app.py

# /// script
# [tool.marimo.display]
# custom_css = ["./custom_header_font.css"]
# ///

import marimo

__generated_with = "0.13.4"
app = marimo.App(
    width="full",
    app_title="watsonx-SheetProcessor-9000",
)


@app.cell
def _():
    import marimo as mo
    from typing import Dict, Optional, List, Union, Any, Set
    from ibm_watsonx_ai import APIClient, Credentials
    from pathlib import Path
    import pandas as pd
    import mimetypes
    import requests
    import zipfile
    import tempfile
    import base64
    import json
    import glob
    import ast
    import re
    import os
    import io
    return APIClient, Credentials, ast, io, mo, os, pd


@app.cell
def _():
    ### Loads baked in credentials if present
    from baked_in_credentials.creds import credentials
    from base_variables import wx_regions, wx_platform_url
    ### Loads helper functions
    from helper_functions.helper_functions import (
            get_cred_value,
            get_model_selection_table,
            filter_models_by_function,
            _enforce_model_selection,
            update_max_tokens_limit,
            get_key_by_value,
            markdown_spacing,
            load_file_dataframe,
            create_parameter_table,
            convert_table_to_json_docs,
            get_cell_values,
            wrap_with_spaces,
            load_templates
    )
    ### Table Related Helper Functions
    from helper_functions.table_helper_functions import (
            append_llm_results_to_dataframe,
            display_answers_as_markdown,
            display_answers_stacked,
            process_with_llm
    )
    return (
        append_llm_results_to_dataframe,
        convert_table_to_json_docs,
        create_parameter_table,
        credentials,
        get_cell_values,
        get_cred_value,
        get_key_by_value,
        get_model_selection_table,
        load_file_dataframe,
        load_templates,
        process_with_llm,
        wrap_with_spaces,
        wx_regions,
    )


@app.cell
def _(credentials, get_cred_value, mo, wx_regions):
    # Create a form with multiple elements
    baked_in_creds = credentials
    client_instantiation_form = (
        mo.md('''
        ###**watsonx.ai credentials:**

        {wx_region}

        {wx_api_key}

        {project_id}

        {space_id}
    ''')
        .batch(
            wx_region = mo.ui.dropdown(
                wx_regions, 
                label="Select your watsonx.ai region:", 
                value="US", 
                searchable=True
            ),
            wx_api_key = mo.ui.text(
                placeholder="Add your IBM Cloud api-key...", 
                label="IBM Cloud Api-key:", 
                kind="password", 
                value=get_cred_value('api_key', creds_var_name='baked_in_creds')
            ),
            project_id = mo.ui.text(
                placeholder="Add your watsonx.ai project_id...", 
                label="Project_ID:", 
                kind="text", 
                value=get_cred_value('project_id', creds_var_name='baked_in_creds')
            ),
            space_id = mo.ui.text(
                placeholder="Add your watsonx.ai space_id...", 
                label="Space_ID:", 
                kind="text",
                value=get_cred_value('space_id', creds_var_name='baked_in_creds')
            )
        ,)
        .form(show_clear_button=True, bordered=False)
    )

    return (client_instantiation_form,)


@app.cell
def _(client_section, mo):
    ui_accordion_section_1 = mo.accordion(
        {"Section 1: **watsonx.ai Credentials**": client_section}
    ) 
    ui_accordion_section_1
    return


@app.cell
def _(file_uploader, mo):
    ui_accordion_section_2 = mo.accordion(
        {"Section 2: **File Loading**": file_uploader}
    ) 
    ui_accordion_section_2
    return


@app.cell
def _(column_and_rows_sector, mo):
    ui_accordion_section_3 = mo.accordion(
        {"Section 3: **Column and Row Selection**": column_and_rows_sector}
    ) 
    ui_accordion_section_3
    return


@app.cell
def _(llm_setup, mo):
    ui_accordion_section_4 = mo.accordion(
        {"Section 4: **Model Setup**": llm_setup}
    ) 
    ui_accordion_section_4
    return


