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import base64 | |
import io | |
import os | |
import pandas as pd | |
from docx import Document | |
from io import BytesIO, StringIO | |
import dash | |
import dash_bootstrap_components as dbc | |
from dash import html, dcc, Input, Output, State, callback_context, MATCH, ALL | |
from dash.dash_table import DataTable | |
from docx.shared import Pt | |
from docx.enum.style import WD_STYLE_TYPE | |
from PyPDF2 import PdfReader | |
import openai | |
import logging | |
import threading | |
import re | |
import markdown | |
from bs4 import BeautifulSoup | |
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s %(message)s') | |
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP], suppress_callback_exceptions=True) | |
openai.api_key = os.environ.get("OPENAI_API_KEY", "") | |
uploaded_files = {} | |
current_document = None | |
document_type = None | |
shredded_document = None | |
pink_review_document = None | |
pink_document = None | |
red_review_document = None | |
red_document = None | |
gold_review_document = None | |
gold_document = None | |
uploaded_doc_contents = {} | |
spreadsheet_types = ["Shred", "Pink Review", "Red Review", "Gold Review", "Virtual Board", "LOE"] | |
narrative_types = ["Pink", "Red", "Gold"] | |
document_types = { | |
"Shred": "Ignore all other instructions and generate only requirements spreadsheet of the Project Work Statement (PWS) identified by action words like shall, will, perform etc. by pws section, requirement. Do not write as if you're responding to the proposal. Its a spreadsheet to distill the requirements, not microhealth's approach", | |
"Pink": "Create a Pink Team document based on the PWS outline. Your goal is to be compliant and compelling. Focus on describing the approach and how it will be done, the steps, workflow, people, processes and technology based on well known industry standards to accomplish the task. Be sure to demonstrate innovation.", | |
"Pink Review": "Ignore all other instructions and generate and evaluate compliance of the Pink Team document against the requirements and output only a spreadsheet of non compliant findings by pws number, the goal of that pws section, what made it non compliant and your recommendations for recovery. you must also take into account section L&M of the document which is the evaluation criteria to be sure we address them.", | |
"Red": "Produce a Red Team document based on the Pink Review by pws sections. Your goal is to be compliant and compelling by recovering all the findings in Pink Review. Focus on describing the approach and how it will be done, the steps, workflow, people, processes and technology to accomplish the task. Be sure to refer to research that validates the approach and cite sources with measurable outcomes", | |
"Red Review": "Ignore all other instructions and generate and evaluate compliance of the Red Team document against the requirements and output a only a spreadsheet of non compliant findings by pws number, the goal of that pws section, what made it non compliant and your recommendations for recovery. you must also take into account section L&M of the document which is the evaluation criteria to be sure we address them", | |
"Gold": "Create a Gold Team document based on the PWS response by pws sections. Your goal is to be compliant and compelling by recovering all the findings in Red Review. Focus on describing the approach and how it will be done, the steps, workflow, people, processes and technology to accomplish the task. Be sure to refer to research that validates the approach and cite sources with measurable outcomes and improve on innovations of the approach", | |
"Gold Review": "Ignore all other instructions and generate and perform a final compliance review against the requirements and output only a spreadsheet of non compliant findings by pws number, the goal of that pws section, what made it non compliant and your recommendations for recovery. you must also take into account section L&M of the document which is the evaluation criteria to be sure we address them", | |
