Create functions for each visualization

app.py

@@ -30,15 +30,20 @@ def example_display(input):
         display = False
     return [gr.update(visible=display),gr.update(visible=display)]
 
-css= ".file_marker .large{min-height:50px !important;} .example_btn{max-width:300px;}"
+css= ".file_marker .large{min-height:50px !important;} .example_btn{max-width:300px;} .padding{padding:0;}"
 
 with gr.Blocks(css=css, delete_cache=(3600,3600)) as demo:
     title = gr.HTML("<h1 style='text-align:center;'>Virtual Data Analyst</h1>")
-    description = gr.HTML("""<p style='text-align:center;'>Upload a data file and chat with our virtual data analyst 
-                          to get insights on your data set. Currently accepts CSV, TSV, TXT, XLS, XLSX, XML, and JSON files. 
-                          Can now generate charts and graphs! Can run linear regressions!
+    description = gr.HTML("""<p style='text-align:center;'>A helpful tool for data analysis, visualizations, regressions, and more. 
+                          Upload a data file and chat with our virtual data analyst to get insights on your data set. 
                           Try a sample file to get started!</p>
-                          <p style='text-align:center;'>This tool is under active development. If you experience bugs with use, 
+                          <div style="margin:auto;max-width: 500px;">
+                          <p style="margin:0;font-style:italic;">Currently accepts CSV, TSV, TXT, XLS, XLSX, XML, and JSON files.</p>
+                          <p style="margin:0;font-style:italic;">Can run SQL queries, linear regressions, and analyze the results.</p>
+                          <p style="margin:0;font-style:italic;">Can generate scatter plots, line charts, pie charts, bar graphs, histograms, time series, and more.
+                          New visualizations types added regularly.</p>
+                          </div>
+                          <p style='text-align:center;'>This application is under active development. If you experience bugs with use, 
                           open a discussion in the community tab and I will respond.</p>""")
     example_file_1 = gr.File(visible=False, value="samples/bank_marketing_campaign.csv")
     example_file_2 = gr.File(visible=False, value="samples/online_retail_data.csv")

functions/__init__.py

@@ -1,6 +1,9 @@
 from .sqlite_functions import SQLiteQuery, sqlite_query_func
-from .chart_functions import chart_generation_func, table_generation_func
+from .chart_functions import table_generation_func, scatter_chart_generation_func, \
+line_chart_generation_func, bar_chart_generation_func, pie_chart_generation_func, histogram_generation_func, scatter_chart_fig
 from .chat_functions import example_question_generator, chatbot_with_fc
 from .stat_functions import regression_func
 
-__all__ = ["SQLiteQuery","sqlite_query_func","chart_generation_func","table_generation_func","regression_func","example_question_generator","chatbot_with_fc"]
+__all__ = ["SQLiteQuery","sqlite_query_func","table_generation_func","scatter_chart_generation_func",
+           "line_chart_generation_func","bar_chart_generation_func","regression_func", "pie_chart_generation_func", "histogram_generation_func",
+           "scatter_chart_fig","example_question_generator","chatbot_with_fc"]

functions/chart_functions.py

@@ -12,92 +12,325 @@ load_dotenv()
 
 root_url = os.getenv("ROOT_URL")
 
-def chart_generation_func(data: List[dict], x_column: str, y_column: str, graph_type: str, session_hash: str, layout: List[dict]=[{}], category: str=""):
-    print("CHART GENERATION")
-    print(data)
-    print(graph_type)
-    print(x_column)
-    print(y_column)
-    print(category)
-    print(layout)
-    try:
-        dir_path = TEMP_DIR / str(session_hash)
-        chart_path = f'{dir_path}/chart.html'
-        csv_query_path = f'{dir_path}/query.csv'
+def llm_chart_data_scrub(data, layout):
+   #Processing data to account for variation from LLM
+   data_list = []
+   layout_dict = {}
 
-        df = pd.read_csv(csv_query_path)
+   if isinstance(data, list):
+      data_list = data
+   else:
+      data_list.append(data) 
 
