Update table function to use query.csv (#16)

- Update table function to use query.csv (58e8e451a0556a962a115be4e2b32efff8ab2af8)

functions/chart_functions.py

@@ -100,27 +100,14 @@ def chart_generation_func(data: List[str], x_column: str, y_column: str, graph_t
               """
       return {"reply": reply}
 
-def table_generation_func(data: List[dict], session_hash):
+def table_generation_func(session_hash):
     print("TABLE GENERATION")
-    print(data)
     try: 
         dir_path = TEMP_DIR / str(session_hash)
-        csv_path = f'{dir_path}/data.csv'
-
-        #Processing data to account for variation from LLM
-        if isinstance(data, list):
-           data_obj = data[0]
-        else:
-           data_obj = data
-
-        if isinstance(data_obj, str):
-           data_dict = ast.literal_eval(data_obj)
-        else:
-           data_dict = data_obj        
+        csv_query_path = f'{dir_path}/query.csv'
 
-        df = pd.DataFrame.from_dict(data_dict)
+        df = pd.read_csv(csv_query_path)
         print(df)
-        df.to_csv(csv_path)
 
         html_table = df.to_html()
         print(html_table)

functions/chat_functions.py

@@ -48,7 +48,7 @@ def chatbot_with_fc(message, history, session_hash):
             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 and generates a link to download as CSV.
+                You also have access to a function, called table_generation_func, that builds table formatted html.
                 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."""
             )
         ]

tools.py

@@ -103,27 +103,13 @@ def tools_call(session_hash):
         "type": "function",
             "function": {
                 "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. 
+                "description": f"""This an table generation tool useful to format data as a table from queried data from our SQL table called 'data_source'.
+                Takes no parameters as it uses data queried in our query.csv file to build the table.
+                Call this function after running our SQLite query and generating query.csv.
                 Returns an html string generated from the pandas library and pandas.to_html() 
                 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",
-                    "properties": {
-                        "data": {
-                            "type": "array",
-                            "description": """The data points to use in the table generation. Infer this from the user's message. 
-                            Send a python dictionary object with query data that correspond to data that will be converted into a pandas DataFrame and that correspond to the users request.
-                            The keys of this python dictionary object will be the names of the columns and values will be a list of values for each object.
-                            Make sure this is a dictionary object and not a string or an array.
-                            Send nothing else.""",
-                            "items": {
-                                "type": "string",
-                            }
-                        }
-                    },
-                    "required": ["data"],
-                },
+                "parameters": {},
             }, 
         },
         {