"Virtual Board": "Ignore all other instructions and generate and based on the requirements and in particular the evaulation criteria, you will evaluate the proposal as if you were a contracting office and provide section by section evaluation as unsatisfactory, satisfactory, good, very good, excellent and why and produce only spreadsheet", | |
"LOE": "Ignore all other instructions and generate and generate a Level of Effort (LOE) breakdown and produce only spreadsheet" | |
} | |
# Document dependency rules: mapping doc type to allowed sources for generation and review | |
doc_dependencies = { | |
"Pink": {"source": ["shred"], "require": True}, | |
"Pink Review": {"source": ["pink", "shred"], "require": True}, | |
"Red": {"source": ["pink_review"], "require": True}, | |
"Red Review": {"source": ["red", "shred"], "require": True}, | |
"Gold": {"source": ["red_review"], "require": True}, | |
"Gold Review": {"source": ["gold", "shred"], "require": True}, | |
"LOE": {"source": ["gold"], "require": True}, | |
"Virtual Board": {"source": ["shred"], "require": True}, | |
} | |
def get_right_col_content(selected_type): | |
controls = [] | |
controls.append(html.Div([ | |
html.Div(className="blinking-dot", style={'margin':'0 auto','width':'16px','height':'16px'}), | |
], style={'textAlign':'center', 'marginBottom':'10px'})) | |
controls.append(dcc.Loading( | |
id="loading-indicator", | |
type="dot", | |
children=[html.Div(id="loading-output")] | |
)) | |
# Shred: can always upload | |
if selected_type == "Shred": | |
controls.append( | |
html.Div([ | |
dcc.Upload( | |
id='upload-document', | |
children=html.Div([ | |
'Drag and Drop or ', | |
html.A('Select Files') | |
]), | |
style={ | |
'width': '100%', | |
'height': '60px', | |
'lineHeight': '60px', | |
'borderWidth': '1px', | |
'borderStyle': 'dashed', | |
'borderRadius': '5px', | |
'textAlign': 'center', | |
'margin': '10px 0' | |
}, | |
multiple=True | |
), | |
file_list_component() | |
]) | |
) | |
# For all proposal/response/review types, show only allowed upload controls | |
elif selected_type in doc_dependencies: | |
sources = doc_dependencies[selected_type]["source"] | |
# For each source, show upload and radio if loaded/generated exists | |
for src in sources: | |
label = "" | |
store_var = None | |
if src == "shred": | |
label = "Shred (Requirements)" | |
store_var = shredded_document | |
elif src == "pink": | |
label = "Pink Document" | |
store_var = pink_document | |
elif src == "pink_review": | |
label = "Pink Review" | |
store_var = pink_review_document | |
elif src == "red": | |
label = "Red Document" | |
store_var = red_document | |
elif src == "red_review": | |
label = "Red Review" | |
store_var = red_review_document | |
elif src == "gold": | |
label = "Gold Document" | |
store_var = gold_document | |
# Upload control for this source | |
controls.append(html.Div([ | |
html.Label(f"Upload {label}"), | |
dcc.Upload( | |
id={'type': f'upload-doc-type-{src}', 'index': selected_type}, | |
children=html.Div(['Drag and Drop or ', html.A('Select File')]), | |
style={ | |
'width': '100%', | |
'height': '60px', | |
'lineHeight': '60px', | |
'borderWidth': '1px', | |
'borderStyle': 'dashed', | |
'borderRadius': '5px', | |
'textAlign': 'center', | |
'margin': '10px 0' | |
}, | |
multiple=False | |
), | |
html.Div(id={'type': f'uploaded-doc-name-{src}', 'index': selected_type}), | |
dbc.RadioItems( | |
id={'type': f'radio-doc-source-{src}', 'index': selected_type}, | |
options=[ | |
{'label': 'Loaded Document', 'value': 'loaded'}, | |
{'label': 'Uploaded Document', 'value': 'uploaded'} | |
] if store_var else [{'label': 'Uploaded Document', 'value': 'uploaded'}], | |
value='loaded' if store_var else 'uploaded', | |
inline=True, | |
className="mb-2" | |
), | |
], id={'type': f'doc-type-controls-{src}', 'index': selected_type})) | |
controls.append( | |
dbc.Row([ | |
dbc.Col( | |
dbc.Button("Generate Document", id={'type': 'btn-generate-doc', 'index': selected_type}, color="primary", className="mb-3 w-100"), | |
width=6 | |
), | |
dbc.Col( | |
dbc.Button("Download Document", id="btn-download", color="success", className="mb-3 w-100"), | |