-        #setting up the plotly express objects 
-        if graph_type == "bar":
-         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)  
-         else:
-            initial_graph = px.scatter(df, x=x_column, y=y_column)
-        elif graph_type == "line":
-         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)   
-        elif graph_type == "pie":
-         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('{') or not data_obj.endswith('}'):
-               data_obj = "{" + data_obj + "}"
-            data_dict = ast.literal_eval(data_obj)
-         else:
-            data_dict = data_obj
-    
-        if layout and isinstance(layout, list):
-           layout_obj = layout[0]
-        else:
-           layout_obj = layout
-
-        if layout_obj and isinstance(layout_obj, str):
-           layout_dict = ast.literal_eval(layout_obj)
-        else:
-           layout_dict = layout_obj
-
-        #Applying stylings and settings generated from LLM
-        if layout_dict:
+   data_dict = {}   
+   for data_obj in data_list:   
+      if isinstance(data_obj, str):
+         data_obj = data_obj.replace("\n", "")
+         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 layout and isinstance(layout, list):
+      layout_obj = layout[0]
+   else:
+      layout_obj = layout
+
+   if layout_obj and isinstance(layout_obj, str):
+      layout_dict = ast.literal_eval(layout_obj)
+   else:
+      layout_dict = layout_obj
+
+   return data_dict, layout_dict
+
+def scatter_chart_fig(df, x_column: List[str], y_column: str, category: str="", trendline: str="", 
+                      trendline_options: List[dict]=[{}], marginal_x: str="", marginal_y: str=""):
+   
+   function_args = {"data_frame":df, "x":x_column, "y":y_column}
+
+   if category:
+      function_args["color"] = category
+   if trendline:
+      function_args["trendline"] = trendline
+   if marginal_x:
+      function_args["marginal_x"] = marginal_x
+   if marginal_y:
+      function_args["marginal_y"] = marginal_y
+   if trendline_options:
+      trendline_options_dict = {}
+      if trendline_options and isinstance(trendline_options, list):
+         trendline_options_obj = trendline_options[0]
+      else:
+         trendline_options_obj = trendline_options
+
+      if trendline_options_obj and isinstance(trendline_options_obj, str):
+         trendline_options_dict = ast.literal_eval(trendline_options_obj)
+      else:
+         trendline_options_dict = trendline_options_obj
+      function_args["trendline_options"] = trendline_options_dict
+
+   fig = px.scatter(**function_args)  
+
+   return fig
+
+def scatter_chart_generation_func(x_column: List[str], y_column: str, session_hash, data: List[dict]=[{}], layout: List[dict]=[{}], 
+                                  category: str="", trendline: str="", trendline_options: List[dict]=[{}], marginal_x: str="", marginal_y: str=""):
+   try:
+      dir_path = TEMP_DIR / str(session_hash)
+      chart_path = f'{dir_path}/chart.html'
+      csv_query_path = f'{dir_path}/query.csv'
+
+      df = pd.read_csv(csv_query_path)
+
+      initial_graph = scatter_chart_fig(df, x_column=x_column, y_column=y_column, 
+                              category=category, trendline=trendline, trendline_options=trendline_options,
+                              marginal_x=marginal_x, marginal_y=marginal_y)
+      
+      fig = initial_graph.to_dict()
+
+      data_dict,layout_dict = llm_chart_data_scrub(data,layout)
+
+      print(data_dict)
+      print(layout_dict)
+
+      #Applying stylings and settings generated from LLM
+      if layout_dict:
          fig["layout"] = layout_dict
 
-        for key, value in data_dict.items():
-           if key not in ["x","y","type"]:
+      for key, value in data_dict.items():
+         if key not in ["x","y","type"]:
             for data_item in fig["data"]:
                data_item[key] = value
-     
-        pio.write_html(fig, chart_path, full_html=False)
+   
+      pio.write_html(fig, chart_path, full_html=False)
 
-        chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
+      chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
 
-        iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
+      iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
 