@app.cell
def _(mo, prompt_setup_stack):
    ui_accordion_section_5 = mo.accordion(
        {"Section 5: **Choose the Number of Prompts and Templates**": prompt_setup_stack}
    ) 
    ui_accordion_section_5
    return


@app.cell
def _(mo, prompt_stack):
    ui_accordion_section_6 = mo.accordion(
        {"Section 6: **Prompt Setup**": prompt_stack}
    ) 
    ui_accordion_section_6
    return


@app.cell
def _(client_instantiation_form, os):
    if client_instantiation_form.value:
        client_setup = client_instantiation_form.value
    else:
        client_setup = None

    ### Extract Credential Variables:
    if client_setup is not None:
        wx_url = client_setup["wx_region"]
        wx_api_key = client_setup["wx_api_key"]
        os.environ["WATSONX_APIKEY"] = wx_api_key
        project_id = client_setup.get("project_id")
        space_id = client_setup.get("space_id")
    else:
        os.environ["WATSONX_APIKEY"] = ""
        project_id = space_id = wx_api_key = wx_url = None
    return client_setup, project_id, space_id, wx_api_key, wx_url


@app.cell
def _(
    APIClient,
    Credentials,
    client_setup,
    project_id,
    space_id,
    wx_api_key,
    wx_url,
):
    if client_setup:
        wx_credentials = Credentials(url=wx_url, 
                                                api_key=wx_api_key)

        project_client = APIClient(credentials=wx_credentials, 
                                                project_id=project_id) if project_id else None

        deployment_client = APIClient(credentials=wx_credentials, 
                                                space_id=space_id) if space_id else None

    else:
        wx_credentials = project_client = deployment_client = None
    return deployment_client, project_client


@app.cell
def _(
    client,
    client_key,
    client_options,
    client_selector,
    get_key_by_value,
    mo,
    wrap_with_spaces,
):
    active_client_name = get_key_by_value(client_options,client_key)
    client_status = mo.md(f"### Client Instantiation Status will turn Green When Ready\n\n {client_selector}\n\n**Active Client:**{wrap_with_spaces(active_client_name, prefix_spaces=5)}")

    client_callout_kind = "success" if client is not None else "neutral"
    return client_callout_kind, client_status


@app.cell
def _(client_callout_kind, client_instantiation_form, client_status, mo):
    client_callout = mo.callout(client_status, kind=client_callout_kind)

    client_section = mo.hstack([client_instantiation_form, client_callout], align="center", justify="space-around")
    return (client_section,)


@app.cell
def _(deployment_client, mo, project_client):
    if project_client is not None and deployment_client is not None:
        client_options = {"Project Client":project_client, "Deployment Client":deployment_client}

    elif project_client is not None:
        client_options = {"Project Client":project_client}

    elif deployment_client is not None:
        client_options = {"Deployment Client":deployment_client}

    else:
        client_options = {"No Client": "Instantiate a Client"}

    default_client = next(iter(client_options))
    client_selector = mo.ui.dropdown(client_options, value=default_client, label="**Switch your active client:**")
    return client_options, client_selector


@app.cell
def _(client_selector):
    client_key = client_selector.value
    if client_key == "Instantiate a Client":
        client = None
    else:
        client = client_key
    return client, client_key


@app.cell
def _(mo):
    file =  mo.ui.file(
            kind="area",
            filetypes=[".xlsx", ".xls", ".csv", ".json"],
            label="Upload a file (CSV, Excel, or JSON)"
        )
    return (file,)


@app.cell
def _(file, io, mo, os, pd):
    def get_file_extension(filename):
        """Get the file extension from a filename."""
        if not filename:
            return None
        return os.path.splitext(filename)[1].lower()

    # Initialize variables
    sheet_names = []
    file_extension = None
    excel_data = None

    if file.contents():
        file_extension = get_file_extension(file.name())