width=6 | |
), | |
dcc.Download(id="download-document") | |
], className="mb-2") | |
) | |
controls.append(html.Hr()) | |
controls.append(html.Div(id='document-preview', className="border p-3 mb-3")) | |
return dbc.Card(dbc.CardBody(controls)) | |
def get_left_col_content(): | |
chat_card = dbc.Card( | |
dbc.CardBody([ | |
html.H5("Maiko Chat", className="mb-2"), | |
dcc.Loading( | |
id="chat-loading", | |
type="dot", | |
children=[ | |
dcc.Textarea( | |
id="chat-input", | |
placeholder="Chat with AI to update document...", | |
className="mb-2", | |
style={ | |
'whiteSpace':'pre-wrap', | |
'width': '100%', | |
'minHeight': '100px', | |
'maxHeight': '300px', | |
'resize': 'vertical', | |
'overflowY': 'auto' | |
}, | |
rows=5, | |
wrap='soft' | |
), | |
dcc.Store(id="chat-input-rows", data=5), | |
dbc.Row([ | |
dbc.Col( | |
dbc.Button("Send", id="btn-send-chat", color="primary", className="mb-3 w-100"), | |
width=6 | |
), | |
dbc.Col( | |
dbc.Button("Clear Chat", id="btn-clear-chat", color="secondary", className="mb-3 w-100"), | |
width=6 | |
), | |
], className="g-1 mb-2"), | |
html.Div(id="chat-output") | |
] | |
) | |
]), | |
className="mt-4" | |
) | |
return [ | |
html.H4("Proposal Writer", className="mt-3 mb-4"), | |
html.Div([ | |
html.Div(className="blinking-dot", style={'margin':'0 auto','width':'16px','height':'16px'}), | |
], style={'textAlign':'center', 'marginBottom':'10px'}), | |
html.Hr(), | |
html.Div( | |
id='doc-type-buttons' | |
), | |
chat_card | |
] | |
def file_list_component(): | |
return html.Div( | |
id='file-list-container', | |
children=[ | |
html.Div(id='file-list') | |
] | |
) | |
app.layout = dbc.Container([ | |
dcc.Store(id='selected-doc-type', data="Shred"), | |
dbc.Row([ | |
dbc.Col( | |
html.H2(id='main-title', className="mt-3 mb-2", style={'textAlign': 'center', 'width':'100%'}), | |
width=12 | |
) | |
]), | |
dbc.Row([ | |
dbc.Col( | |
html.Div([ | |
html.Div(className="blinking-dot", style={'margin':'0 auto','width':'16px','height':'16px'}), | |
], style={'textAlign':'center', 'marginBottom':'10px'}) | |
) | |
]), | |
dbc.Row([ | |
dbc.Col( | |
dbc.Card( | |
dbc.CardBody(get_left_col_content()) | |
), | |
width=3 | |
), | |
dbc.Col( | |
html.Div(id='right-col-content'), | |
width=9 | |
) | |
]) | |
], fluid=True) | |
def update_main_title(selected_type): | |
return selected_type | |
def render_doc_type_buttons(selected_type): | |
buttons = [] | |
for doc_type in document_types.keys(): | |
btn_style = {'overflow': 'hidden', 'text-overflow': 'ellipsis', 'white-space': 'nowrap'} | |
btn_class = "mb-2 w-100 text-left custom-button" | |
if doc_type == selected_type: | |
btn_class += " active-doc-type" | |
buttons.append( | |
dbc.Button( | |
doc_type, | |
id={'type': 'btn-doc-type', 'index': doc_type}, | |
color="link", | |
className=btn_class, | |
style=btn_style | |
) | |
) | |
return buttons | |
def update_selected_doc_type(n_clicks_list, btn_ids): | |
triggered = callback_context.triggered | |
if not triggered or all(x is None for x in n_clicks_list): | |
raise dash.exceptions.PreventUpdate | |
idx = [i for i, x in enumerate(n_clicks_list) if x] | |
if idx: | |
selected_type = btn_ids[idx[-1]]['index'] | |
else: | |
selected_type = "Shred" | |
logging.info(f"Doc type selected: {selected_type}") | |
return selected_type | |
def update_right_col(selected_type): | |
return get_right_col_content(selected_type) | |
def process_document(contents, filename): | |
content_type, content_string = contents.split(',') | |
decoded = base64.b64decode(content_string) | |
try: | |
if filename.lower().endswith('.docx'): | |
doc = Document(BytesIO(decoded)) | |
text = "\n".join([para.text for para in doc.paragraphs]) | |
return text | |
elif filename.lower().endswith('.pdf'): | |
pdf = PdfReader(BytesIO(decoded)) | |
text = "" | |
for page in pdf.pages: | |
page_text = page.extract_text() | |
if page_text: | |
text += page_text | |
return text | |
else: | |
return f"Unsupported file format: {filename}. Please upload a PDF or DOCX file." | |
except Exception as e: | |
logging.error(f"Error processing document: {str(e)}") | |
