diff --git a/EmotionDetection/__init__.py b/EmotionDetection/__init__.py
new file mode 100644
index 000000000..0b7bf8661
--- /dev/null
+++ b/EmotionDetection/__init__.py
@@ -0,0 +1 @@
+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..3ae4e0d00
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+++ b/EmotionDetection/emotion_detection.py
@@ -0,0 +1,33 @@
+import requests
+import json
+
+def emotion_detector(text_to_analyze):
+    """
+    Sends a POST request to Watson NLP Emotion Detection API and returns the formatted response.
+    """
+    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}}
+    
+    response = requests.post(url, json=payload, headers=headers)
+    response_dict = json.loads(response.text)  # Convert response to dictionary
+    
+    # Extract emotion scores
+    emotions = response_dict.get("emotionPredictions", [{}])[0].get("emotion", {})
+    anger = emotions.get("anger", 0)
+    disgust = emotions.get("disgust", 0)
+    fear = emotions.get("fear", 0)
+    joy = emotions.get("joy", 0)
+    sadness = emotions.get("sadness", 0)
+    
+    # Determine the dominant emotion
+    dominant_emotion = max(emotions, key=emotions.get, default="unknown")
+    
+    return {
+        "anger": anger,
+        "disgust": disgust,
+        "fear": fear,
+        "joy": joy,
+        "sadness": sadness,
+        "dominant_emotion": dominant_emotion
+    }
diff --git a/emotion_detection.py b/emotion_detection.py
new file mode 100644
index 000000000..798dafc12
--- /dev/null
+++ b/emotion_detection.py
@@ -0,0 +1,30 @@
+import requests
+
+def emotion_detector(text_to_analyze):
+    """
+    Diagnostic version of the emotion_detector function
+    that prints the entire JSON to identify its structure.
+    """
+    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",
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "raw_document": {
+            "text": text_to_analyze
+        }
+    }
+
+    response = requests.post(url, headers=headers, json=payload)
+
+    if response.status_code == 200:
+        try:
+            response_json = response.json()
+            # Print the entire response JSON to see its structure
+            print("DEBUG: Entire Watson Response:", response_json)
+            return response_json
+        except ValueError:
+            return "Error parsing JSON response."
+    else:
+        return f"Error: {response.status_code}, {response.text}"
diff --git a/server.py b/server.py
new file mode 100644
index 000000000..9d0d70368
--- /dev/null
+++ b/server.py
@@ -0,0 +1,28 @@
+from flask import Flask, request, jsonify
+from EmotionDetection import emotion_detector
+
+app = Flask(__name__, template_folder="templates")
+
+@app.route('/')
+def home():
+    return "Emotion Detection API is running! Use /emotionDetector endpoint to analyze text."
+
+@app.route('/emotionDetector', methods=['GET'])
+def emotion_detector_endpoint():
+    text_to_analyze = request.args.get('textToAnalyze', '')
+
+    if not text_to_analyze:
+        return jsonify({"error": "No text provided for analysis."}), 400
+
+    response = emotion_detector(text_to_analyze)
+
+    formatted_response = (
+        f"For the given statement, the system response is 'anger': {response['anger']}, 'disgust': {response['disgust']}, "
+        f"'fear': {response['fear']}, 'joy': {response['joy']} and 'sadness': {response['sadness']}. "
+        f"The dominant emotion is {response['dominant_emotion']}."
+    )
+
+    return formatted_response
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000, debug=True)
diff --git a/test_emotion_detection.py b/test_emotion_detection.py
new file mode 100644
index 000000000..c589f38aa
--- /dev/null
+++ b/test_emotion_detection.py
@@ -0,0 +1,28 @@
+import unittest
+from EmotionDetection import emotion_detector
+
+class TestEmotionDetection(unittest.TestCase):
+    
+    def test_emotion_detector(self):
+        # Test for joy
+        response = emotion_detector("I am glad this happened")
+        self.assertEqual(response['dominant_emotion'], "joy")
+        
+        # Test for anger
+        response = emotion_detector("I am really mad about this")
+        self.assertEqual(response['dominant_emotion'], "anger")
+        
+        # Test for disgust
+        response = emotion_detector("I feel disgusted just hearing about this")
+        self.assertEqual(response['dominant_emotion'], "disgust")
+        
+        # Test for sadness
+        response = emotion_detector("I am so sad about this")
+        self.assertEqual(response['dominant_emotion'], "sadness")
+        
+        # Test for fear
+        response = emotion_detector("I am really afraid that this will happen")
+        self.assertEqual(response['dominant_emotion'], "fear")
+
+if __name__ == "__main__":
+    unittest.main()