        # Handle Excel files to get sheet names
        if file_extension in ['.xlsx', '.xls']:
            # For Excel files
            excel_data = io.BytesIO(file.contents())
            # Get sheet names without loading the data yet
            sheet_names = pd.ExcelFile(excel_data).sheet_names

    # Create sheet selector for Excel files
    if file_extension in ['.xlsx', '.xls'] and sheet_names:
        sheet_selector = mo.ui.dropdown(
            options=sheet_names,
            value=sheet_names[0],
            label="Select Sheet:",
            full_width=False,
            searchable=True
        )
    else:
        sheet_selector = None
    return excel_data, file_extension, sheet_selector


@app.cell
def _(mo, table_dataframe_raw):
    if not table_dataframe_raw.empty:
        apply_header_readjustment = mo.ui.checkbox(label="Activate Header Adjustment")
    else:
        apply_header_readjustment = None
    return (apply_header_readjustment,)


@app.cell
def _(mo):
    show_variable_sidebar = mo.ui.checkbox(label="Show Sidebar with Input Variables", value=False)
    return (show_variable_sidebar,)


@app.cell
def _(apply_header_readjustment, mo, sheet_selector, table_dataframe_raw):
    if not table_dataframe_raw.empty:
        if apply_header_readjustment.value:
            header_row = mo.ui.number(
                label="Header Row index:",
                value=0,
                start=0,
                stop=len(table_dataframe_raw)+1
            )
        else:
            header_row = mo.ui.number(
                label="Header Row index:",
                value=0,
                start=0,
                stop=0
            )
    else:
        header_row = None

    sheet_and_column_controls = mo.hstack([sheet_selector, apply_header_readjustment, header_row], gap=2, justify="space-around")
    return header_row, sheet_and_column_controls


@app.cell
def _(file, mo, sheet_and_column_controls):
    if file.name():
        name_printout = mo.md(f"**{file.name()}**")
    else:
        name_printout = mo.md(f"No File Uploaded")

    file_uploader = mo.vstack([file,name_printout, sheet_and_column_controls], justify="space-around", align="center")
    return (file_uploader,)


@app.function
def apply_header_row(table_dataframe, header_row_value):
    """
    Set a specific row as the header for a dataframe.

    Parameters:
    -----------
    table_dataframe : pd.DataFrame
        The dataframe to modify
    header_row_value : int
        Row index to use as header (0-based)

    Returns:
    --------
    tuple : (pd.DataFrame, list)
        Modified dataframe with new headers and list of column names
    """
    if not table_dataframe.empty:
        # Convert header row to column names
        new_header = table_dataframe.iloc[header_row_value]
        # Create new dataframe without the header row
        new_df = table_dataframe.iloc[header_row_value+1:]
        # Set the new header
        new_df.columns = new_header
        # Get list of column names
        column_names = list(new_df.columns)
        return new_df, column_names
    return table_dataframe, []


@app.cell
def _(excel_data, file, file_extension, load_file_dataframe, sheet_selector):
    table_dataframe_raw, table_column_names_raw = load_file_dataframe(file=file, 
                                    file_extension=file_extension,
                                    sheet_selector=sheet_selector, 
                                    excel_data=excel_data)
    return table_column_names_raw, table_dataframe_raw


@app.cell
def _(
    apply_header_readjustment,
    header_row,
    table_column_names_raw,
    table_dataframe_raw,
):
    if apply_header_readjustment is not None and apply_header_readjustment.value:
        table_dataframe, table_column_names = apply_header_row(table_dataframe_raw, header_row_value=header_row.value if header_row is not None else 0)
    else:
        table_dataframe, table_column_names = table_dataframe_raw, table_column_names_raw
    return table_column_names, table_dataframe


@app.cell
def _(mo, pd, table_column_names, table_dataframe):
    if not table_dataframe.empty:
        center_column_text = {col: "center" for col in table_column_names}
        table = mo.ui.table(table_dataframe, 
                                      show_column_summaries=False,
                                      initial_selection=[0],
                                      wrapped_columns=table_column_names, 
                                      text_justify_columns=center_column_text, 
                                      label="**Select the Rows to Process**")
    else:
        table = (
            mo.md('''###**No data available in the uploaded file**''')
            .batch(upload_a_file = mo.ui.table(data=pd.DataFrame(
                                                                                   {"Upload File":"No File"}, 
                                                                                  index=[0])
                        )
                  )
            )
    return (table,)