return f"Error processing document: {str(e)}" | |
def update_output(list_of_contents, list_of_names, existing_files): | |
global uploaded_files, shredded_document | |
if list_of_contents is not None: | |
new_files = [] | |
for i, (content, name) in enumerate(zip(list_of_contents, list_of_names)): | |
file_content = process_document(content, name) | |
uploaded_files[name] = file_content | |
new_files.append( | |
dbc.Row([ | |
dbc.Col( | |
html.Button('×', id={'type': 'remove-file', 'index': name}, style={'marginRight': '5px', 'fontSize': '10px'}), | |
width=1 | |
), | |
dbc.Col( | |
html.Span(name, style={'wordBreak': 'break-all'}), | |
width=11 | |
) | |
], id={'type': 'file-row', 'index': name}, align="center", className="mb-1") | |
) | |
if existing_files is None: | |
existing_files = [] | |
elif not isinstance(existing_files, list): | |
existing_files = [existing_files] | |
shredded_document = None | |
logging.info("Documents uploaded and file list updated.") | |
return existing_files + new_files | |
return existing_files | |
def remove_file(n_clicks, existing_files): | |
global uploaded_files, shredded_document | |
ctx = dash.callback_context | |
if not ctx.triggered: | |
raise dash.exceptions.PreventUpdate | |
triggered_id = ctx.triggered[0]['prop_id'].split('.')[0] | |
if not triggered_id.startswith("{\"type\":\"remove-file\""): | |
raise dash.exceptions.PreventUpdate | |
try: | |
import json | |
triggered_dict = json.loads(triggered_id) | |
removed_file = triggered_dict['index'] | |
except Exception as e: | |
logging.error(f"Could not parse removed file from callback context: {e}") | |
raise dash.exceptions.PreventUpdate | |
uploaded_files.pop(removed_file, None) | |
shredded_document = None | |
logging.info(f"Removed file: {removed_file}") | |
filtered_files = [] | |
if existing_files: | |
for file in existing_files: | |
try: | |
file_id = file['props']['id'] | |
if file_id['index'] != removed_file: | |
filtered_files.append(file) | |
except Exception as e: | |
filtered_files.append(file) | |
return filtered_files | |
# Upload callbacks for all doc dependencies (Pink, Pink Review, Red, Red Review, Gold, Gold Review, LOE, Virtual Board) | |
def make_upload_callback(src): | |
def update_uploaded_doc_name(contents, filename, id_dict): | |
global uploaded_doc_contents | |
if contents is not None: | |
uploaded_doc_contents[(src, id_dict['index'])] = (contents, filename) | |
logging.info(f"{id_dict['index']} {src} file uploaded: {filename}") | |
return filename, contents, "uploaded" | |
return "", None, "loaded" | |
for src in ["shred", "pink", "pink_review", "red", "red_review", "gold"]: | |
make_upload_callback(src) | |
def extract_markdown_tables(md_text): | |
tables = [] | |
lines = md_text.split('\n') | |
in_table = False | |
table_lines = [] | |
for line in lines: | |
if re.match(r'^\s*\|.*\|\s*$', line): | |
in_table = True | |
table_lines.append(line) | |
elif in_table and (re.match(r'^\s*\|.*\|\s*$', line) or re.match(r'^\s*$', line)): | |
table_lines.append(line) | |
else: | |
if in_table and table_lines: | |
tables.append('\n'.join(table_lines)) | |
table_lines = [] | |
in_table = False | |
if in_table and table_lines: | |
tables.append('\n'.join(table_lines)) | |
return tables | |
def markdown_table_to_df(md_table): | |
lines = [line.strip() for line in md_table.split('\n') if line.strip()] | |
if len(lines) < 2: | |
return None | |
header = [h.strip() for h in lines[0].strip('|').split('|')] | |
sep_idx = 1 | |
while sep_idx < len(lines) and not re.match(r'^\|\s*:?-+:?\s*(\|\s*:?-+:?\s*)+\|?$', lines[sep_idx]): | |
sep_idx += 1 | |
data_lines = lines[sep_idx+1:] if sep_idx+1 < len(lines) else [] | |
rows = [] | |
for row in data_lines: | |
if not row.strip() or not row.strip().startswith('|'): | |
continue | |
cells = [c.strip() for c in row.strip('|').split('|')] | |
if len(cells) < len(header): | |
cells += [''] * (len(header) - len(cells)) | |
elif len(cells) > len(header): | |
cells = cells[:len(header)] | |
rows.append(cells) | |
df = pd.DataFrame(rows, columns=header) | |
return df | |
def markdown_table_preview(md_text): | |