-        return {"reply": iframe}
-    
-    except Exception as e:
-      print("CHART ERROR")
+      return {"reply": iframe}
+
+   except Exception as e:
+      print("SCATTER PLOT ERROR")
       print(e)
-      reply = f"""There was an error generating the Plotly Chart from {x_column}, {y_column}, {graph_type}, and {layout}
-              The error is {e},
-              You should probably try again.
-              """
+      reply = f"""There was an error generating the Plotly Scatter Plot from {x_column}, {y_column}, {data}, and {layout}
+            The error is {e},
+            You should probably try again.
+            """
+      return {"reply": reply}
+   
+def line_chart_generation_func(data: List[dict], x_column: str, y_column: str, session_hash, layout: List[dict]=[{}], 
+                                  category: str=""):
+   try:
+      dir_path = TEMP_DIR / str(session_hash)
+      chart_path = f'{dir_path}/chart.html'
+      csv_query_path = f'{dir_path}/query.csv'
+
+      df = pd.read_csv(csv_query_path)
+
+      function_args = {"data_frame":df, "x":x_column, "y":y_column}
+
+      if category:
+         function_args["color"] = category
+
+      initial_graph = px.line(**function_args)  
+
+      fig = initial_graph.to_dict()
+
+      data_dict,layout_dict = llm_chart_data_scrub(data,layout)
+
+      print(data_dict)
+      print(layout_dict)
+
+      #Applying stylings and settings generated from LLM
+      if layout_dict:
+         fig["layout"] = layout_dict
+
+      for key, value in data_dict.items():
+         if key not in ["x","y","type"]:
+            for data_item in fig["data"]:
+               data_item[key] = value
+
+      print(fig)       
+   
+      pio.write_html(fig, chart_path, full_html=False)
+
+      chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
+
+      iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
+
+      return {"reply": iframe}
+
+   except Exception as e:
+      print("LINE CHART ERROR")
+      print(e)
+      reply = f"""There was an error generating the Plotly Line Chart from {x_column}, {y_column}, {data}, and {layout}
+            The error is {e},
+            You should probably try again.
+            """
+      return {"reply": reply}
+
+def bar_chart_generation_func(data: List[dict], x_column: str, y_column: str, session_hash, layout: List[dict]=[{}], 
+                                  category: str="", facet_row: str="", facet_col: str=""):
+   try:
+      dir_path = TEMP_DIR / str(session_hash)
+      chart_path = f'{dir_path}/chart.html'
+      csv_query_path = f'{dir_path}/query.csv'
+
+      df = pd.read_csv(csv_query_path)
+
+      function_args = {"data_frame":df, "x":x_column, "y":y_column}
+
+      if category:
+         function_args["color"] = category
+      if facet_row:
+         function_args["facet_row"] = facet_row
+      if facet_col:
+         function_args["facet_col"] = facet_col
+
+      initial_graph = px.bar(**function_args)  
+
+      fig = initial_graph.to_dict()
+
+      data_dict,layout_dict = llm_chart_data_scrub(data,layout)
+
+      print(data_dict)
+      print(layout_dict)
+
+      #Applying stylings and settings generated from LLM
+      if layout_dict:
+         fig["layout"] = layout_dict
+
+      for key, value in data_dict.items():
+         if key not in ["x","y","type"]:
+            for data_item in fig["data"]:
+               data_item[key] = value
+
+      print(fig)       
+   
+      pio.write_html(fig, chart_path, full_html=False)
+
+      chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
+
+      iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
+
+      return {"reply": iframe}
+
+   except Exception as e:
+      print("BAR CHART ERROR")
+      print(e)
+      reply = f"""There was an error generating the Plotly Bar Chart from {x_column}, {y_column}, {data}, and {layout}
+            The error is {e},
+            You should probably try again.
+            """
+      return {"reply": reply}
+
+def pie_chart_generation_func(data: List[dict], values: str, names: str, session_hash, layout: List[dict]=[{}]):
+   try:
+      dir_path = TEMP_DIR / str(session_hash)
+      chart_path = f'{dir_path}/chart.html'
+      csv_query_path = f'{dir_path}/query.csv'
+
+      df = pd.read_csv(csv_query_path)
+
+      function_args = {"data_frame":df, "values":values, "names":names}
+
+      initial_graph = px.pie(**function_args)  
+
+      fig = initial_graph.to_dict()
+
+      data_dict,layout_dict = llm_chart_data_scrub(data,layout)
+
+      print(data_dict)
+      print(layout_dict)
+
+      #Applying stylings and settings generated from LLM
+      if layout_dict:
+         fig["layout"] = layout_dict
+
+      for key, value in data_dict.items():
+         if key not in ["x","y","type"]:
+            for data_item in fig["data"]:
+               data_item[key] = value
+
+      print(fig)       
+   
+      pio.write_html(fig, chart_path, full_html=False)
+
+      chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
+
+      iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
+
+      return {"reply": iframe}
+
+   except Exception as e:
+      print("PIE CHART ERROR")
+      print(e)
+      reply = f"""There was an error generating the Plotly Pie Chart from {values}, {names}, {data}, and {layout}
+            The error is {e},
+            You should probably try again.
+            """
+      return {"reply": reply}
+   
+def histogram_generation_func(x_column: str, session_hash, y_column: str="", data: List[dict]=[{}], layout: List[dict]=[{}], histnorm: str="", category: str="",
+                              histfunc: str=""):   
+   try:
+      dir_path = TEMP_DIR / str(session_hash)
+      chart_path = f'{dir_path}/chart.html'
+      csv_query_path = f'{dir_path}/query.csv'
+
+      df = pd.read_csv(csv_query_path)
+
+      print(df)
+      print(x_column)
+
+      function_args = {"data_frame":df, "x":x_column}
+
+      if y_column:
+         function_args["y"] = y_column
+      if histnorm:
+         function_args["histnorm"] = histnorm
+      if category:
+         function_args["color"] = category
+      if histfunc:
+         function_args["histfunc"] = histfunc
+
+      initial_graph = px.histogram(**function_args)  
+
+      fig = initial_graph.to_dict()
+
+      data_dict,layout_dict = llm_chart_data_scrub(data,layout)
+
+      print(data_dict)
+      print(layout_dict)
+
+      #Applying stylings and settings generated from LLM
+      if layout_dict:
+         fig["layout"] = layout_dict
+
+      for key, value in data_dict.items():
+         if key not in ["x","y","type"]:
+            for data_item in fig["data"]:
+               data_item[key] = value
+
+      print(fig)       
+   
+      pio.write_html(fig, chart_path, full_html=False)
+
+      chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/chart.html'
+
+      iframe = '<div style=overflow:auto;><iframe\n    scrolling="yes"\n    width="1000px"\n    height="500px"\n    src="' + chart_url + '"\n    frameborder="0"\n    allowfullscreen\n></iframe>\n</div>'
+
+      return {"reply": iframe}
+
+   except Exception as e:
+      print("HISTOGRAM ERROR")
+      print(e)
+      reply = f"""There was an error generating the Plotly Histogram from {x_column}.
+            The error is {e},
+            You should probably try again.
+            """
       return {"reply": reply}
 
