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Update app.py via AI Editor
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app.py
CHANGED
@@ -27,6 +27,9 @@ shredded_document = None
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pink_review_document = None
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uploaded_doc_contents = {}
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document_types = {
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"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",
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"Pink": "Create a Pink Team document based on the PWS outline. Your goal is to be compliant and compelling.",
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@@ -40,88 +43,60 @@ document_types = {
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}
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def get_right_col_content(selected_type):
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'margin': '10px 0'
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},
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multiple=False
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),
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html.Div(id={'type': 'uploaded-doc-name', 'index': selected_type}),
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dbc.RadioItems(
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id={'type': 'radio-doc-source', 'index': selected_type},
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options=[
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{'label': 'Loaded Document', 'value': 'loaded'},
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{'label': 'Uploaded Document', 'value': 'uploaded'}
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],
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value='loaded',
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inline=True,
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className="mb-2"
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),
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dbc.Button("Generate Document", id={'type': 'btn-generate-doc', 'index': selected_type}, color="primary", className="mb-3"),
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], id={'type': 'doc-type-controls', 'index': selected_type}),
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dcc.Loading(
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id="chat-loading",
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type="dot",
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children=[
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dbc.Input(id="chat-input", type="text", placeholder="Chat with AI to update document...", className="mb-2", style={'whiteSpace':'pre-wrap'}),
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dbc.Button("Send", id="btn-send-chat", color="primary", className="mb-3"),
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html.Div(id="chat-output")
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]
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)
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])
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)
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app.layout = dbc.Container([
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dcc.Store(id='selected-doc-type', data="Shred"),
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@@ -279,40 +254,6 @@ def remove_file(n_clicks, existing_files):
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@app.callback(
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Output('document-preview', 'children'),
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Output('loading-output', 'children'),
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Input({'type': 'btn-doc-type', 'index': 'Shred'}, 'n_clicks'),
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prevent_initial_call=True
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)
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def generate_shred_doc(n_clicks):
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global current_document, document_type, shredded_document
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if not uploaded_files:
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return html.Div("Please upload a document before shredding."), ""
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file_contents = list(uploaded_files.values())
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try:
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shredded_document = generate_document("Shred", file_contents)
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current_document = shredded_document
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return dcc.Markdown(shredded_document), "Shred generated"
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except Exception as e:
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logging.error(f"Error generating document: {str(e)}")
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return html.Div(f"Error generating document: {str(e)}"), "Error"
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@app.callback(
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Output({'type': 'uploaded-doc-name', 'index': MATCH}, 'children'),
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Output({'type': 'upload-doc-type', 'index': MATCH}, 'contents'),
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Output({'type': 'radio-doc-source', 'index': MATCH}, 'value'),
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Input({'type': 'upload-doc-type', 'index': MATCH}, 'contents'),
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State({'type': 'upload-doc-type', 'index': MATCH}, 'filename'),
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State({'type': 'upload-doc-type', 'index': MATCH}, 'id')
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)
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def update_uploaded_doc_name(contents, filename, id_dict):
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if contents is not None:
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uploaded_doc_contents[id_dict['index']] = (contents, filename)
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logging.info(f"{id_dict['index']} file uploaded: {filename}")
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return filename, contents, "uploaded"
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return "", None, "loaded"
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@app.callback(
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Output('document-preview', 'children', allow_duplicate=True),
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Output('loading-output', 'children', allow_duplicate=True),
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Input({'type': 'btn-generate-doc', 'index': ALL}, 'n_clicks'),
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State({'type': 'btn-generate-doc', 'index': ALL}, 'id'),
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State({'type': 'radio-doc-source', 'index': ALL}, 'value'),
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@@ -320,7 +261,7 @@ def update_uploaded_doc_name(contents, filename, id_dict):
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State({'type': 'upload-doc-type', 'index': ALL}, 'filename'),
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prevent_initial_call=True
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)
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def
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global current_document, document_type, shredded_document, pink_review_document
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ctx = callback_context
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if not ctx.triggered:
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@@ -332,15 +273,29 @@ def generate_other_doc(n_clicks_list, btn_ids, radio_values, upload_contents, up
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doc_type = btn_ids[idx]['index']
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document_type = doc_type
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if doc_type == "Shred":
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-
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if shredded_document is None:
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return html.Div("Please shred a document first."), ""
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source = radio_values[idx] if radio_values and len(radio_values) > idx else 'loaded'
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doc_content = None
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if source == 'uploaded':
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if upload_contents and len(upload_contents) > idx and upload_contents[idx] and upload_filenames and len(upload_filenames) > idx and upload_filenames[idx]:
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doc_content = process_document(upload_contents[idx], upload_filenames[idx])
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try:
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if doc_type == "Pink Review":
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pink_review_document =
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else:
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except Exception as e:
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logging.error(f"Error generating document: {str(e)}")
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return html.Div(f"Error generating document: {str(e)}"), "Error"
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def generate_document(document_type, file_contents):
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{' '.join(file_contents)}
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Instructions:
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1. Create the {document_type} as a detailed document.