tables = extract_markdown_tables(md_text) | |
if not tables: | |
return html.Div("No table found.") | |
table_divs = [] | |
for i, table in enumerate(tables): | |
df = markdown_table_to_df(table) | |
if df is not None and not df.empty: | |
table_divs.append( | |
html.Div([ | |
DataTable( | |
columns=[{"name": str(col), "id": str(col)} for col in df.columns], | |
data=df.to_dict('records'), | |
style_table={'overflowX': 'auto'}, | |
style_cell={'whiteSpace': 'normal', 'height': 'auto', 'textAlign': 'left', 'fontFamily': 'monospace', 'fontSize': '14px', 'maxWidth': '400px', 'minWidth': '80px', 'wordBreak': 'break-word'}, | |
style_header={'fontWeight': 'bold'}, | |
page_size=100, | |
id={'type': 'datatable-preview', 'index': i} | |
) | |
], className="mb-4") | |
) | |
return html.Div(table_divs) | |
def markdown_narrative_preview(md_text): | |
return html.Div(dcc.Markdown(md_text, dangerously_allow_html=True, style={'whiteSpace': 'pre-wrap', 'fontFamily': 'sans-serif'})) | |
def markdown_tables_to_xlsx(md_text): | |
tables = extract_markdown_tables(md_text) | |
output = BytesIO() | |
with pd.ExcelWriter(output, engine='xlsxwriter') as writer: | |
for i, table in enumerate(tables): | |
df = markdown_table_to_df(table) | |
if df is not None: | |
sheet_name = f"Table{i+1}" | |
df.to_excel(writer, sheet_name=sheet_name, index=False) | |
output.seek(0) | |
return output | |
def strip_markdown(text): | |
text = re.sub(r'(\*\*|__)(.*?)\1', r'\2', text) | |
text = re.sub(r'(\*|_)(.*?)\1', r'\2', text) | |
text = re.sub(r'`{1,3}[^`]*`{1,3}', '', text) | |
text = re.sub(r'^#+ ', '', text, flags=re.MULTILINE) | |
text = re.sub(r'^> ', '', text, flags=re.MULTILINE) | |
text = re.sub(r'!\[.*?\]\(.*?\)', '', text) | |
text = re.sub(r'\[([^\]]+)\]\([^)]+\)', r'\1', text) | |
text = re.sub(r'^\s*[-*+] ', '', text, flags=re.MULTILINE) | |
text = re.sub(r'^\s*\d+\.\s+', '', text, flags=re.MULTILINE) | |
text = text.replace('---', '') | |
text = text.replace('___', '') | |
text = text.replace('***', '') | |
return text.strip() | |
def generate_document(document_type, file_contents, extra_context=None): | |
if document_type in spreadsheet_types: | |
prompt = f"""Ignore all other instructions and output only a spreadsheet for {document_type} as described below. Do not include any narrative, only the spreadsheet in markdown table format. | |
Instructions: {document_types[document_type]} | |
Project Artifacts: | |
{' '.join(file_contents)} | |
Output only the spreadsheet as a markdown table, no narrative or explanation.""" | |
elif document_type in narrative_types: | |
prompt = f"""Generate a {document_type} document based on the following project artifacts: | |
{' '.join(file_contents)} | |
Instructions: | |
1. Create the {document_type} as a detailed document. | |
2. Use proper formatting and structure. | |
3. Include all necessary sections and details. | |
4. Start the output immediately with the document content. | |
Now, generate the {document_type}: | |
""" | |
else: | |
prompt = f"""Generate a {document_type} based on the following project artifacts: | |
{' '.join(file_contents)} | |
Instructions: | |
{document_types.get(document_type, '')} | |
Now, generate the {document_type}: | |
""" | |
if extra_context: | |
prompt += f"\n\n{extra_context}" | |
logging.info(f"Generating document for type: {document_type}") | |
try: | |
response = openai.ChatCompletion.create( | |
model="gpt-4-1106-preview", | |
messages=[ | |
{"role": "system", "content": "You are a helpful, expert government proposal writer."}, | |
{"role": "user", "content": prompt} | |
], | |
max_tokens=4096, | |
temperature=0.25, | |
) | |
generated_text = response['choices'][0]['message']['content'] | |
logging.info("Document generated successfully.") | |
return generated_text | |
except Exception as e: | |
logging.error(f"Error generating document: {str(e)}") | |
raise | |
def generate_any_doc( | |
n_clicks_list, btn_ids, | |
radio_shred, upload_shred_contents, upload_shred_filenames, | |
radio_pink, upload_pink_contents, upload_pink_filenames, | |
radio_pink_review, upload_pink_review_contents, upload_pink_review_filenames, | |
