - Emotion Detection</h1>
             <div style="padding: 25px 25px 25px 25px;">
             <h2 class="mb-3">
                 <label class="form-label">Please enter the text to be analyzed</label>
@@ -30,3 +30,4 @@ <h2 class="mb-3">
         </div>
     </div>
 </body>
+</html>