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| import gradio as gr | |
| import os | |
| import time | |
| import pandas as pd | |
| import sqlite3 | |
| import ocrmypdf | |
| from langchain.document_loaders import OnlinePDFLoader # for loading the pdf | |
| from langchain.embeddings import HuggingFaceEmbeddings # open source embedding model | |
| from langchain.text_splitter import CharacterTextSplitter | |
| from langchain.vectorstores import Chroma # for the vectorization part | |
| from langchain.chains import RetrievalQA # for conversing with chatGPT | |
| from langchain.chat_models import ChatOpenAI # the LLM model we'll use (ChatGPT) | |
| from langchain import PromptTemplate | |
| def load_pdf_and_generate_embeddings(pdf_doc, open_ai_key, relevant_pages): | |
| # If an OpenAI API key is provided, it will be used for ChatOpenAI (GPT-4) | |
| if open_ai_key is not None: | |
| os.environ['OPENAI_API_KEY'] = open_ai_key | |
| # OCR Conversion - skips conversion of pages that already contain text | |
| pdf_doc = ocr_converter(pdf_doc) | |
| # Load the pdf file | |
| loader = OnlinePDFLoader(pdf_doc) | |
| pages = loader.load_and_split() | |
| print('pages loaded:', len(pages)) | |
| # Create an instance of HuggingFaceEmbeddings (open source) for generating embeddings | |
| embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2") | |
| pages_to_be_loaded = [] | |
| if relevant_pages: | |
| page_numbers = relevant_pages.split(",") | |
| if len(page_numbers) != 0: | |
| for page_number in page_numbers: | |
| if page_number.isdigit(): | |
| pageIndex = int(page_number) - 1 | |
| if pageIndex >= 0 and pageIndex < len(pages): | |
| pages_to_be_loaded.append(pages[pageIndex]) | |
| # If no valid pages are specified, use the entire PDF. | |
| if len(pages_to_be_loaded) == 0: | |
| pages_to_be_loaded = pages.copy() | |
| # Create a vector store using the Chroma class with the open-source embeddings | |
| vectordb = Chroma.from_documents(pages_to_be_loaded, embedding=embeddings) | |
| # Configure the prompt template for the QA chain | |
| prompt_template = ( | |
| """Use the following pieces of context to answer the question at the end. If you do not know the answer, just return N/A. | |
| If you encounter a date, return it in mm/dd/yyyy format. If there is a Preface section in the document, extract the chapter# and the short description from the Preface. | |
| Chapter numbers are listed to the left in Preface and always start with an alphabet, for example A1-1. | |
| {context} | |
| Question: {question} | |
| Return the answer. Provide the answer in the JSON format and extract the key from the question. Where applicable, break the answer into bullet points. | |
| When the sentences are long, try and break them into sub sections and include all the information and do not skip any information. | |
| If there is an exception to the answer, please do include it in a 'Note:' section. If there are no exceptions to the answer, please skip the 'Note:' section. | |
| Include a 'For additional details refer to' section when the document has more information to offer on the topic being questioned. | |
| If the document has a Preface or 'Table of Contents' section, extract the chapter# and a short description and include the info under the 'For additional details refer to' section. | |
| List only the chapters that contain information or skip this section altogether. Do not use page numbers as chapter numbers as they are different. | |
| If additional information is found in multiple pages within the same chapter, list the chapter only once. | |
| If chapter information cannot be extracted, include any other information that will help the user navigate to the relevant sections of the document. | |
