Bugfixes from refactor

functions/chart_functions.py

@@ -27,11 +27,9 @@ def chart_generation_func(data: List[str], x_column: str, y_column: str, graph_t
 
         df = pd.read_csv(csv_query_path)
 
+        #setting up the plotly express objects 
         if graph_type == "bar":
-         if category in df.columns:
-            initial_graph = px.bar(df, x=x_column, y=y_column, color=category, barmode="group")
-         else:
-            initial_graph = px.bar(df, x=x_column, y=y_column, barmode="group")
+         initial_graph = px.bar(df, x=x_column, y=y_column, barmode="group")
         elif graph_type == "scatter":
          if category in df.columns:
             initial_graph = px.scatter(df, x=x_column, y=y_column, color=category)  
@@ -41,46 +39,44 @@ def chart_generation_func(data: List[str], x_column: str, y_column: str, graph_t
          if category in df.columns:
             initial_graph = px.line(df, x=x_column, y=y_column, color=category)
          else:
-            initial_graph = px.line(df, x=x_column, y=y_column)
+            initial_graph = px.line(df, x=x_column, y=y_column)   
         elif graph_type == "pie":
-         if category in df.columns:
-            initial_graph = px.pie(df, x=x_column, y=y_column, color=category)
-         else:
-            initial_graph = px.pie(df, x=x_column, y=y_column)
-
-        if isinstance(data, list):
-           data_list = data
-        else:
-           data_list.append(data) 
+         initial_graph = px.pie(df, x=x_column, y=y_column)
 
+        fig = initial_graph.to_dict()   
 
         #Processing data to account for variation from LLM
         data_list = []
         layout_dict = {}
 
+        if isinstance(data, list):
+           data_list = data
+        else:
+           data_list.append(data) 
+
         data_dict = {}   
         for data_obj in data_list:   
          if isinstance(data_obj, str):
             data_obj = data_obj.replace("\n", "")
-            if not data_obj.startswith('{') and not data_obj.endswith('}'):
+            if not data_obj.startswith('{') or not data_obj.endswith('}'):
                data_obj = "{" + data_obj + "}"
             data_dict = ast.literal_eval(data_obj)
          else:
             data_dict = data_obj
     
-        if isinstance(layout, list):
+        if layout and isinstance(layout, list):
            layout_obj = layout[0]
         else:
            layout_obj = layout
 
-        if isinstance(layout_obj, str):
+        if layout and isinstance(layout_obj, str):
            layout_dict = ast.literal_eval(layout_obj)
         else:
            layout_dict = layout_obj
-           
-        fig = initial_graph.to_dict()
 
-        fig["layout"] = layout_dict
+        #Applying stylings and settings generated from LLM
+        if layout:
+         fig["layout"] = layout_dict
 
         for key, value in data_dict.items():
            if key not in ["x","y"]:
@@ -126,8 +122,7 @@ def table_generation_func(data: List[dict], session_hash):
         print(df)
         df.to_csv(csv_path)
 
-        download_path = f'{root_url}/gradio_api/file/temp/{session_hash}/data.csv'
-        html_table = df.to_html() + f'<p>Download as a <a href="{download_path}">CSV file</a></p>'
+        html_table = df.to_html()
         print(html_table)
 
         return {"reply": html_table}

functions/sqlite_functions.py

@@ -33,7 +33,7 @@ def sqlite_query_func(queries: List[str], session_hash):
     sql_query = SQLiteQuery(f'{dir_path}/data_source.db')
     try:
       result = sql_query.run(queries, session_hash)
-      if len(result["results"][0]) > 300:
+      if len(result["results"][0]) > 500:
         print("QUERY TOO LARGE")
         return {"reply": "query result too large to be processed by llm, the query results are in our query.csv file"}
       else:   

tools.py

@@ -105,7 +105,7 @@ def tools_call(session_hash):
                 "name": "table_generation_func",
                 "description": f"""This an table generation tool useful to format data as a table from queried data from our SQL table called 'data_source. 
                 Returns an html string generated from the pandas library and pandas.to_html() 
-                function which will be displayed inline in our chat window. There will also be a link to download the CSV included in the HTML string. 
+                function which will be displayed inline in our chat window.
                 Do not edit the string returned by the function in any way when displaying to the user.""",
                 "parameters": {
                     "type": "object",