diff --git a/EmotionDetection/__init__.py b/EmotionDetection/__init__.py
new file mode 100644
index 000000000..d69073368
--- /dev/null
+++ b/EmotionDetection/__init__.py
@@ -0,0 +1 @@
+from . import emotion_detection
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diff --git a/EmotionDetection/emotion_detection.py b/EmotionDetection/emotion_detection.py
new file mode 100644
index 000000000..648941cbd
--- /dev/null
+++ b/EmotionDetection/emotion_detection.py
@@ -0,0 +1,39 @@
+import requests, json
+
+def emotion_detector(text_to_analyze):
+    url = 'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'
+    myobj = { "raw_document": { "text": text_to_analyze } }
+    header = {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"} 
+    response = requests.post(url, json = myobj, headers=header)
+
+    if response.status_code == 400:
+        response_text = (
+            {
+                "anger": None, 
+                "disgust": None, 
+                "fear": None, 
+                "joy": None, 
+                "sadness": None, 
+                "dominant_emotion": None
+            }
+        )
+
+        return response_text
+    else:
+
+        formatted_response = json.loads(response.text)
+        emotions = formatted_response['emotionPredictions'][0]['emotion']
+
+        emotions['dominant_emotion'] = max(emotions, key=emotions.get)
+
+        response_text = (
+            f"For the given statement, the system response is "
+            f"'anger': {emotions['anger']}, "
+            f"'disgust': {emotions['disgust']}, "
+            f"'fear': {emotions['fear']}, "
+            f"'joy': {emotions['joy']} and "
+            f"'sadness': {emotions['sadness']}. "
+            f"The dominant emotion is {emotions['dominant_emotion']}."
+        )
+
+        return response_text
diff --git a/server.py b/server.py
new file mode 100644
index 000000000..283c7681a
--- /dev/null
+++ b/server.py
@@ -0,0 +1,25 @@
+"""Flask app for detecting emotions from text input."""
+
+from flask import Flask, render_template, request
+from EmotionDetection.emotion_detection import emotion_detector
+
+app = Flask("Emotion Detector")
+
+@app.route("/")
+def render_index_page():
+    """Render the home page."""
+    return render_template("index.html")
+
+@app.route("/emotionDetector")
+def emotion_detect():
+    """Handle emotion detection requests."""
+    text_to_analyze = request.args.get("textToAnalyze")
+    response = emotion_detector(text_to_analyze)
+
+    if response["dominant_emotion"] is not None:
+        return response
+
+    return "Invalid text! Please try again!"
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5003)
diff --git a/test_emotion_detection.py b/test_emotion_detection.py
new file mode 100644
index 000000000..e6e537a9c
--- /dev/null
+++ b/test_emotion_detection.py
@@ -0,0 +1,22 @@
+from EmotionDetection.emotion_detection import emotion_detector
+import unittest
+
+class TestEmotionDetector(unittest.TestCase):
+    def test_emotion_detector(self):
+        # Test case for joy emotion
+        result_1 = emotion_detector('I am glad this happened')
+        self.assertEqual(result_1['dominant_emotion'], 'joy')
+        # Test case for anger emotion
+        result_2 = emotion_detector('I am really mad about this')
+        self.assertEqual(result_2['dominant_emotion'], 'anger')
+        # Test case for disgust emotion
+        result_3 = emotion_detector('I feel disgusted just hearing about this')
+        self.assertEqual(result_3['dominant_emotion'], 'disgust')
+        # Test case for sadness emotion
+        result_4 = emotion_detector('I am so sad about this')
+        self.assertEqual(result_4['dominant_emotion'], 'sadness')
+        # Test case for fear emotion
+        result_5 = emotion_detector('I am really afraid that this will happen')
+        self.assertEqual(result_5['dominant_emotion'], 'fear')
+
+unittest.main()
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