| If the document does not contain a Preface or 'Table of Contents' section, please do not call that out. For example, do not include statements like | |
| the following in the answer - 'The document does not contain a Preface or 'Table of Contents' section'""" | |
| ) | |
| PROMPT = PromptTemplate(template=prompt_template, input_variables=["context", "question"]) | |
| chain_type_kwargs = {"prompt": PROMPT} | |
| global pdf_qa | |
| pdf_qa = RetrievalQA.from_chain_type( | |
| llm=ChatOpenAI(temperature=0, model_name="gpt-4"), | |
| chain_type="stuff", | |
| retriever=vectordb.as_retriever(search_kwargs={"k": 5}), | |
| chain_type_kwargs=chain_type_kwargs, | |
| return_source_documents=False | |
| ) | |
| return "Ready" | |
| def create_db_connection(): | |
| DB_FILE = "./questionset.db" | |
| connection = sqlite3.connect(DB_FILE, check_same_thread=False) | |
| return connection | |
| def create_sqlite_table(connection): | |
| print("*****Entered the create_sqlite_table method*****") | |
| cursor = connection.cursor() | |
| try: | |
| data = f'SELECT * FROM questions' | |
| cursor.execute(data) | |
| cursor.fetchall() | |
| except sqlite3.OperationalError: | |
| cursor.execute( | |
| ''' | |
| CREATE TABLE questions (document_type TEXT NOT NULL, questionset_tag TEXT NOT NULL, field TEXT NOT NULL, question TEXT NOT NULL) | |
| ''') | |
| print("*****questions table has been created******") | |
| connection.commit() | |
| def load_master_questionset_into_sqlite(connection): | |
| create_sqlite_table(connection) | |
| cursor = connection.cursor() | |
| masterlist_for_DOT_count = cursor.execute( | |
| "Select COUNT(document_type) from questions where document_type=? and questionset_tag=?", | |
| ("DOT", "masterlist",) | |
| ).fetchone()[0] | |
| if masterlist_for_DOT_count == 0: | |
| print("DOT masterlist has not yet been loaded, proceeding to load.") | |
| fieldListForDOT, queryListForDOT = create_field_and_question_list_for_DOT() | |
| fieldListForTransmittalSummary, queryListForTransmittalSummary = create_field_and_question_list_for_Transmittal_Summary() | |
| i = 0 | |
| print("*****Entered the load master question set method*****") | |
| while i < len(queryListForDOT): | |
| cursor.execute( | |
| "INSERT INTO questions(document_type, questionset_tag, field, question) VALUES(?,?,?,?)", | |
| ["DOT", "masterlist", fieldListForDOT[i], queryListForDOT[i]] | |
| ) | |
| i += 1 | |
| i = 0 | |
| while i < len(queryListForTransmittalSummary): | |
| cursor.execute( | |
| "INSERT INTO questions(document_type, questionset_tag, field, question) VALUES(?,?,?,?)", | |
| ["Transmittal Summary", "masterlist", fieldListForTransmittalSummary[i], queryListForTransmittalSummary[i]] | |
| ) | |
| i += 1 | |
| connection.commit() | |
| total_questions = cursor.execute("Select COUNT(document_type) from questions").fetchone()[0] | |
| print("*******Total number of questions in the DB:", total_questions) | |
| def create_field_and_question_list_for_DOT(): | |
| query1 = "what is the Loan Number?" | |
| field1 = "Loan Number" | |
| query2 = "Who is the Borrower?" | |
| field2 = "Borrower" | |
| query3 = "what is the Case Number?" | |
| field3 = "Case Number" | |
| query4 = "what is the Mortgage Identification number?" | |
| field4 = "MIN Number" | |
| query5 = "DOT signed date?" | |
| field5 = "Signed Date" | |
| query6 = "Who is the Lender?" | |
| field6 = "Lender" | |
| query7 = "what is the VA/FHA Number?" | |
| field7 = "VA/FHA Number" | |
| query8 = "Who is the Co-Borrower?" | |
| field8 = "Co-Borrower" | |
| query9 = "What is the property type - single family, multi family?" | |
| field9 = "Property Type" | |
| query10 = "what is the Property Address?" | |
| field10 = "Property Address" | |