@app.cell
def _(create_parameter_table, table_column_names, table_dataframe):
    if not table_dataframe.empty:
        column_selector = create_parameter_table(
                                               label="Select the Columns to Process",
                                               input_list=table_column_names,
                                               column_name="Column Options", 
                                               selection_type="multi-cell", 
                                               text_justify="center"
                                              )
    else:
        column_selector = create_parameter_table(
                                               label="Select the Columns to Process",
                                               input_list=[],
                                               column_name="Column Options", 
                                               selection_type="multi-cell", 
                                               text_justify="center"
                                              )

    return (column_selector,)


@app.cell
def _(column_selector, get_cell_values):
    columns_to_use = get_cell_values(column_selector)
    return (columns_to_use,)


@app.cell
def _(column_selector, mo, table):
    column_and_rows_sector = mo.vstack([column_selector, table], align="stretch", justify="start")
    return (column_and_rows_sector,)


@app.cell
def _(columns_to_use, convert_table_to_json_docs, pd, table):
    if table.value is not None:
        selected_rows = table.value
        fields_to_process = convert_table_to_json_docs(selected_rows, selected_columns=columns_to_use)
    else:
        selected_rows = pd.DataFrame([])
        fields_to_process = []
    return fields_to_process, selected_rows


@app.cell
def _(client, get_model_selection_table):
    if client is not None:
        model_selector, resources, model_id_list = get_model_selection_table(client=client, 
                                                                                                                        model_type="chat",
                                                                                                                        filter_functionality=None,
                                                                                                                        selection_mode="single-cell"
                                                                                                                        )
    else:
        model_selector = get_model_selection_table(client=None, selection_mode="single-cell")
        resources = model_id_list = None
    return (model_selector,)


@app.cell
def _(mo, model_selector):
    from ibm_watsonx_ai.foundation_models import ModelInference
    from ibm_watsonx_ai.metanames import GenTextParamsMetaNames as GenParams
    # Create a form with multiple elements
    llm_parameters = (
        mo.md('''
        ###**LLM parameters:**

        {decoding_method}

        {repetition_penalty}

        {min_tokens}

        {max_tokens}

        {stop_sequences}
    ''')
        .batch(
            ### Preset Options
            decoding_method = mo.ui.dropdown(options=["greedy", "sample"], value="greedy",label="Decoding Method:"),
            min_tokens = mo.ui.number(start=1, stop=1, label="Minimum Output Tokens:"),
            max_tokens = mo.ui.number(start=1, stop=8096, value=500, label="Maximum Output Tokens:"),
            repetition_penalty = mo.ui.number(start=1.0, stop=2.0, step=0.01, label="Repetition Penalty:"),
            stop_sequences = mo.ui.text(label="Stopping Sequences:", value="['<|end_of_text|>','</s>']", placeholder="List of Strings, e.g. ['<|end_of_text|>','</s>']", full_width=False)
        )
    )

    llm_setup = mo.hstack([model_selector, llm_parameters], align="center", justify="space-around")
    return GenParams, ModelInference, llm_parameters, llm_setup


@app.cell
def _(model_selector):
    if model_selector.value:
        selected_model = model_selector.value[0]['value']
    else:
        selected_model = "mistralai/mistral-large"
    return (selected_model,)