 def table_generation_func(session_hash):

functions/chat_functions.py

@@ -36,10 +36,15 @@ def example_question_generator(session_hash):
     return example_response["replies"][0].text
 
 def chatbot_with_fc(message, history, session_hash):
-    from functions import sqlite_query_func, chart_generation_func, table_generation_func, regression_func
+    from functions import sqlite_query_func, table_generation_func, regression_func, scatter_chart_generation_func, \
+        line_chart_generation_func,bar_chart_generation_func,pie_chart_generation_func,histogram_generation_func
     import tools
 
-    available_functions = {"sql_query_func": sqlite_query_func, "chart_generation_func": chart_generation_func, "table_generation_func":table_generation_func, "regression_func":regression_func }
+    available_functions = {"sql_query_func": sqlite_query_func,"table_generation_func":table_generation_func,
+                           "line_chart_generation_func":line_chart_generation_func,"bar_chart_generation_func":bar_chart_generation_func,
+                           "scatter_chart_generation_func":scatter_chart_generation_func, "pie_chart_generation_func":pie_chart_generation_func,
+                           "histogram_generation_func":histogram_generation_func,
+                           "regression_func":regression_func }
 
     if message_dict[session_hash] != None:
         message_dict[session_hash].append(ChatMessage.from_user(message))
@@ -47,8 +52,12 @@ def chatbot_with_fc(message, history, session_hash):
         messages = [
             ChatMessage.from_system(
                 """You are a helpful and knowledgeable agent who has access to an SQLite database which has a table called 'data_source'. 
-                You also have access to a chart function that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate charts and graphs and returns an iframe that we can display in our chat window.
                 You also have access to a function, called table_generation_func, that builds table formatted html.
+                You also have access to a scatter plot function, called scatter_chart_generation_func, that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate a scatter plot and returns an iframe that we can display in our chat window.
+                You also have access to a line chart function, called line_chart_generation_func, that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate a line chart and returns an iframe that we can display in our chat window.
+                You also have access to a bar graph function, called line_chart_generation_func, that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate a bar graph and returns an iframe that we can display in our chat window.
+                You also have access to a pie chart function, called pie_chart_generation_func, that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate a pie chart and returns an iframe that we can display in our chat window.
+                You also have access to a histogram function, called histogram_generation_func, that can take a query.csv file generated from our sql query and uses plotly dictionaries to generate a histogram and returns an iframe that we can display in our chat window.
                 You also have access to a linear regression function, called regression_func, that can take a query.csv file generated from our sql query and a list of column names for our independent and dependent variables and return a regression data string and a regression chart which is returned as an iframe."""
             )
         ]