| query11 = "In what County is the property located?" | |
| field11 = "Property County" | |
| query12 = "what is the Electronically recorded date" | |
| field12 = "Electronic Recording Date" | |
| queryList = [query1, query2, query3, query4, query5, query6, query7, query8, query9, query10, query11, query12] | |
| fieldList = [field1, field2, field3, field4, field5, field6, field7, field8, field9, field10, field11, field12] | |
| return fieldList, queryList | |
| def create_field_and_question_list_for_Transmittal_Summary(): | |
| query1 = "Who is the Borrower?" | |
| field1 = "Borrower" | |
| query2 = "what is the Property Address?" | |
| field2 = "Property Address" | |
| query3 = "what is the Loan Term?" | |
| field3 = "Loan Term" | |
| query4 = "What is the Base Income?" | |
| field4 = "Base Income" | |
| query5 = "what is the Borrower's SSN?" | |
| field5 = "Borrower's SSN" | |
| query6 = "Who is the Co-Borrower?" | |
| field6 = "Co-Borrower" | |
| query7 = "What is the Original Loan Amount?" | |
| field7 = "Original Loan Amount" | |
| query8 = "What is the Initial P&I payment?" | |
| field8 = "Initial P&I payment" | |
| query9 = "What is the Co-Borrower's SSN?" | |
| field9 = "Co-Borrower’s SSN" | |
| query10 = "Number of units?" | |
| field10 = "Units#" | |
| query11 = "Who is the Seller?" | |
| field11 = "Seller" | |
| query12 = "Document signed date?" | |
| field12 = "Signed Date" | |
| queryList = [query1, query2, query3, query4, query5, query6, query7, query8, query9, query10, query11, query12] | |
| fieldList = [field1, field2, field3, field4, field5, field6, field7, field8, field9, field10, field11, field12] | |
| return fieldList, queryList | |
| def retrieve_document_type_and_questionsettag_from_sqlite(): | |
| connection = create_db_connection() | |
| load_master_questionset_into_sqlite(connection) | |
| cursor = connection.cursor() | |
| rows = cursor.execute("SELECT document_type, questionset_tag FROM questions order by document_type, upper(questionset_tag)").fetchall() | |
| print("Number of rows retrieved from DB:", len(rows)) | |
| list_for_dropdown = [] | |
| for i in rows: | |
| entries_in_row = list(i) | |
| concatenated_value = entries_in_row[0] + ":" + entries_in_row[1] | |
| if concatenated_value not in list_for_dropdown: | |
| list_for_dropdown.append(concatenated_value) | |
| print(concatenated_value) | |
| print("Number of unique entries found in the DB:", len(list_for_dropdown)) | |
| connection.close() | |
| return gr.Dropdown.update(choices=list_for_dropdown, value=list_for_dropdown[0]) | |
| def retrieve_fields_and_questions(dropdownoption): | |
| print("dropdownoption is:", dropdownoption) | |
| splitwords = dropdownoption.split(":") | |
| connection = create_db_connection() | |
| cursor = connection.cursor() | |
| fields_and_questions = cursor.execute( | |
| "SELECT document_type, field, question FROM questions where document_type=? and questionset_tag=?", | |
| (splitwords[0], splitwords[1],) | |
| ).fetchall() | |
| connection.close() | |
| return pd.DataFrame(fields_and_questions, columns=["documentType", "field", "question"]) | |
| def add_questionset(data, document_type, tag_for_questionset): | |
| connection = create_db_connection() | |
| create_sqlite_table(connection) | |
| cursor = connection.cursor() | |
| for index, row in data.iterrows(): | |
| cursor.execute( | |
| "INSERT INTO questions(document_type, questionset_tag, field, question) VALUES(?,?,?,?)", | |
| [document_type, tag_for_questionset, row['field'], row['question']] | |
| ) | |
| connection.commit() | |
| connection.close() | |
| def load_csv_and_store_questionset_into_sqlite(csv_file, document_type, tag_for_questionset): | |
| print('document type is:', document_type) | |