radio_red, upload_red_contents, upload_red_filenames, | |
radio_red_review, upload_red_review_contents, upload_red_review_filenames, | |
radio_gold, upload_gold_contents, upload_gold_filenames | |
): | |
global current_document, document_type, shredded_document, pink_review_document, pink_document, red_review_document, red_document, gold_review_document, gold_document | |
ctx = callback_context | |
logging.info(f"generate_any_doc triggered: n_clicks_list={n_clicks_list}, btn_ids={btn_ids}") | |
if not ctx.triggered: | |
raise dash.exceptions.PreventUpdate | |
idx = [i for i, x in enumerate(n_clicks_list) if x] | |
if not idx: | |
raise dash.exceptions.PreventUpdate | |
idx = idx[-1] | |
doc_type = btn_ids[idx]['index'] | |
document_type = doc_type | |
# SHRED - always allowed | |
if doc_type == "Shred": | |
if not uploaded_files: | |
logging.info("No uploaded files for Shred. Aborting.") | |
return html.Div("Please upload a document before shredding."), "" | |
file_contents = list(uploaded_files.values()) | |
try: | |
generated = generate_document(doc_type, file_contents) | |
current_document = generated | |
shredded_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("Shred document generated.") | |
return preview, "Shred generated" | |
except Exception as e: | |
logging.error(f"Error generating document: {str(e)}") | |
return html.Div(f"Error generating document: {str(e)}"), "Error" | |
# Dependency rules | |
def get_doc_from_radio(radio, upload_contents, upload_filenames, loaded_var): | |
if radio and radio[0] == 'uploaded': | |
if upload_contents and upload_contents[0] and upload_filenames and upload_filenames[0]: | |
return process_document(upload_contents[0], upload_filenames[0]) | |
else: | |
return None | |
else: | |
return loaded_var | |
# Pink: can only use Shred (requirements), loaded or uploaded | |
if doc_type == "Pink": | |
shred_doc = get_doc_from_radio(radio_shred, upload_shred_contents, upload_shred_filenames, shredded_document) | |
if not shred_doc: | |
return html.Div("Please provide a Shred requirements document (either loaded or uploaded) to generate Pink."), "" | |
try: | |
generated = generate_document(doc_type, [shred_doc]) | |
current_document = generated | |
pink_document = generated | |
preview = markdown_narrative_preview(generated) | |
logging.info("Pink document generated.") | |
return preview, "Pink generated" | |
except Exception as e: | |
logging.error(f"Error generating Pink: {str(e)}") | |
return html.Div(f"Error generating Pink: {str(e)}"), "Error" | |
# Pink Review: must compare Pink (uploaded or generated) with Shred (uploaded or generated) | |
if doc_type == "Pink Review": | |
pink_doc = get_doc_from_radio(radio_pink, upload_pink_contents, upload_pink_filenames, pink_document) | |
shred_doc = get_doc_from_radio(radio_shred, upload_shred_contents, upload_shred_filenames, shredded_document) | |
if not pink_doc or not shred_doc: | |
return html.Div("Please provide both Pink and Shred documents (either loaded or uploaded) to generate Pink Review."), "" | |
try: | |
generated = generate_document(doc_type, [pink_doc, shred_doc]) | |
current_document = generated | |
pink_review_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("Pink Review document generated.") | |
return preview, "Pink Review generated" | |
except Exception as e: | |
logging.error(f"Error generating Pink Review: {str(e)}") | |
return html.Div(f"Error generating Pink Review: {str(e)}"), "Error" | |
# Red: can only use Pink Review (uploaded or generated) | |
if doc_type == "Red": | |
pink_review_doc = get_doc_from_radio(radio_pink_review, upload_pink_review_contents, upload_pink_review_filenames, pink_review_document) | |
if not pink_review_doc: | |
return html.Div("Please provide a Pink Review document (either loaded or uploaded) to generate Red."), "" | |
try: | |
generated = generate_document(doc_type, [pink_review_doc]) | |
current_document = generated | |
red_document = generated | |
preview = markdown_narrative_preview(generated) | |
logging.info("Red document generated.") | |
return preview, "Red generated" | |
except Exception as e: | |