functions/stat_functions.py

@@ -5,16 +5,14 @@ from utils import TEMP_DIR
 import plotly.express as px
 import plotly.io as pio
 import os
+from functions import scatter_chart_fig
 from dotenv import load_dotenv
 
 load_dotenv()
 
 root_url = os.getenv("ROOT_URL")
 
-def basic_stats_function(data_list: List[str]):
-   return
-
-def regression_func(independent_variables: List[str], dependent_variable: str, session_hash, category: str='', regression_type: str="ols"):
+def regression_func(independent_variables: List[str], dependent_variable: str, session_hash, category: str=''):
     print("LINEAR REGRESSION CALCULATION")
     print(independent_variables)
     print(dependent_variable)
@@ -26,9 +24,11 @@ def regression_func(independent_variables: List[str], dependent_variable: str, s
         df = pd.read_csv(csv_query_path)
 
         if category in df.columns:
-           fig = px.scatter(df, x=independent_variables, y=dependent_variable, color=category, trendline="ols")
+           fig = scatter_chart_fig(df=df, x_column=independent_variables,y_column=dependent_variable, 
+                                    category=category,trendline="ols")
         else:
-           fig = px.scatter(df, x=independent_variables, y=dependent_variable, trendline="ols")
+           fig = scatter_chart_fig(df=df,x_column=independent_variables,y_column=dependent_variable, 
+                                    trendline="ols")
 
         pio.write_html(fig, chart_path, full_html=False)
 

tools.py

@@ -12,14 +12,16 @@ def tools_call(session_hash):
     cur.close()
     connection.close()
 