| print('tag_for_questionset is:', tag_for_questionset) | |
| if tag_for_questionset: | |
| if document_type: | |
| data = pd.read_csv(csv_file.name) | |
| add_questionset(data, document_type, tag_for_questionset) | |
| responseString = "Task Complete. Uploaded {} fields and the corresponding questions into the Database for {}:{}".format(data.shape[0], document_type, tag_for_questionset) | |
| return responseString | |
| else: | |
| return "Please select the Document Type and provide a name for the Question Set" | |
| def answer_predefined_questions(document_type_and_questionset): | |
| print('chosen document_type_and_questionset:', document_type_and_questionset) | |
| option_chosen = document_type_and_questionset.split(":") | |
| document_type = option_chosen[0] | |
| question_set = option_chosen[1] | |
| fields = [] | |
| questions = [] | |
| responses = [] | |
| connection = create_db_connection() | |
| cursor = connection.cursor() | |
| if document_type is not None and question_set is not None: | |
| rows = cursor.execute( | |
| "SELECT field, question FROM questions where document_type=? and questionset_tag=?", | |
| (document_type, question_set,) | |
| ).fetchall() | |
| for i in rows: | |
| entries_in_row = list(i) | |
| fields.append(entries_in_row[0]) | |
| questions.append(entries_in_row[1]) | |
| responses.append(pdf_qa.run(entries_in_row[1])) | |
| else: | |
| return "Please choose your Document Type:QuestionSet" | |
| return pd.DataFrame({"Field": fields, "Question to gpt-4": questions, "Response from gpt-4": responses}) | |
| def ocr_converter(input_file): | |
| image_pdf = input_file.name | |
| ocrmypdf.ocr(image_pdf, image_pdf, redo_ocr=True, language="eng") | |
| return image_pdf | |
| def summarize_contents(): | |
| question = "Generate a short summary of the contents along with no more than 3 leading/example questions. Do not return the response in json format" | |
| return pdf_qa.run(question) | |
| def answer_query(query): | |
| question = query | |
| return pdf_qa.run(question) | |
| css = """ | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| """ | |
| title = """ | |
| <div style="text-align: center;max-width: 700px;"> | |
| <h1>AskMoli - Chatbot for PDFs</h1> | |
| <p style="text-align: center;">Upload a .PDF, click the "Upload PDF and generate embeddings" button, <br /> | |
| Wait for the Status to show Ready. You can choose to get answers to the pre-defined question set OR ask your own question <br /> | |
| The app is built on GPT-4 and leverages the magic of PromptTemplate</p> | |
| </div> | |
| """ | |
| with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.HTML(title) | |
| with gr.Tab("Chatbot"): | |
| with gr.Column(): | |
| open_ai_key = gr.Textbox(label="Your GPT-4 OpenAI API key", type="password") | |
| pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type='file') | |
| relevant_pages = gr.Textbox(label="*Optional - List comma separated page numbers to load or leave this field blank to use the entire PDF") | |
| with gr.Row(): | |
| status = gr.Textbox(label="Status", placeholder="", interactive=False) | |
| load_pdf = gr.Button("Upload PDF and generate embeddings").style(full_width=False) | |
| with gr.Row(): | |
| summary = gr.Textbox(label="Summary") | |
| summarize_pdf = gr.Button("Have Moli Summarize the Contents").style(full_width=False) | |
| with gr.Row(): | |
| input = gr.Textbox(label="Type in your question") | |
| output = gr.Textbox(label="Answer") | |
| submit_query = gr.Button("Submit your own question to AskMoli").style(full_width=False) | |
| with gr.Row(): | |
| questionsets = gr.Dropdown(label="Pre-defined Question Sets stored in the DB", choices=[]) | |