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2. Use proper formatting and structure.
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3. Include all necessary sections and details.
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4. Start the output immediately with the document content.
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5. IMPORTANT: If the document type is Pink, Red, Gold and not
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outcomes, the industry standard that
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methodology is based on if applicable,
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detail the workflow or steps to accomplish
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the requirement with labor categories that
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will do those tasks in that workflow,
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reference reputable research like gartner,
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forrester, IDC, Deloitte, Accenture etc
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with measures of success and substantiation
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of MicroHealth's approach. Never use soft words
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like maybe, could be, should, possible be definitive in your language and confident.
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6. you must also take into account section L&M of the document which is the evaluation criteria
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to be sure we address them.
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Now, generate the {document_type}:
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"""
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logging.info(f"Generating document for type: {document_type}")
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try:
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response = openai.ChatCompletion.create(
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Output('document-preview', 'children', allow_duplicate=True),
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Input('btn-send-chat', 'n_clicks'),
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State('chat-input', 'value'),
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prevent_initial_call=True
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)
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def update_document_via_chat(n_clicks, chat_input):
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global current_document, document_type
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if not chat_input or current_document is None:
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raise dash.exceptions.PreventUpdate
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Current document:
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{current_document}
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Instructions:
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1. Provide the updated document content.
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2. Maintain proper formatting and structure.
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3. Incorporate the requested changes seamlessly.
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Now, provide the updated {
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"""
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logging.info(f"Updating document via chat for {document_type} instruction: {chat_input}")
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try:
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response = openai.ChatCompletion.create(
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model="gpt-4-1106-preview",
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)
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current_document = response['choices'][0]['message']['content']
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logging.info("Document updated via chat successfully.")
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except Exception as e:
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logging.error(f"Error updating document via chat: {str(e)}")
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return f"Error updating document: {str(e)}", html.Div(f"Error updating document: {str(e)}")
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@app.callback(
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Output("download-document", "data"),
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Input("btn-download", "n_clicks"),
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prevent_initial_call=True
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)
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def download_document(n_clicks):
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global current_document
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if current_document is None:
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raise dash.exceptions.PreventUpdate
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if
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try:
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df = pd.read_csv(StringIO(current_document))
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output = BytesIO()
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with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
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df.to_excel(writer, sheet_name=
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logging.info("
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except Exception as e:
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logging.error(f"Error downloading
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return dcc.send_string(f"Error downloading
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else:
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try:
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doc = Document()
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doc.add_paragraph(current_document)
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output = BytesIO()
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doc.save(output)
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logging.info("
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except Exception as e:
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logging.error(f"Error downloading document: {str(e)}")
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return dcc.send_string(f"Error downloading document: {str(e)}", f"{
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if __name__ == '__main__':
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print("Starting the Dash application...")
