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diff --git a/app/data_loader.py b/app/data_loader.py
index 1052e9d1..d92f11dc 100644
--- a/app/data_loader.py
+++ b/app/data_loader.py
@@ -4,9 +4,10 @@
 from dotenv import load_dotenv
 import os
 
-load_dotenv()
+load_dotenv(dotenv_path=os.path.join(os.path.dirname(__file__), "..", ".env"))
 
-BASE_URL = os.getenv("BASE_API_URL")
+BASE_API_URL = os.getenv("BASE_API_URL")
+print(BASE_API_URL)
 
 
 def fetch_data(endpoint, params=None):
@@ -29,11 +30,18 @@ def fetch_data(endpoint, params=None):
     if params is None:
         params = {}
 
-    url = f"{BASE_URL}{endpoint}"
+    url = f"{BASE_API_URL}{endpoint}"
     full_url = requests.Request('GET', url, params=params).prepare().url
-    response = requests.get(full_url)
-    response.raise_for_status()
-    return pd.DataFrame(response.json())
+    try:
+        response = requests.get(full_url)
+
+        if response.status_code == 404:
+            return pd.DataFrame()
+        response.raise_for_status()
+        return pd.DataFrame(response.json())
+    except requests.exceptions.RequestException as e:
+        print("API Error:", e)
+        return pd.DataFrame()
 
 
 # Cached API calls using Streamlit's cache_data decorator
diff --git a/main.py b/main.py
index adaccab4..f886c74d 100644
--- a/main.py
+++ b/main.py
@@ -1,4 +1,5 @@
 import streamlit as st
+import datetime
 from app.data_loader import (
     fetch_data,
     fetch_sessions,
@@ -28,15 +29,19 @@
 
 with col1:
     # Step 1: Select Year and Country dynamically
-    available_years = [2023, 2024, 2025]
+    available_years = [2023, 2024, 2025, 2026]
     selected_year = st.selectbox("Select Year", available_years, index=len(available_years) - 1)
 
     # Fetch all meetings for selected year
     all_meetings = fetch_data("meetings", {"year": selected_year})
+    current_year = datetime.datetime.now().year
 
     if all_meetings.empty:
-        st.error("No meetings found for this year.")
-        st.stop()
+        if selected_year >= current_year:
+             st.warning("No race data yet. Showing upcoming schedule if available.")
+        else:
+            st.error("No meetings found for this year.")
+            st.stop()
 
     available_countries = sorted(all_meetings["country_name"].dropna().unique())
     selected_country = st.selectbox("Select Country", available_countries)
@@ -46,12 +51,21 @@
     filtered_meetings["label"] = filtered_meetings["meeting_name"] + " - " + filtered_meetings["location"]
     filtered_meetings = filtered_meetings.sort_values(by="meeting_key", ascending=False)
 
+    if filtered_meetings.empty:
+        st.warning("🚧 No Grand Prix available yet for this selection.")
+        st.stop()
+
 with col2:
     selected_meeting = st.selectbox("Select Grand Prix", filtered_meetings["label"], disabled=True)
     selected_meeting_key = filtered_meetings.loc[
         filtered_meetings["label"] == selected_meeting, "meeting_key"
     ].values[0]
     sessions = fetch_sessions(selected_meeting_key)
+
+    if sessions.empty:
+        st.info("📅 Session schedule not available yet.")
+        st.stop()
+
     selected_session = st.selectbox("Select Session", sessions["label"])
     sessions["session_type"] = sessions["label"].str.extract(r"^(.*?)\s\(")
     selected_session_type = sessions.loc[sessions["label"] == selected_session, "session_type"].values[0]
@@ -72,8 +86,16 @@
 with st.expander(f"📈 Lap Time Chart for {selected_session_type} at {selected_country} {selected_year}",
                  expanded=True):
     lap_df = fetch_laps(selected_session_key)
+
+    if lap_df.empty:
+        st.info("🚧 This session hasn't happened yet. Showing schedule only.")
+        st.stop()
+
     processed_df = process_lap_data(lap_df)
 
+    if processed_df.empty:
+        st.info("🚧 This session hasn’t happened yet. Data will appear after completion.")
+
     # Merge name_acronym into the lap data
     processed_df["driver_number"] = processed_df["driver_number"].astype(str)
     processed_df = processed_df.merge(driver_info, on="driver_number", how="left")