@app.cell
def _(GenParams, ModelInference, ast, client, llm_parameters, selected_model):
    if llm_parameters.value:
        params = {
            GenParams.DECODING_METHOD: llm_parameters.value['decoding_method'],
            GenParams.MAX_NEW_TOKENS: llm_parameters.value['max_tokens'],
            GenParams.MIN_NEW_TOKENS: llm_parameters.value['min_tokens'],
            GenParams.REPETITION_PENALTY: llm_parameters.value['repetition_penalty'],
            GenParams.STOP_SEQUENCES: ast.literal_eval(llm_parameters.value['stop_sequences']),
            GenParams.RETURN_OPTIONS: {
                'input_text': False,
                'generated_tokens': False,
                'input_tokens': True,
                'token_logprobs': False
            }
        }
    else:
        params = {}

    if client:
        inf_model = ModelInference(api_client=client, model_id=selected_model, params=params)
    else:
        inf_model = None
    return inf_model, params


@app.cell
def _(mo):
    prompt_template_folders = get_subfolder_paths("watsonx Sheet Processor MNB/prompt_templates", depth=1)
    prompt_template_model_paths = mo.ui.dropdown(options=prompt_template_folders, label="Prompt Template Variants *(Select Based on your Model)*")
    return (prompt_template_model_paths,)


@app.cell
def _(load_templates, prompt_template_model_paths):
    template_folder = str(prompt_template_model_paths.value)
    templates = load_templates(template_folder)
    return (templates,)


@app.cell
def _(mo):
    prompt_number_slider = mo.ui.slider(start=1, stop=5, value=1, step=1, label="Prompt Templates", show_value=True)
    return (prompt_number_slider,)


@app.cell
def _(mo, prompt_number_slider, prompt_template_model_paths):
    prompt_mechanics_stack = mo.vstack([prompt_number_slider, prompt_template_model_paths], align="start")
    return (prompt_mechanics_stack,)


@app.cell
def _(mo, prompt_mechanics_stack, template_selector_stack):
    prompt_setup_stack = mo.hstack([prompt_mechanics_stack, template_selector_stack], justify="space-around")
    return (prompt_setup_stack,)


@app.cell
def _(mo):
    get_pt_state, set_pt_state = mo.state(None)
    return get_pt_state, set_pt_state


@app.function
def get_subfolder_paths(base_path, depth=1):
    """Lists subfolder paths up to specified depth.

    Args:
        base_path: Directory to search in
        depth: Subdirectory levels to traverse (default: 1)

    Returns:
        Dict with folder names as keys and paths as values
    """
    import os

    result = {}
    if depth <= 0 or not os.path.isdir(base_path):
        return result

    for entry in os.scandir(base_path):
        if entry.is_dir():
            result[entry.name] = entry.path
            if depth > 1:
                # Recursively get subdirectories
                subfolders = get_subfolder_paths(entry.path, depth - 1)
                # Update result with subfolders
                result.update(subfolders)

    return result


@app.cell
def _(mo, prompt_number_slider, set_pt_state, templates):
    def update_state_from_templates(value):
        # Get current values from all template selectors
        template_values = [selector.value for selector in template_selectors]

        # Update the state with the list of values
        set_pt_state(template_values)

        # Return the list of values
        return template_values

    def create_template_dropdowns(num=1):
        return mo.ui.dropdown(
            options=templates,
            label=f"**Select Prompt {num} Template with Syntax:**", 
            value="empty", 
            on_change=update_state_from_templates
        )

    template_selectors = [create_template_dropdowns(i) for i in range(1, prompt_number_slider.value+1)]
    template_selector_stack = mo.vstack(template_selectors, align="start")
    return (template_selector_stack,)


@app.cell
def _(fields_to_process):
    if fields_to_process:
        variable_names = [key for key in fields_to_process[0].keys() 
                         if key != "_marimo_row_id" and key != "upload_a_file"]
    else:
        variable_names = []
    return (variable_names,)


@app.cell
def _(prompt_number_slider):
    def is_disabled(button_num):
        return prompt_number_slider.value < button_num
    return (is_disabled,)