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pink_review_document = None
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uploaded_doc_contents = {}
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spreadsheet_types = ["Shred", "Pink Review", "Red Review", "Gold Review", "Virtual Board", "LOE"]
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narrative_types = ["Pink", "Red", "Gold"]
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document_types = {
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"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",
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"Pink": "Create a Pink Team document based on the PWS outline. Your goal is to be compliant and compelling.",
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}
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def get_right_col_content(selected_type):
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controls = []
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controls.append(html.Div([
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html.Div(className="blinking-dot", style={'margin':'0 auto','width':'16px','height':'16px'}),
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], style={'textAlign':'center', 'marginBottom':'10px'}))
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controls.append(dcc.Loading(
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id="loading-indicator",
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type="dot",
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children=[html.Div(id="loading-output")]
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))
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controls.append(html.Div(id='document-preview', className="border p-3 mb-3"))
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controls.append(dbc.Button("Download Document", id="btn-download", color="success", className="mt-3"))
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controls.append(dcc.Download(id="download-document"))
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controls.append(html.Hr())
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if selected_type != "Shred":
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controls.append(html.Div([
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html.Label(f"Upload {selected_type} Document"),
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dcc.Upload(
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id={'type': 'upload-doc-type', 'index': selected_type},
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children=html.Div(['Drag and Drop or ', html.A('Select File')]),
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style={
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'width': '100%',
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'height': '60px',
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'lineHeight': '60px',
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'borderWidth': '1px',
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'borderStyle': 'dashed',
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'borderRadius': '5px',
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'textAlign': 'center',
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'margin': '10px 0'
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},
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multiple=False
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),
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html.Div(id={'type': 'uploaded-doc-name', 'index': selected_type}),
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dbc.RadioItems(
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id={'type': 'radio-doc-source', 'index': selected_type},
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options=[
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{'label': 'Loaded Document', 'value': 'loaded'},
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{'label': 'Uploaded Document', 'value': 'uploaded'}
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],
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value='loaded',
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inline=True,
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className="mb-2"
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),
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dbc.Button("Generate Document", id={'type': 'btn-generate-doc', 'index': selected_type}, color="primary", className="mb-3"),
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], id={'type': 'doc-type-controls', 'index': selected_type}))
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controls.append(dcc.Loading(
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id="chat-loading",
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type="dot",
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children=[
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dbc.Input(id="chat-input", type="text", placeholder="Chat with AI to update document...", className="mb-2", style={'whiteSpace':'pre-wrap'}),
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dbc.Button("Send", id="btn-send-chat", color="primary", className="mb-3"),
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html.Div(id="chat-output")
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]
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))
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return dbc.Card(dbc.CardBody(controls))
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app.layout = dbc.Container([
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dcc.Store(id='selected-doc-type', data="Shred"),
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@app.callback(
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Output('document-preview', 'children'),
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Output('loading-output', 'children'),
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Input({'type': 'btn-generate-doc', 'index': ALL}, 'n_clicks'),
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State({'type': 'btn-generate-doc', 'index': ALL}, 'id'),
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State({'type': 'radio-doc-source', 'index': ALL}, 'value'),
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State({'type': 'upload-doc-type', 'index': ALL}, 'filename'),
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prevent_initial_call=True
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)
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def generate_any_doc(n_clicks_list, btn_ids, radio_values, upload_contents, upload_filenames):
