diff --git a/EmotionDetection/__init__.py b/EmotionDetection/__init__.py
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index 000000000..b4042ae25
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+++ b/EmotionDetection/__init__.py
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+
+from .emotion_detection import emotion_detector
+
+
+
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diff --git a/EmotionDetection/__pycache__/emotion_detection.cpython-311.pyc b/EmotionDetection/__pycache__/emotion_detection.cpython-311.pyc
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diff --git a/EmotionDetection/emotion_detection.py b/EmotionDetection/emotion_detection.py
new file mode 100644
index 000000000..e0cae637b
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+++ b/EmotionDetection/emotion_detection.py
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+import requests
+import json
+
+def emotion_detector(text_to_analyze):
+    url = "https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict"
+    headers = {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"}
+    payload = {"raw_document": {"text": text_to_analyze}}
+    
+    # Verificar si el texto está vacío
+    if not text_to_analyze.strip():
+        return {
+            'anger': None,
+            'disgust': None,
+            'fear': None,
+            'joy': None,
+            'sadness': None,
+            'dominant_emotion': None
+        }
+    
+    response = requests.post(url, headers=headers, json=payload)
+    
+    # Manejo de error si el servidor responde con un código 400
+    if response.status_code == 400:
+        return {
+            'anger': None,
+            'disgust': None,
+            'fear': None,
+            'joy': None,
+            'sadness': None,
+            'dominant_emotion': None
+        }
+    
+    response_data = response.json()
+    emotions = response_data.get("emotionPredictions", [])[0].get("emotion", {})
+    
+    if not emotions:
+        return {
+            'anger': None,
+            'disgust': None,
+            'fear': None,
+            'joy': None,
+            'sadness': None,
+            'dominant_emotion': None
+        }
+    
+    # Encontrar la emoción dominante
+    dominant_emotion = max(emotions, key=emotions.get)
+    
+    return {
+        'anger': emotions.get('anger'),
+        'disgust': emotions.get('disgust'),
+        'fear': emotions.get('fear'),
+        'joy': emotions.get('joy'),
+        'sadness': emotions.get('sadness'),
+        'dominant_emotion': dominant_emotion
+    }
+
diff --git a/__pycache__/emotion_detection.cpython-311.pyc b/__pycache__/emotion_detection.cpython-311.pyc
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diff --git a/oaqjp-final-project-emb-ai b/oaqjp-final-project-emb-ai
new file mode 160000
index 000000000..3e04588b7
--- /dev/null
+++ b/oaqjp-final-project-emb-ai
@@ -0,0 +1 @@
+Subproject commit 3e04588b7b73640f1afb806d3e6bf3e2a41e8fd2
diff --git a/server.py b/server.py
new file mode 100644
index 000000000..b8168ac20
--- /dev/null
+++ b/server.py
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+from flask import Flask, request, jsonify, render_template
+from EmotionDetection import emotion_detector  # Import the function
+
+app = Flask(__name__)
+
+# Route to serve the web application
+@app.route("/")
+def home():
+    return render_template("index.html")
+
+# Route to handle emotion detection
+@app.route("/emotionDetector", methods=["POST"])
+def detect_emotion():
+    try:
+        # Get text input from request
+        data = request.get_json()
+        text_to_analyze = data.get("text", "")
+
+        if not text_to_analyze:
+            return jsonify({"error": "No text provided"}), 400
+
+        # Call the emotion detection function
+        result = emotion_detector(text_to_analyze)
+
+        # Check if dominant_emotion is None
+        if result.get('dominant_emotion') is None:
+            return jsonify({"error": "Invalid text! Please try again!"}), 400
+
+        # Format the response as requested
+        response_text = (
+            f"For the given statement, the system response is "
+            f"'anger': {result['anger']}, 'disgust': {result['disgust']}, "
+            f"'fear': {result['fear']}, 'joy': {result['joy']} and "
+            f"'sadness': {result['sadness']}. The dominant emotion is {result['dominant_emotion']}."
+        )
+
+        return jsonify({"message": response_text})
+
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+if __name__ == "__main__":
+    app.run(debug=True, host="127.0.0.1", port=5000)
+
+
diff --git a/test_emotion_detection.py b/test_emotion_detection.py
new file mode 100644
index 000000000..6ba894414
--- /dev/null
+++ b/test_emotion_detection.py
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+import unittest
+from EmotionDetection import emotion_detector
+
+class TestEmotionDetector(unittest.TestCase):
+    """Pruebas unitarias para la función emotion_detector."""
+
+    def test_joy(self):
+        """Prueba si la emoción dominante es 'joy'."""
+        result = emotion_detector("I am glad this happened")
+        self.assertIn("dominant_emotion", result)
+        self.assertEqual(result["dominant_emotion"], "joy")
+
+    def test_anger(self):
+        """Prueba si la emoción dominante es 'anger'."""
+        result = emotion_detector("I am really mad about this")
+        self.assertIn("dominant_emotion", result)
+        self.assertEqual(result["dominant_emotion"], "anger")
+
+    def test_disgust(self):
+        """Prueba si la emoción dominante es 'disgust'."""
+        result = emotion_detector("I feel disgusted just hearing about this")
+        self.assertIn("dominant_emotion", result)
+        self.assertEqual(result["dominant_emotion"], "disgust")
+
+    def test_sadness(self):
+        """Prueba si la emoción dominante es 'sadness'."""
+        result = emotion_detector("I am so sad about this")
+        self.assertIn("dominant_emotion", result)
+        self.assertEqual(result["dominant_emotion"], "sadness")
+
+    def test_fear(self):
+        """Prueba si la emoción dominante es 'fear'."""
+        result = emotion_detector("I am really afraid that this will happen")
+        self.assertIn("dominant_emotion", result)
+        self.assertEqual(result["dominant_emotion"], "fear")
+
+if __name__ == "__main__":
+    unittest.main()
+
+