@app.cell
def _(mo):
    def create_stats_from_variables(variable_names):
        """
        Creates mo.stat objects for each variable name in the list.
        Labels are formatted as "Column Variable Tag: {index+1}"
        Values display the variable name itself.
        """
        stats = []

        for i, var_name in enumerate(variable_names):
            stat = mo.stat(
                value=f"{{{var_name}}}",
                label=f"Column Variable Tag {i+1}",
                bordered=True
            )
            stats.append(stat)

        return mo.sidebar(stats, width="375")
    return (create_stats_from_variables,)


@app.cell
def _(create_stats_from_variables, variable_names):
    if variable_names:
        prompt_input_variables_sidebar = create_stats_from_variables(variable_names)
    else:
        prompt_input_variables_sidebar = None
    return (prompt_input_variables_sidebar,)


@app.cell
def _(get_pt_state, mo, prompt_number_slider):
    def create_prompt(num=1):
        # Wrap in a function to create reactive dependency on state
        def get_template_content(num=1):
            content = get_pt_state()[num-1] if get_pt_state() and num-1 < len(get_pt_state()) else "empty"
            return content

        prompt_column_label = mo.ui.text(label=f"**Add output column name for Prompt {num}:**", value=f"Added Column {num}")
        prompt_editor = mo.ui.code_editor(value=get_template_content(num), language="python", min_height=300, theme="dark")

        return [
            prompt_column_label,
            prompt_editor
        ]

    prompts_raw = [create_prompt(i) for i in range(1, prompt_number_slider.value+1)]
    return (prompts_raw,)


@app.cell
def _(is_disabled, mo):
    run_prompt_button_1 = mo.ui.run_button(label="Run Prompt 1", disabled=is_disabled(1))
    return (run_prompt_button_1,)


@app.cell
def _(is_disabled, mo):
    run_prompt_button_2 = mo.ui.run_button(label="Run Prompt 2", disabled=is_disabled(2))
    return (run_prompt_button_2,)


@app.cell
def _(is_disabled, mo):
    run_prompt_button_3 = mo.ui.run_button(label="Run Prompt 3", disabled=is_disabled(3))
    return (run_prompt_button_3,)


@app.cell
def _(is_disabled, mo):
    run_prompt_button_4 = mo.ui.run_button(label="Run Prompt 4", disabled=is_disabled(4))
    return (run_prompt_button_4,)


@app.cell
def _(is_disabled, mo):
    run_prompt_button_5 = mo.ui.run_button(label="Run Prompt 5", disabled=is_disabled(5))
    return (run_prompt_button_5,)


@app.cell
def _(
    append_llm_results_to_dataframe,
    fields_to_process,
    inf_model,
    params,
    process_with_llm,
    prompts_raw,
    results_table,
    run_prompt_button_1,
    selected_rows,
):
    if run_prompt_button_1.value:
        prompt_answers_1 = process_with_llm(fields_to_process=fields_to_process, 
                                           prompt_template=prompts_raw[0][1].value,
                                           inf_model=inf_model, params=params, batch_size=10)
        append_llm_results_to_dataframe(target_dataframe=results_table, fields_to_process=fields_to_process, llm_results=prompt_answers_1, selection_table=selected_rows, column_name=prompts_raw[0][0].value)
    else:
        prompt_answers_1 = []
    return


@app.cell
def _(
    append_llm_results_to_dataframe,
    fields_to_process,
    inf_model,
    params,
    process_with_llm,
    prompts_raw,
    results_table,
    run_prompt_button_2,
    selected_rows,
):
    if run_prompt_button_2.value:
        prompt_answers_2 = process_with_llm(fields_to_process=fields_to_process, 
                                           prompt_template=prompts_raw[1][1].value,
                                           inf_model=inf_model, params=params, batch_size=10)
        append_llm_results_to_dataframe(target_dataframe=results_table, fields_to_process=fields_to_process, llm_results=prompt_answers_2, selection_table=selected_rows, column_name=prompts_raw[1][0].value)
    else:
        prompt_answers_2 = []
    return