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global current_document, document_type, shredded_document, pink_review_document
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ctx = callback_context
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if not ctx.triggered:
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doc_type = btn_ids[idx]['index']
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document_type = doc_type
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if not uploaded_files and doc_type == "Shred":
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return html.Div("Please upload a document before shredding."), ""
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# Source selection
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source = radio_values[idx] if radio_values and len(radio_values) > idx else 'loaded'
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doc_content = None
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if doc_type == "Shred":
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file_contents = list(uploaded_files.values())
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try:
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generated = generate_document(doc_type, file_contents)
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current_document = generated
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shredded_document = generated
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preview = spreadsheet_preview(generated)
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return preview, "Shred generated"
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except Exception as e:
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logging.error(f"Error generating document: {str(e)}")
|
293 |
+
return html.Div(f"Error generating document: {str(e)}"), "Error"
|
294 |
|
295 |
+
# For all other types
|
296 |
if shredded_document is None:
|
297 |
return html.Div("Please shred a document first."), ""
|
298 |
|
|
|
|
|
|
|
299 |
if source == 'uploaded':
|
300 |
if upload_contents and len(upload_contents) > idx and upload_contents[idx] and upload_filenames and len(upload_filenames) > idx and upload_filenames[idx]:
|
301 |
doc_content = process_document(upload_contents[idx], upload_filenames[idx])
|
|
|
323 |
|
324 |
try:
|
325 |
if doc_type == "Pink Review":
|
326 |
+
generated = generate_document(doc_type, [doc_content, shredded_document])
|
327 |
+
pink_review_document = generated
|
328 |
+
current_document = generated
|
329 |
+
preview = spreadsheet_preview(generated)
|
330 |
+
return preview, f"{doc_type} generated"
|
331 |
+
elif doc_type in ["Red Review", "Gold Review", "Virtual Board", "LOE"]:
|
332 |
+
generated = generate_document(doc_type, [doc_content, shredded_document])
|
333 |
+
current_document = generated
|
334 |
+
preview = spreadsheet_preview(generated)
|
335 |
+
return preview, f"{doc_type} generated"
|
336 |
+
elif doc_type in ["Pink", "Red", "Gold"]:
|
337 |
+
generated = generate_document(doc_type, [doc_content])
|
338 |
+
current_document = generated
|
339 |
+
preview = dcc.Markdown(generated)
|
340 |
+
return preview, f"{doc_type} generated"
|
341 |
else:
|
342 |
+
generated = generate_document(doc_type, [doc_content])
|
343 |
+
current_document = generated
|
344 |
+
preview = dcc.Markdown(generated)
|
345 |
+
return preview, f"{doc_type} generated"
|
346 |
except Exception as e:
|
347 |
logging.error(f"Error generating document: {str(e)}")
|
348 |
return html.Div(f"Error generating document: {str(e)}"), "Error"
|
349 |
|
350 |
+
@app.callback(
|
351 |
+
Output({'type': 'uploaded-doc-name', 'index': MATCH}, 'children'),
|
352 |
+
Output({'type': 'upload-doc-type', 'index': MATCH}, 'contents'),
|
353 |
+
Output({'type': 'radio-doc-source', 'index': MATCH}, 'value'),
|
354 |
+
Input({'type': 'upload-doc-type', 'index': MATCH}, 'contents'),
|
355 |
+
State({'type': 'upload-doc-type', 'index': MATCH}, 'filename'),
|
356 |
+
State({'type': 'upload-doc-type', 'index': MATCH}, 'id')
|
357 |
+
)
|
358 |
+
def update_uploaded_doc_name(contents, filename, id_dict):
|
359 |
+
if contents is not None:
|
360 |
+
uploaded_doc_contents[id_dict['index']] = (contents, filename)
|
361 |
+
logging.info(f"{id_dict['index']} file uploaded: {filename}")
|
362 |
+
return filename, contents, "uploaded"
|
363 |
+
return "", None, "loaded"
|
364 |
+
|
365 |
+
def spreadsheet_preview(text):
|
366 |
+
try:
|
367 |
+
# Try to parse as CSV, fallback to plain text
|
368 |
+
df = pd.read_csv(StringIO(text))
|
369 |
+
return dbc.Table.from_dataframe(df, striped=True, bordered=True, hover=True, size="sm")
|
370 |
+
except Exception:
|
371 |
+
return html.Pre(text, style={'whiteSpace': 'pre-wrap', 'fontFamily': 'monospace'})
|
372 |
+
|
373 |
def generate_document(document_type, file_contents):
|
374 |
+
if document_type in spreadsheet_types:
|
375 |
+
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 CSV format.
|
376 |
+
Instructions: {document_types[document_type]}
|
377 |
+
Project Artifacts:
|
378 |
+
{' '.join(file_contents)}
|
379 |
+
Output only the spreadsheet in CSV format, no narrative or explanation."""
|
380 |
+
elif document_type in narrative_types:
|
381 |
+
prompt = f"""Generate a {document_type} document based on the following project artifacts:
|
382 |
{' '.join(file_contents)}
|
383 |
Instructions:
|
384 |
1. Create the {document_type} as a detailed document.
|
385 |
2. Use proper formatting and structure.
|
386 |
3. Include all necessary sections and details.
|
387 |
4. Start the output immediately with the document content.
|
388 |
+
5. IMPORTANT: If the document type is Pink, Red, Gold and not Pink Review, Red Review, Gold Review, or spreadsheet, loe or virtual board then your goal is to be compliant and compelling based on the requrements, write in paragraph in active voice as MicroHealth, limit bullets, answer the requirement with what MicroHealth will do to satisfy the requirement, the technical approach with innovation for efficiency, productivity, quality and measurable outcomes, the industry standard that methodology is based on if applicable, detail the workflow or steps to accomplish the requirement with labor categories that will do those tasks in that workflow, reference reputable research like gartner, forrester, IDC, Deloitte, Accenture etc with measures of success and substantiation of MicroHealth's approach. Never use soft words like maybe, could be, should, possible be definitive in your language and confident.
|
389 |
+
6. you must also take into account section L&M of the document which is the evaluation criteria to be sure we address them.
