Upload 3 files

app.py

@@ -8,14 +8,14 @@ import time
 # Page Title
 st.title("RAG7 - Real World RAG System")
 
-global retrieved_documents
-retrieved_documents = []
+# global retrieved_documents
+# retrieved_documents = []
 
-global response 
-response = ""
+# global response 
+# response = ""
 
-global time_taken_for_response
-time_taken_for_response = 'N/A'
+# global time_taken_for_response
+# time_taken_for_response = 'N/A'
 
 # @st.cache_data
 # def load_data():
@@ -84,4 +84,5 @@ with col1:
         metrics = ""
 
 with col2:
-    st.text_area("Metrics:", value=metrics, height=100, disabled=True)
+    #st.text_area("Metrics:", value=metrics, height=100, disabled=True)
+    st.json(metrics)

evaluation.py

@@ -6,6 +6,8 @@ from sklearn.metrics.pairwise import cosine_similarity
 
 from data_processing import load_ragbench
 
+global ground_truth_answer, ground_truth_metrics
+
 ground_truth_answer = ''
 ground_truth_metrics = {}
 
@@ -14,6 +16,7 @@ def calculate_metrics(question, response, docs, time_taken):
     retrieve_ground_truths(question, data)
     # Predicted metrics
     predicted_metrics = {
+        "ground_truth": ground_truth_answer,
         "context_relevance": context_relevance(question, docs),
         "context_utilization": context_utilization(response, docs),
         "completeness": completeness(response, ground_truth_answer),