Update app.py

app.py

@@ -542,10 +542,11 @@ def ask_with_llm():
     - Loads databases and mappings
     - Parses natural-language queries
     - Executes queries and renders results
+    - Allows download of resulting data
     """
     # ---------- CONFIG ----------
-    DATABASE_PATH  = r"vehicle_analysis_1.db"
-    STATE_RTO_JSON = r"state_rto_data.json"
+    DATABASE_PATH  = r"D:\Data_for_query_tool\vehicle_analysis_DHRUMI.db"
+    STATE_RTO_JSON = r"D:\Data_for_query_tool\data_for_excel\state_rto_data.json"
 
     TABLE_MAPPINGS = {
         'fuel':    {'state': 'fuel_vs_state',                   'state_ev': 'fuel_vs_stateev',                   'rto': 'fuel_vs_rto',                   'rto_ev': 'fuel_vs_rtoev'},
@@ -606,14 +607,19 @@ def ask_with_llm():
                 return match[0]
         return None
 
-    def parse_year_filter(q: str) -> tuple[str|None,int|None]:
+    def parse_year_filter(q: str) -> tuple[str|None,int|tuple[int,int]|None]:
         ql = q.lower()
+        # Check for year range like "from 2018 to 2022"
+        if m := re.search(r"(from|between)\s*(20\d{2})\s*(to|-)\s*(20\d{2})", ql):
+            y1, y2 = int(m.group(2)), int(m.group(4))
+            return ('range', (min(y1, y2), max(y1, y2)))
         if m := re.search(r"after\s*(20\d{2})", ql):   return ('>',  int(m.group(1)))
         if m := re.search(r"before\s*(20\d{2})", ql):  return ('<',  int(m.group(1)))
         if m := re.search(r"in\s*(20\d{2})", ql):      return ('==', int(m.group(1)))
-        if m := re.search(r"\b(20\d{2})\b", ql):     return ('==', int(m.group(1)))
+        if m := re.search(r"\b(20\d{2})\b", ql):       return ('==', int(m.group(1)))
         return (None, None)
 
+
     def parse_top_n(q: str) -> int|None:
         ql = q.lower()
         if m := re.search(r"top\s*(\d+)\s*states?\b", ql):
@@ -660,7 +666,10 @@ def ask_with_llm():
 
     df = df_map[tbl_name]
     if op and year:
-        df = df.query(f"year {op} @year")
+        if op == 'range' and isinstance(year, tuple):
+            df = df[df['year'].between(year[0], year[1])]
+        else:
+            df = df.query(f"year {op} @year")
     if loc_type == 'rto':
         df = df[df['column_value']==loc]
     elif loc_type == 'state':
@@ -698,15 +707,30 @@ def ask_with_llm():
             title  = f"Overall total registrations{' (EV)' if ev else ''}"
             result = ts.rename(columns={'count':'Total'})
             fig    = px.line(ts, x='year', y='count', labels={'count':'Total'})
+
+    st.subheader(title)
     st.dataframe(result)
+
+    # Append year info to result if applicable
+    if op and year:
+        if op == '==':
+            year_info = f"In {year}"
+        elif op == '>':
+            year_info = f"After {year}"
+        elif op == '<':
+            year_info = f"Before {year}"
+        elif op == 'range' and isinstance(year, tuple):
+            year_info = f"From {year[0]} to {year[1]}"
+        else:
+            year_info = f"Year Filter: {op} {year}"
+        result['Query_Year_Info'] = year_info
+
+    # Download option
+    csv = result.to_csv(index=False).encode('utf-8')
+    st.download_button("⬇ Download Result as CSV", data=csv, file_name="query_result.csv", mime='text/csv')
+
     st.plotly_chart(fig)
-    st.markdown("#### 💬 Try asking:")
-    st.markdown("- Top 5 states by fuel in 2022  ")
-    st.markdown("- Norm-wise registrations in Maharashtra in 2024 ")
-    st.markdown("- Electric (EV) norm-wise registrations in Karnataka after 2021 ")
-    st.markdown("- Fuel-wise registrations in Delhi in 2020")
-    st.markdown("- vehicle classes by registrations in Tamil Nadu in 2022 ")
-   
+    
     
 
 # Run the entire app
@@ -738,4 +762,10 @@ elif section == "State Analysis":
 elif section == "Vehicle Class & Category":
     vehicle_class_category()
 elif section == "Ask with Text (LLM)":
-    ask_with_llm()
+    ask_with_llm()
+    st.markdown("#### 💬 Try asking:")
+    st.markdown("- Top 5 states by fuel in 2022  ")
+    st.markdown("- Norm-wise registrations in Maharashtra in 2024 ")
+    st.markdown("- Electric (EV) norm-wise registrations in Karnataka after 2021 ")
+    st.markdown("- Fuel-wise registrations in Delhi in 2020")
+    st.markdown("- Vehicle classes by registrations in Tamil Nadu in 2022 ")