+    column_string = (columns[:625] + '..') if len(columns) > 625 else columns
+
     return [
         {
             "type": "function",
             "function": {
                 "name": "sql_query_func",
-                "description": f"""This a tool useful to query a SQLite table called 'data_source' with the following Columns: {columns}.
-                This function also saves the results of the query to csv file called query.csv. This is useful when query results are too large to process
-                or need to be used in an another function.""",
+                "description": f"""This is a tool useful to query a SQLite table called 'data_source' with the following Columns: {column_string}.
+                There may also be more columns in the table if the number of columns is too large to process. 
+                This function also saves the results of the query to csv file called query.csv.""",
                 "parameters": {
                     "type": "object",
                     "properties": {
@@ -38,8 +40,8 @@ def tools_call(session_hash):
         {
         "type": "function",
             "function": {
-                "name": "chart_generation_func",
-                "description": f"""This a chart generation tool useful to generate charts and graphs from queried data from our SQL table called 'data_source.
+                "name": "scatter_chart_generation_func",
+                "description": f"""This is a scatter plot generation tool useful to generate scatter plots from queried data from our SQL table called 'data_source'.
                 The data values will come from the columns of our query.csv (the 'x' and 'y' values of each graph) file but the layout section of the plotly dictionary objects will be generated by you.
                 Returns an iframe string which will be displayed inline in our chat window. Do not edit the string returned 
                 from the chart_generation_func function in any way and display it fully to the user in the chat window. You can add your own text supplementary 
@@ -58,8 +60,9 @@ def tools_call(session_hash):
                             }
                         },
                         "x_column": {
-                            "type": "string",
-                            "description": f"""The column in our query.csv file that contain the x values of the graph.""",
+                            "type": "array",
+                            "description": f"""An array of strings that correspond to the the columns in our query.csv file that contain the x values of the graph. There can be more than one column
+                            that can each be plotted against the y_column, if needed.""",
                             "items": {
                                 "type": "string",
                             }
@@ -78,16 +81,45 @@ def tools_call(session_hash):
                                 "type": "string",
                             }
                         },
-                        "graph_type": {
+                        "trendline": {
                             "type": "string",
-                            "description": f"""The type of plotly graph we wish to generate.
-                             This graph_type value can be one of ['bar','scatter','line','pie']. 
+                            "description": f"""An optional field to specify the type of plotly trendline we wish to use in the scatter plot.
+                             This trendline value can be one of ['ols','lowess','rolling','ewm','expanding']. 
                              Do not send any values outside of this array as the function will fail. 
                              Infer this from the user's message.""",
                             "items": {
                                 "type": "string",
                             }
                         },
+                        "trendline_options": {
+                            "type": "array",
+                            "description": """An array containing a dictionary that contains the 'trendline_options' portion of the plotly chart generation.
+                            The 'lowess', 'rolling', and 'ewm' options require trendline_options to be included.
+                            The array must contain a dictionary, any other format will not work.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "marginal_x": {
+                            "type": "string",
+                            "description": f"""The type of marginal distribution plot we'd like to specify for the plotly scatter plot for the x axis.
+                             This marginal_x value can be one of ['histogram','rug','box','violin']. 
+                             Do not send any values outside of this array as the function will fail. 
+                             Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },  
+                        "marginal_y": {
+                            "type": "string",
+                            "description": f"""The type of marginal distribution plot we'd like to specify for the plotly scatter plot for the y axis.
+                             This marginal_y value can be one of ['histogram','rug','box','violin']. 
+                             Do not send any values outside of this array as the function will fail. 
+                             Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },                                               
                         "layout": {
                             "type": "array",
                             "description": """An array containing a dictionary that contains the 'layout' portion of the plotly chart generation. 
@@ -97,11 +129,263 @@ def tools_call(session_hash):
                             }
                         }
                     },
-                    "required": ["graph_type","x_column","y_column","layout"],
+                    "required": ["x_column","y_column"],
+                },
+            }, 
+        }, 
+        {
+        "type": "function",
+            "function": {
+                "name": "line_chart_generation_func",
+                "description": f"""This is a line chart generation tool useful to generate line charts from queried data from our SQL table called 'data_source'.
+                The data values will come from the columns of our query.csv (the 'x' and 'y' values of each graph) file but the layout section of the plotly dictionary objects will be generated by you.
+                Returns an iframe string which will be displayed inline in our chat window. Do not edit the string returned 
+                from the chart_generation_func function in any way and display it fully to the user in the chat window. You can add your own text supplementary 
+                to it for context if desired.""",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "data": {
+                            "type": "array",
+                            "description": """The array containing a dictionary that contains the 'data' portion of the plotly chart generation and will include the options requested by the user. 
+                            The array must contain a dictionary, any other format will not work. 
+                            Do not include the 'x' or 'y' portions of the object as this will come from the query.csv file generated by our SQLite query. 
+                            Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "x_column": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contain the x values of the graph.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "y_column": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contain the y values of the graph.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "category": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contain a parameter that will define the category for the data.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },                                               
+                        "layout": {
+                            "type": "array",
+                            "description": """An array containing a dictionary that contains the 'layout' portion of the plotly chart generation. 
+                            The array must contain a dictionary, any other format will not work.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        }
+                    },
+                    "required": ["x_column","y_column","layout"],
+                },
+            }, 
+        }, 
+        {
+        "type": "function",
+            "function": {
+                "name": "bar_chart_generation_func",
+                "description": f"""This is a bar chart generation tool useful to generate line charts from queried data from our SQL table called 'data_source'.
+                The data values will come from the columns of our query.csv (the 'x' and 'y' values of each graph) file but the layout section of the plotly dictionary objects will be generated by you.
+                Returns an iframe string which will be displayed inline in our chat window. Do not edit the string returned 
+                from the chart_generation_func function in any way and display it fully to the user in the chat window. You can add your own text supplementary 
+                to it for context if desired.""",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "data": {