|
390 |
+
Now, generate the {document_type}:
|
391 |
+
"""
|
392 |
+
else:
|
393 |
+
prompt = f"""Generate a {document_type} based on the following project artifacts:
|
394 |
+
{' '.join(file_contents)}
|
395 |
+
Instructions:
|
396 |
+
{document_types.get(document_type, '')}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
397 |
Now, generate the {document_type}:
|
398 |
"""
|
|
|
399 |
logging.info(f"Generating document for type: {document_type}")
|
400 |
try:
|
401 |
response = openai.ChatCompletion.create(
|
|
|
419 |
Output('document-preview', 'children', allow_duplicate=True),
|
420 |
Input('btn-send-chat', 'n_clicks'),
|
421 |
State('chat-input', 'value'),
|
422 |
+
State('selected-doc-type', 'data'),
|
423 |
prevent_initial_call=True
|
424 |
)
|
425 |
+
def update_document_via_chat(n_clicks, chat_input, selected_doc_type):
|
426 |
global current_document, document_type
|
427 |
if not chat_input or current_document is None:
|
428 |
raise dash.exceptions.PreventUpdate
|
429 |
+
|
430 |
+
if selected_doc_type in spreadsheet_types:
|
431 |
+
prompt = f"""Update the following {selected_doc_type} spreadsheet based on this instruction: {chat_input}
|
432 |
+
Current spreadsheet (CSV format):
|
433 |
+
{current_document}
|
434 |
+
Instructions:
|
435 |
+
1. Provide the updated spreadsheet in CSV format only.
|
436 |
+
2. Do not include any narrative, only the spreadsheet in CSV.
|
437 |
+
Now, provide the updated {selected_doc_type} spreadsheet:
|
438 |
+
"""
|
439 |
+
else:
|
440 |
+
prompt = f"""Update the following {selected_doc_type} document based on this instruction: {chat_input}
|
441 |
Current document:
|
442 |
{current_document}
|
443 |
Instructions:
|
444 |
1. Provide the updated document content.
|
445 |
2. Maintain proper formatting and structure.
|
446 |
3. Incorporate the requested changes seamlessly.
|
447 |
+
Now, provide the updated {selected_doc_type}:
|
448 |
"""
|
449 |
+
logging.info(f"Updating document via chat for {selected_doc_type} instruction: {chat_input}")
|
|
|
450 |
try:
|
451 |
response = openai.ChatCompletion.create(
|
452 |
model="gpt-4-1106-preview",
|
|
|
459 |
)
|
460 |
current_document = response['choices'][0]['message']['content']
|
461 |
logging.info("Document updated via chat successfully.")
|
462 |
+
if selected_doc_type in spreadsheet_types:
|
463 |
+
preview = spreadsheet_preview(current_document)
|
464 |
+
else:
|
465 |
+
preview = dcc.Markdown(current_document)
|
466 |
+
return f"Document updated based on: {chat_input}", preview
|
467 |
except Exception as e:
|
468 |
logging.error(f"Error updating document via chat: {str(e)}")
|
469 |
return f"Error updating document: {str(e)}", html.Div(f"Error updating document: {str(e)}")
|
|
|
471 |
@app.callback(
|
472 |
Output("download-document", "data"),
|
473 |
Input("btn-download", "n_clicks"),
|
474 |
+
State('selected-doc-type', 'data'),
|
475 |
prevent_initial_call=True
|
476 |
)
|
477 |
+
def download_document(n_clicks, selected_doc_type):
|
478 |
+
global current_document
|
479 |
if current_document is None:
|
480 |
raise dash.exceptions.PreventUpdate
|
481 |
+
|
482 |
+
if selected_doc_type in spreadsheet_types:
|
483 |
try:
|
484 |
df = pd.read_csv(StringIO(current_document))
|
485 |
output = BytesIO()
|
486 |
with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
|
487 |
+
df.to_excel(writer, sheet_name=selected_doc_type, index=False)
|
488 |
+
logging.info(f"{selected_doc_type} document downloaded as Excel.")
|
489 |
+
output.seek(0)
|
490 |
+
return dcc.send_bytes(output.read(), f"{selected_doc_type}.xlsx")
|
491 |
except Exception as e:
|
492 |
+
logging.error(f"Error downloading {selected_doc_type} document: {str(e)}")
|
493 |
+
return dcc.send_string(f"Error downloading {selected_doc_type}: {str(e)}", f"{selected_doc_type}_error.txt")
|
494 |
else:
|
495 |
try:
|
496 |
doc = Document()
|
497 |
doc.add_paragraph(current_document)
|
498 |
output = BytesIO()
|
499 |
doc.save(output)
|
500 |
+
logging.info(f"{selected_doc_type} document downloaded as Word.")
|
501 |
+
output.seek(0)
|
502 |
+
return dcc.send_bytes(output.read(), f"{selected_doc_type}.docx")
|
503 |
except Exception as e:
|
504 |
logging.error(f"Error downloading document: {str(e)}")
|
505 |
+
return dcc.send_string(f"Error downloading document: {str(e)}", f"{selected_doc_type}_error.txt")
|
506 |
|
507 |
if __name__ == '__main__':
|
508 |
print("Starting the Dash application...")
|