logging.error(f"Error generating Red: {str(e)}") | |
return html.Div(f"Error generating Red: {str(e)}"), "Error" | |
# Red Review: must compare Red (uploaded or generated) with Shred (uploaded or generated) | |
if doc_type == "Red Review": | |
red_doc = get_doc_from_radio(radio_red, upload_red_contents, upload_red_filenames, red_document) | |
shred_doc = get_doc_from_radio(radio_shred, upload_shred_contents, upload_shred_filenames, shredded_document) | |
if not red_doc or not shred_doc: | |
return html.Div("Please provide both Red and Shred documents (either loaded or uploaded) to generate Red Review."), "" | |
try: | |
generated = generate_document(doc_type, [red_doc, shred_doc]) | |
current_document = generated | |
red_review_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("Red Review document generated.") | |
return preview, "Red Review generated" | |
except Exception as e: | |
logging.error(f"Error generating Red Review: {str(e)}") | |
return html.Div(f"Error generating Red Review: {str(e)}"), "Error" | |
# Gold: can only use Red Review (uploaded or generated) | |
if doc_type == "Gold": | |
red_review_doc = get_doc_from_radio(radio_red_review, upload_red_review_contents, upload_red_review_filenames, red_review_document) | |
if not red_review_doc: | |
return html.Div("Please provide a Red Review document (either loaded or uploaded) to generate Gold."), "" | |
try: | |
generated = generate_document(doc_type, [red_review_doc]) | |
current_document = generated | |
gold_document = generated | |
preview = markdown_narrative_preview(generated) | |
logging.info("Gold document generated.") | |
return preview, "Gold generated" | |
except Exception as e: | |
logging.error(f"Error generating Gold: {str(e)}") | |
return html.Div(f"Error generating Gold: {str(e)}"), "Error" | |
# Gold Review: must compare Gold (uploaded or generated) with Shred (uploaded or generated) | |
if doc_type == "Gold Review": | |
gold_doc = get_doc_from_radio(radio_gold, upload_gold_contents, upload_gold_filenames, gold_document) | |
shred_doc = get_doc_from_radio(radio_shred, upload_shred_contents, upload_shred_filenames, shredded_document) | |
if not gold_doc or not shred_doc: | |
return html.Div("Please provide both Gold and Shred documents (either loaded or uploaded) to generate Gold Review."), "" | |
try: | |
generated = generate_document(doc_type, [gold_doc, shred_doc]) | |
current_document = generated | |
gold_review_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("Gold Review document generated.") | |
return preview, "Gold Review generated" | |
except Exception as e: | |
logging.error(f"Error generating Gold Review: {str(e)}") | |
return html.Div(f"Error generating Gold Review: {str(e)}"), "Error" | |
# LOE: can only use Gold (uploaded or generated) | |
if doc_type == "LOE": | |
gold_doc = get_doc_from_radio(radio_gold, upload_gold_contents, upload_gold_filenames, gold_document) | |
if not gold_doc: | |
return html.Div("Please provide a Gold document (either loaded or uploaded) to generate LOE."), "" | |
try: | |
generated = generate_document(doc_type, [gold_doc]) | |
current_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("LOE document generated.") | |
return preview, "LOE generated" | |
except Exception as e: | |
logging.error(f"Error generating LOE: {str(e)}") | |
return html.Div(f"Error generating LOE: {str(e)}"), "Error" | |
# Virtual Board: can only use Shred (L&M evaluation criteria) | |
if doc_type == "Virtual Board": | |
shred_doc = get_doc_from_radio(radio_shred, upload_shred_contents, upload_shred_filenames, shredded_document) | |
if not shred_doc: | |
return html.Div("Please provide a Shred requirements document (either loaded or uploaded) to generate Virtual Board."), "" | |
try: | |
# Extract section L&M if possible | |
lm_text = "" | |
lm_match = re.search(r'(Section\s+L[\s\S]+?)(Section\s+M|$)', shred_doc, re.IGNORECASE) | |
if lm_match: | |
lm_text = lm_match.group(1) | |
else: | |
lm_text = shred_doc | |
generated = generate_document(doc_type, [lm_text]) | |
current_document = generated | |
preview = markdown_table_preview(generated) | |