| load_questionsets = gr.Button("Retrieve Pre-defined Question Sets from DB").style(full_width=False) | |
| fields_and_questions = gr.Dataframe(label="Fields and Questions in the chosen Question Set") | |
| load_fields_and_questions = gr.Button("Retrieve Pre-defined Questions from the DB for the chosen QuestionSet").style(full_width=False) | |
| with gr.Row(): | |
| answers = gr.Dataframe(label="Answers to Predefined Question set") | |
| answers_for_predefined_question_set = gr.Button("Get answers to the chosen pre-defined question set").style(full_width=False) | |
| with gr.Tab("OCR Converter"): | |
| with gr.Column(): | |
| image_pdf = gr.File(label="Load the pdf to be converted", file_types=['.pdf'], type='file') | |
| with gr.Row(): | |
| ocr_pdf = gr.File(label="OCR'd pdf", file_types=['.pdf'], type='file', file_count="single") | |
| convert_into_ocr = gr.Button("Convert").style(full_width=False) | |
| with gr.Tab("Upload Question Set"): | |
| with gr.Column(): | |
| document_types = [ | |
| "Mortgage 1040 US Individual Tax Returns 8453 Elec Form", | |
| "Mortgage 1098", | |
| "Mortgage 1099", | |
| "Mortgage Abstract", | |
| "Mortgage ACH Authorization Form", | |
| "Mortgage Advance Fee Agreement", | |
| "Mortgage Affidavit", | |
| "Mortgage Affidavit of Suspense Funds", | |
| "Mortgage Agreement Documents", | |
| "Mortgage Sales Contract", | |
| "Mortgage Loan Estimate", | |
| "Mortgage Alimony Or Child Support", | |
| "Mortgage Amended Proof Of Claim", | |
| "Mortgage Amortization Schedule", | |
| "Mortgage Flood Insurance", | |
| "Mortgage Appraisal Report", | |
| "Mortgage Appraisal Disclosure", | |
| "Mortgage ARM Letter", | |
| "Mortgage Arms Length Affidavit", | |
| "Mortgage Assignment-Recorded", | |
| "Mortgage Assignment-Unrecorded", | |
| "Mortgage Assignment of Rent or Lease", | |
| "Mortgage Automated Value Model", | |
| "Mortgage Award Letters", | |
| "Mortgage Bailee Letter", | |
| "Mortgage Balloon Disclosure", | |
| "Mortgage Bank Statement", | |
| "Mortgage Bankruptcy Documents", | |
| "Mortgage Bill of Sale", | |
| "Mortgage Billing Statement", | |
| "Mortgage Birth-Marriage-Death Certificate", | |
| "Mortgage Borrower Certification Authorization", | |
| "Mortgage Borrower Response Package", | |
| "Mortgage Brokers Price Opinion", | |
| "Mortgage Business Plan", | |
| "Mortgage Buydown Agreement", | |
| "Mortgage Bylaws Covenants Conditions Restrictions", | |
| "Mortgage Cash for Keys", | |
| "Mortgage Certificate of Redemption", | |
| "Mortgage Certificate of Sale", | |
| "Mortgage Certificate of Title", | |
| "Mortgage Certification of Amount Due Payoff Reinstatement", | |
| "Mortgage Checks-Regular or Cashiers", | |
| "Mortgage Closing Disclosure", | |
| "Mortgage Closing Protection Letter", | |
| "Mortgage Closing Other", | |
| "Mortgage Code Violations", | |
| "Mortgage Request for Release", | |
| "Mortgage Certificate of Liability Insurance", | |
| "Mortgage Commitment Letter", | |
| "Mortgage Complaint", | |
| "Mortgage Complaint Answer Counter Claim", | |
| "Mortgage Conditional Approval Letter", | |
| "Mortgage Conditional Commitment", | |
| "Mortgage Consent Order", | |
| "Mortgage Consolidated Mortgage CEMA", | |
| "Mortgage Conveyance Claims", | |
| "Mortgage Correction and Revision Agreement", | |
| "Mortgage Correspondence", | |
| "Mortgage Court Order Settlement Divorce Decree", | |
| "Mortgage Credit Report", | |
| "Mortgage Customer Signature Authorization", | |
| "Mortgage Debt Validation", | |
| "Mortgage Deed", | |
| "Mortgage Default Notices", | |
| "Mortgage Direct Debit Authorization Form", | |
| "Mortgage Disclosure Documents", | |
| "Mortgage Document Checklist", | |
| "Mortgage Document Correction and Fee Due Agreement", | |
| "Mortgage Dodd Frank Certification", | |
