update tools

tools.py

@@ -144,46 +144,8 @@ def convert_units(value: float, from_unit: str, to_unit: str) -> float:
     return conversions[key](value)
 
 
-def convert_query_to_pandas_syntax(natural_query: str, column_names: list) -> str:
-    """
-    Converts a natural language query to pandas query syntax using basic heuristics.
-    
-    Args:
-        natural_query: A string with a question or filter expression in plain English.
-        column_names: List of column names from the DataFrame.
-
-    Returns:
-        A best-effort string in pandas query() format.
-    """
-    # Preprocess query
-    query = natural_query.lower().strip()
-
-    # Heuristic rules
-    rules = [
-        (r"(\w+) greater than (\d+)", r"\1 > \2"),
-        (r"(\w+) less than (\d+)", r"\1 < \2"),
-        (r"(\w+) equal to ['\"]?([\w\s]+)['\"]?", r"\1 == '\2'"),
-        (r"(\w+) not equal to ['\"]?([\w\s]+)['\"]?", r"\1 != '\2'"),
-        (r"(\w+) more than (\d+)", r"\1 > \2"),
-        (r"(\w+) less than or equal to (\d+)", r"\1 <= \2"),
-        (r"(\w+) greater than or equal to (\d+)", r"\1 >= \2"),
-        (r"(\w+) is ['\"]?([\w\s]+)['\"]?", r"\1 == '\2'"),
-    ]
-
-    for pattern, replacement in rules:
-        if re.search(pattern, query):
-            query = re.sub(pattern, replacement, query)
-            break
-
-    # Handle AND/OR logic
-    query = query.replace(" and ", " and ")
-    query = query.replace(" or ", " or ")
-
-    return query
-
-
 @tool
-def query_table_data(file_path: str, query_pandas_syntax: str, sheet_name: str = None) -> str:
+def query_table_data(file_path: str, query: str, sheet_name: str = None) -> str:
     """
     Loads a table from CSV or Excel and filters it using a pandas query.
 
@@ -208,8 +170,30 @@ def query_table_data(file_path: str, query_pandas_syntax: str, sheet_name: str =
         else:
            raise ValueError(f"Unsupported file extension: {ext}")
         try:
-           filtered_df = df.query(query_pandas_syntax)
-           return filtered_df.head(10).to_markdown(index=False)
+            #Converts a natural language query to pandas query syntax using basic heuristics.
+            # Preprocess query
+            query_l = query.lower().strip()
+            # Heuristic rules
+            rules = [
+            (r"(\w+) greater than (\d+)", r"\1 > \2"),
+            (r"(\w+) less than (\d+)", r"\1 < \2"),
+            (r"(\w+) equal to ['\"]?([\w\s]+)['\"]?", r"\1 == '\2'"),
+            (r"(\w+) not equal to ['\"]?([\w\s]+)['\"]?", r"\1 != '\2'"),
+            (r"(\w+) more than (\d+)", r"\1 > \2"),
+            (r"(\w+) less than or equal to (\d+)", r"\1 <= \2"),
+            (r"(\w+) greater than or equal to (\d+)", r"\1 >= \2"),
+            (r"(\w+) is ['\"]?([\w\s]+)['\"]?", r"\1 == '\2'"),
+            ]
+
+            for pattern, replacement in rules:
+                if re.search(pattern, query):
+                  query = re.sub(pattern, replacement, query)
+                break
+            # Handle AND/OR logic
+            query_pandas_syntax = query.replace(" and ", " and ")
+            query_pandas_syntaxs = query.replace(" or ", " or ")
+            filtered_df = df.query(query_pandas_syntax)
+            return filtered_df.head(10).to_markdown(index=False)
         except Exception as e:
            raise ValueError(f"Invalid query: {query_pandas_syntax}. Error: {e}")
     except ImportError:
@@ -368,7 +352,6 @@ level1_tools = [
     web_search,
     arvix_search,
     convert_units,
-    convert_query_to_pandas_syntax,
     query_table_data,
     download_file_from_url,
     save_and_read_file,