logging.info("Virtual Board document generated.") | |
return preview, "Virtual Board generated" | |
except Exception as e: | |
logging.error(f"Error generating Virtual Board: {str(e)}") | |
return html.Div(f"Error generating Virtual Board: {str(e)}"), "Error" | |
return html.Div("Unsupported document type or missing required sources."), "" | |
def update_document_via_chat(btn_send, btn_clear, chat_input, selected_doc_type): | |
global current_document, document_type | |
ctx = callback_context | |
if not ctx.triggered: | |
raise dash.exceptions.PreventUpdate | |
trigger_id = ctx.triggered[0]['prop_id'].split('.')[0] | |
if trigger_id == 'btn-clear-chat': | |
return "", dash.no_update | |
if not chat_input or current_document is None: | |
raise dash.exceptions.PreventUpdate | |
if selected_doc_type in spreadsheet_types: | |
prompt = f"""Update the following {selected_doc_type} spreadsheet based on this instruction: {chat_input} | |
Current spreadsheet (markdown table format): | |
{current_document} | |
Instructions: | |
1. Provide the updated spreadsheet as a markdown table only. | |
2. Do not include any narrative, only the markdown table. | |
Now, provide the updated {selected_doc_type} spreadsheet: | |
""" | |
else: | |
prompt = f"""Update the following {selected_doc_type} document based on this instruction: {chat_input} | |
Current document: | |
{current_document} | |
Instructions: | |
1. Provide the updated document content. | |
2. Maintain proper formatting and structure. | |
3. Incorporate the requested changes seamlessly. | |
Now, provide the updated {selected_doc_type}: | |
""" | |
logging.info(f"Updating document via chat for {selected_doc_type} instruction: {chat_input}") | |
try: | |
response = openai.ChatCompletion.create( | |
model="gpt-4-1106-preview", | |
messages=[ | |
{"role": "system", "content": "You are a helpful, expert government proposal writer."}, | |
{"role": "user", "content": prompt} | |
], | |
max_tokens=4096, | |
temperature=0.2, | |
) | |
current_document = response['choices'][0]['message']['content'] | |
logging.info("Document updated via chat successfully.") | |
if selected_doc_type in spreadsheet_types: | |
preview = markdown_table_preview(current_document) | |
else: | |
preview = markdown_narrative_preview(current_document) | |
return f"Document updated based on: {chat_input}", preview | |
except Exception as e: | |
logging.error(f"Error updating document via chat: {str(e)}") | |
return f"Error updating document: {str(e)}", html.Div(f"Error updating document: {str(e)}") | |
def download_document(n_clicks, selected_doc_type): | |
global current_document | |
if current_document is None: | |
raise dash.exceptions.PreventUpdate | |
if selected_doc_type in spreadsheet_types: | |
try: | |
xlsx_bytes = markdown_tables_to_xlsx(current_document) | |
logging.info(f"{selected_doc_type} document downloaded as Excel.") | |
return dcc.send_bytes(xlsx_bytes.read(), f"{selected_doc_type}.xlsx") | |
except Exception as e: | |
logging.error(f"Error downloading {selected_doc_type} document: {str(e)}") | |
return dcc.send_string(f"Error downloading {selected_doc_type}: {str(e)}", f"{selected_doc_type}_error.txt") | |
else: | |
try: | |
plain = strip_markdown(current_document) | |
doc = Document() | |
for para in plain.split('\n'): | |
doc.add_paragraph(para) | |
output = BytesIO() | |
doc.save(output) | |
logging.info(f"{selected_doc_type} document downloaded as Word.") | |
output.seek(0) | |
return dcc.send_bytes(output.read(), f"{selected_doc_type}.docx") | |
except Exception as e: | |
logging.error(f"Error downloading document: {str(e)}") | |
return dcc.send_string(f"Error downloading document: {str(e)}", f"{selected_doc_type}_error.txt") | |
def auto_expand_textarea(value, current_rows): | |
if value is None or value == "": | |
return 5 | |
num_lines = value.count('\n') + 1 | |
max_rows = 20 | |
rows = min(max(num_lines, 5), max_rows) | |
return rows | |
if __name__ == '__main__': | |
print("Starting the Dash application...") | |
app.run(debug=True, host='0.0.0.0', port=7860, threaded=True) | |
print("Dash application has finished running.") |