| from typing import List
|
| import plotly.io as pio
|
| import plotly.express as px
|
| import pandas as pd
|
| from utils import TEMP_DIR
|
| import os
|
| import ast
|
| from dotenv import load_dotenv
|
|
|
| load_dotenv()
|
|
|
| root_url = os.getenv("ROOT_URL")
|
|
|
| def llm_chart_data_scrub(data, layout):
|
|
|
| data_list = []
|
| layout_dict = {}
|
|
|
| if isinstance(data, list):
|
| data_list = data
|
| else:
|
| data_list.append(data)
|
|
|
| false_replace = [':false', ': false']
|
| false_value = ':False'
|
| true_replace = [':true', ': true']
|
| true_value = ':True'
|
|
|
| data_dict = {}
|
| for data_obj in data_list:
|
| if isinstance(data_obj, str):
|
| data_obj = data_obj.replace("\n", "")
|
| for replace in false_replace:
|
| data_obj = data_obj.replace(replace, false_value)
|
| for replace in true_replace:
|
| data_obj = data_obj.replace(replace, true_value)
|
| print(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):
|
| for replace in false_replace:
|
| layout_obj = layout_obj.replace(replace, false_value)
|
| for replace in true_replace:
|
| layout_obj = layout_obj.replace(replace, true_value)
|
| print(layout_obj)
|
| 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="",
|
| size: 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 size:
|
| df.loc[df[size] < 0, size] = 0
|
| function_args["size"] = size
|
| 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, session_folder, data: List[dict]=[{}], layout: List[dict]=[{}],
|
| category: str="", trendline: str="", trendline_options: List[dict]=[{}], marginal_x: str="", marginal_y: str="",
|
| size: str="", **kwargs):
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| 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, size=size)
|
|
|
| fig = initial_graph.to_dict()
|
|
|
| print(data)
|
| print(layout)
|
|
|
| data_dict,layout_dict = llm_chart_data_scrub(data,layout)
|
|
|
|
|
| if layout_dict:
|
| fig["layout"] = layout_dict
|
|
|
| data_ignore = ["x","y","type"]
|
|
|
| if size:
|
| data_ignore.append("marker")
|
|
|
| for key, value in data_dict.items():
|
| if key not in data_ignore:
|
| for data_item in fig["data"]:
|
| data_item[key] = value
|
|
|
| pio.write_html(fig, chart_path, full_html=False)
|
|
|
| chart_url = f'{root_url}/gradio_api/file/temp/{session_hash}/{session_folder}/chart.html'
|
|
|
| iframe = 'Please display this 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("SCATTER PLOT ERROR")
|
| print(e)
|
| 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(x_column: str, y_column: str, session_hash, session_folder, data: List[dict]=[{}], layout: List[dict]=[{}],
|
| category: str="", **kwargs):
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| 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)
|
|
|
|
|
| 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}/{session_folder}/chart.html'
|
|
|
| iframe = 'Please display this 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(x_column: str, y_column: str, session_hash, session_folder, data: List[dict]=[{}], layout: List[dict]=[{}],
|
| category: str="", facet_row: str="", facet_col: str="", **kwargs):
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| 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)
|
|
|
|
|
| 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}/{session_folder}/chart.html'
|
|
|
| iframe = 'Please display this 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(values: str, names: str, session_hash, session_folder, data: List[dict]=[{}], layout: List[dict]=[{}], **kwargs):
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| 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)
|
|
|
|
|
| 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}/{session_folder}/chart.html'
|
|
|
| iframe = 'Please display this 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, session_folder, y_column: str="", data: List[dict]=[{}], layout: List[dict]=[{}], histnorm: str="", category: str="",
|
| histfunc: str="", **kwargs):
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| chart_path = f'{dir_path}/chart.html'
|
| csv_query_path = f'{dir_path}/query.csv'
|
|
|
| df = pd.read_csv(csv_query_path)
|
|
|
| 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)
|
|
|
|
|
| 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}/{session_folder}/chart.html'
|
|
|
| iframe = 'Please display this 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, session_folder, **kwargs):
|
| print("TABLE GENERATION")
|
| try:
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_folder)
|
| csv_query_path = f'{dir_path}/query.csv'
|
| table_path = f'{dir_path}/table.html'
|
|
|
| df = pd.read_csv(csv_query_path)
|
|
|
| html_table = df.to_html()
|
| print(html_table[:1000])
|
|
|
| with open(table_path, "w") as file:
|
| file.write(html_table)
|
|
|
| table_url = f'{root_url}/gradio_api/file/temp/{session_hash}/{session_folder}/table.html'
|
|
|
| iframe = 'Please display this iframe: <div style=overflow:auto;><iframe\n scrolling="yes"\n width="1000px"\n height="500px"\n src="' + table_url + '"\n frameborder="0"\n allowfullscreen\n></iframe>\n</div>'
|
| print(iframe)
|
| return {"reply": iframe}
|
|
|
| except Exception as e:
|
| print("TABLE ERROR")
|
| print(e)
|
| reply = f"""There was an error generating the Pandas DataFrame table results.
|
| The error is {e},
|
| You should probably try again.
|
| """
|
| return {"reply": reply}
|
|
|