@app.cell
def _(
    append_llm_results_to_dataframe,
    fields_to_process,
    inf_model,
    params,
    process_with_llm,
    prompts_raw,
    results_table,
    run_prompt_button_3,
    selected_rows,
):
    if run_prompt_button_3.value:
        prompt_answers_3 = process_with_llm(fields_to_process=fields_to_process, 
                                           prompt_template=prompts_raw[2][1].value,
                                           inf_model=inf_model, params=params, batch_size=10)
        append_llm_results_to_dataframe(target_dataframe=results_table, fields_to_process=fields_to_process, llm_results=prompt_answers_3, selection_table=selected_rows, column_name=prompts_raw[2][0].value)
    else:
        prompt_answers_3 = []
    return


@app.cell
def _(
    append_llm_results_to_dataframe,
    fields_to_process,
    inf_model,
    params,
    process_with_llm,
    prompts_raw,
    results_table,
    run_prompt_button_4,
    selected_rows,
):
    if run_prompt_button_4.value:
        prompt_answers_4 = process_with_llm(fields_to_process=fields_to_process, 
                                           prompt_template=prompts_raw[3][1].value,
                                           inf_model=inf_model, params=params, batch_size=10)
        append_llm_results_to_dataframe(target_dataframe=results_table, fields_to_process=fields_to_process, llm_results=prompt_answers_4, selection_table=selected_rows, column_name=prompts_raw[3][0].value)
    else:
        prompt_answers_4 = []
    return


@app.cell
def _(
    append_llm_results_to_dataframe,
    fields_to_process,
    inf_model,
    params,
    process_with_llm,
    prompts_raw,
    results_table,
    run_prompt_button_5,
    selected_rows,
):
    if run_prompt_button_5.value:
        prompt_answers_5 = process_with_llm(fields_to_process=fields_to_process, 
                                           prompt_template=prompts_raw[4][1].value,
                                           inf_model=inf_model, params=params, batch_size=10)
        append_llm_results_to_dataframe(target_dataframe=results_table, fields_to_process=fields_to_process, llm_results=prompt_answers_5, selection_table=selected_rows,column_name=prompts_raw[4][0].value)
    else:
        prompt_answers_5 = []
    return


@app.cell
def _(mo, results_stack):
    ui_accordion_section_7 = mo.accordion(
        {"Section 7: **Run and View Results**": results_stack}
    ) 
    ui_accordion_section_7
    return


@app.cell
def _(show_variable_sidebar):
    show_variable_sidebar.right()
    return


@app.cell
def _(prompt_input_variables_sidebar, show_variable_sidebar):
    show_variable_sidebar.value is not False and prompt_input_variables_sidebar
    return


@app.cell
def _(table_dataframe):
    if not table_dataframe.empty:
        results_table = table_dataframe.copy()
    else:
        results_table = []
    return (results_table,)


@app.cell
def _(
    mo,
    results_table,
    run_prompt_button_1,
    run_prompt_button_2,
    run_prompt_button_3,
    run_prompt_button_4,
    run_prompt_button_5,
):
    if run_prompt_button_1.value or run_prompt_button_2.value or run_prompt_button_3.value or run_prompt_button_4.value or run_prompt_button_5.value:
        results_table_view = mo.ui.table(results_table)
    else:
        results_table_view = mo.ui.table(results_table)
    return (results_table_view,)


@app.cell
def _(mo, prompts_raw):
    prompts =  [mo.vstack([prompt[0], prompt[1]]) for prompt in prompts_raw]
    prompt_stack = mo.vstack(prompts, heights="equal", align="stretch", justify="space-around", gap=3)
    return (prompt_stack,)


@app.cell
def _(
    mo,
    results_table_view,
    run_prompt_button_1,
    run_prompt_button_2,
    run_prompt_button_3,
    run_prompt_button_4,
    run_prompt_button_5,
):
    run_button_stack = mo.hstack([run_prompt_button_1,run_prompt_button_2,run_prompt_button_3,run_prompt_button_4,run_prompt_button_5])
    results_stack = mo.vstack([run_button_stack,results_table_view])
    return (results_stack,)


if __name__ == "__main__":
    app.run()