+                            "type": "array",
+                            "description": """The array containing a dictionary that contains the 'data' portion of the plotly chart generation and will include the options requested by the user. 
+                            The array must contain a dictionary, any other format will not work. 
+                            Do not include the 'x' or 'y' portions of the object as this will come from the query.csv file generated by our SQLite query. 
+                            Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "x_column": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contains the x values of the graph.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "y_column": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contains the y values of the graph.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "category": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contains a parameter that will define the category for the data.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "facet_row": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contains a parameter that will define a faceted subplot, where different rows
+                            correspond to different values of the query specified in this parameter.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "facet_col": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contain a parameter that will define the faceted column, corresponding to 
+                            different values of our query specified in this parameter.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },                                            
+                        "layout": {
+                            "type": "array",
+                            "description": """An array containing a dictionary that contains the 'layout' portion of the plotly chart generation. 
+                            The array must contain a dictionary, any other format will not work.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        }
+                    },
+                    "required": ["x_column","y_column","layout"],
+                },
+            }, 
+        },  
+        {
+        "type": "function",
+            "function": {
+                "name": "pie_chart_generation_func",
+                "description": f"""This is a pie chart generation tool useful to generate pie charts from queried data from our SQL table called 'data_source'.
+                The data values will come from the columns of our query.csv (the 'values' and 'names' values of each graph) file but the layout section of the plotly dictionary objects will be generated by you.
+                Returns an iframe string which will be displayed inline in our chat window. Do not edit the string returned 
+                from the chart_generation_func function in any way and display it fully to the user in the chat window. You can add your own text supplementary 
+                to it for context if desired.""",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "data": {
+                            "type": "array",
+                            "description": """The array containing a dictionary that contains the 'data' portion of the plotly chart generation and will include the options requested by the user. 
+                            The array must contain a dictionary, any other format will not work. 
+                            Do not include the 'x' or 'y' portions of the object as this will come from the query.csv file generated by our SQLite query. 
+                            Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "values": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contain the values of the pie chart.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "names": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contain the label or section of each piece of the pie graph and allow us to know what each piece of the pie chart represents.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },                                           
+                        "layout": {
+                            "type": "array",
+                            "description": """An array containing a dictionary that contains the 'layout' portion of the plotly chart generation. 
+                            The array must contain a dictionary, any other format will not work.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        }
+                    },
+                    "required": ["values","names","layout"],
                 },
             }, 
         },
         {
+        "type": "function",
+            "function": {
+                "name": "histogram_generation_func",
+                "description": f"""This is a histogram generation tool useful to generate histograms from queried data from our SQL table called 'data_source'.
+                The data values will come from the columns of our query.csv (the 'values' and 'names' values of each graph) file but the layout section of the plotly dictionary objects will be generated by you.
+                Returns an iframe string which will be displayed inline in our chat window. Do not edit the string returned 
+                from the chart_generation_func function in any way and display it fully to the user in the chat window. You can add your own text supplementary 
+                to it for context if desired.""",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "data": {
+                            "type": "array",
+                            "description": """The array containing a dictionary that contains the 'data' portion of the plotly chart generation and will include the options requested by the user. 
+                            The array must contain a dictionary, any other format will not work. 
+                            Do not include the 'x' or 'y' portions of the object as this will come from the query.csv file generated by our SQLite query. 
+                            Infer this from the user's message.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "x_column": {
+                            "type": "string",
+                            "description": f"""The column in our query.csv file that contains the x values of the histogram. 
+                            This would correspond to the counts that would be distributed in the histogram.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "y_column": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contains the y values of the histogram.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "histnorm": {
+                            "type": "string",
+                            "description": f"""An optional argument to specify the type of normalization if the default isn't used.
+                            This histnorm value can be one of ['percent','probability','density','probability density'].
+                            Do not send any values outside of this array as the function will fail.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        }, 
+                        "category": {
+                            "type": "string",
+                            "description": f"""An optional column in our query.csv file that contains a parameter that will define the category for the data.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },
+                        "histfunc": {
+                            "type": "string",
+                            "description": f"""An optional value that represents the function of data to compute the function which is used on the optional y column.
+                            This histfunc value can be one of ['avg','sum','count']. 
+                             Do not send any values outside of this array as the function will fail.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        },                                         
+                        "layout": {
+                            "type": "array",
+                            "description": """An array containing a dictionary that contains the 'layout' portion of the plotly chart generation. 
+                            The array must contain a dictionary, any other format will not work.""",
+                            "items": {
+                                "type": "string",
+                            }
+                        }
+                    },
+                    "required": ["x_column"],
+                },
+            }, 
+        },                     
+        {
         "type": "function",
             "function": {
                 "name": "table_generation_func",
@@ -150,14 +434,7 @@ def tools_call(session_hash):
                             "items": {
                                 "type": "string",
                             }
-                        },
-                        "regression_type": {
-                            "type": "string",
-                            "description": f"""A parameter that specifies the type of regression being used from the trendline options that plotly offers. Defaults to 'ols'.""",
-                            "items": {
-                                "type": "string",
-                            }
-                        },
+                        }
                     },
                     "required": ["independent_variables","dependent_variable"],
                 },