Update app.py

app.py

@@ -280,10 +280,19 @@ def vectara_query(query: str, config: dict):
 tab1, tab2, tab3, tab4 = st.tabs(["Synthetic Data", "Data Query", "HHEM-Victara Query Tuner", "Model Evaluation"])
 
 with tab1:
-    st.header("Synthetic Data")
-    st.link_button("Create Synthetic Medical Data", "https://chat.openai.com/g/g-XyHciw52w-synthetic-clinical-data")
-    
-   
+
+    # Create two columns, the first for the image, the second for the text and button
+    col1, col2 = st.columns([1, 2])  # Adjust the ratio as needed for your layout
+
+    # In the first column, add your image
+    with col1:
+        st.image("path_or_url_to_your_image", caption="Synthetic Data Visualization")
+
+    # In the second column, add your header and link button
+    with col2:
+        st.header("Synthetic Data")
+        st.link_button("Create Synthetic Medical Data", "https://chat.openai.com/g/g-XyHciw52w-synthetic-clinical-data")
+ 
 
 with tab2:
     st.header("Data Query")
@@ -294,7 +303,7 @@ with tab3:
     st.header("HHEM-Victara Query Tuner")
     
     # User inputs
-    query = st.text_area("Enter your text for query tuning", "", height=75)
+    query = st.text_area("Enter your text for query tuning", "", height=100)
     lambda_val = st.slider("Lambda Value", min_value=0.0, max_value=1.0, value=0.5)
     top_k = st.number_input("Top K Results", min_value=1, max_value=50, value=10)
     
@@ -335,7 +344,8 @@ with tab4:
     st.header("Model Evaluation")
 
     # User input for the research topic
-    research_topic = st.text_input('Enter your research topic:', '')
+    research_topic = st.text_area('Enter your research topic:', '', height=100)
+
 
     # Selection box for the function to execute
     process_selection = st.selectbox(