| "Mortgage Drivers License", | |
| "Mortgage Request for VOE", | |
| "Mortgage Environmental Indemnity Agreement", | |
| "Mortgage Equal Credit Opportunity Act Notice", | |
| "Mortgage Escrow Agreement", | |
| "Mortgage Escrow Analysis Trial Balance Worksheet", | |
| "Mortgage Instructions to Escrow Agent", | |
| "Mortgage Escrow Letters", | |
| "Mortgage Executed Deeds", | |
| "Mortgage Fair Lending Notice", | |
| "Mortgage Foreclosure Complaint", | |
| "Mortgage Foreclosure Judgement", | |
| "Mortgage Foreclosure Sale", | |
| "Mortgage FHA Neighborhood Watch", | |
| "Mortgage Truth-In-Lending Disclosure Statement", | |
| "Mortgage Financial Form", | |
| "Mortgage Financing Agreement", | |
| "Mortgage First Payment Letter", | |
| "Mortgage Forced Place Insurance Documents", | |
| "Mortgage Foreclosure Documents", | |
| "Mortgage Good Faith Estimate", | |
| "Mortgage Guaranty", | |
| "Mortgage HAMP Certifications", | |
| "Mortgage HOA-Condo Covenants and Dues", | |
| "Mortgage Exemption Hold Harmless Letter", | |
| "Mortgage Home Equity Signature Verification Card", | |
| "Mortgage Home Inspection", | |
| "Mortgage Property Liability Insurance", | |
| "Mortgage Homeowners Insurance Notice", | |
| "Mortgage HUD-1 Settlement Statement", | |
| "Mortgage Income Other", | |
| "Mortgage Indemnity Agreement", | |
| "Mortgage Informed Consumer Choice Disclosure Notice", | |
| "Mortgage Initial Escrow Account Disclosure Statement", | |
| "Mortgage Invoices", | |
| "Mortgage Land Lease or Land Trust", | |
| "Mortgage Land Title Adjustment", | |
| "Mortgage Last Will and Testament", | |
| "Mortgage Legal Description", | |
| "Mortgage Letters Of Administration", | |
| "Mortgage Letters of Testamentary", | |
| "Mortgage Listing Agreement", | |
| "Mortgage Litigation Guarantee", | |
| "Mortgage DIL Closing", | |
| "Mortgage Hardship Letter", | |
| "Mortgage Hardship Affidavit", | |
| "Mortgage Home Affordable Modification Agreement", | |
| "Mortgage Profit And Loss", | |
| "Mortgage Earnest Money Promissory Note", | |
| "Mortgage Rental Agreement", | |
| "Mortgage Repayment Plan", | |
| "Mortgage Short Sale Miscellaneous", | |
| "Mortgage LM - Trial Offer Letter or Plan", | |
| "Mortgage Errors and Omissions Agreement", | |
| "Mortgage Custom Type 2", | |
| "Mortgage Custom Type 1", | |
| "Mortgage Loan Agreement", | |
| "Mortgage Loan Closing Information Summary", | |
| "Mortgage Loan Modification", | |
| "Mortgage Loan Summary Report", | |
| "Mortgage Lock Confirmation", | |
| "Mortgage Loss Drafts", | |
| "Mortgage Loss Mitigation", | |
| "Mortgage Lost Assignment Affidavit", | |
| "Mortgage Mech Lien", | |
| "Mortgage Mediation", | |
| "Mortgage MI Claim Explanation of Benefits", | |
| "Mortgage MI Policy Cancellation Document", | |
| "Mortgage MI Repurchase Document", | |
| "Mortgage Miscellaneous Lien Release", | |
| "Mortgage Mobile Home Documentation", | |
| "Mortgage Monthly Activity Report", | |
| "Mortgage Deed of Trust-Recorded", | |
| "Mortgage PMI Disclosure", | |
| "Mortgage Payments", | |
| "Mortgage Deed of Trust-Unrecorded", | |
| "Mortgage Motion For Relief", | |
| "Mortgage Note", | |
| "Mortgage Note Affidavit", | |
| "Mortgage Note Endorsements", | |
| "Mortgage Notice Of Appearance", | |
| "Mortgage Notice of Default Filedrecorded", | |
| "Mortgage Notice of Final Cure", | |
| "Mortgage Notice of Levy", | |
| "Mortgage Notice of Payment Change", | |
| "Mortgage Notice of Right to Cancel", | |
| "Mortgage Notice of Sale", | |
| "Mortgage Notice of Second Lien", | |
| "Mortgage Notice of Servicing Transfer-Transferee", | |
| "Mortgage Notice of Servicing Transfer-Transferor", | |
| "Mortgage Notice of Termination", | |
| "Mortgage Notice to Quit", | |
| "Mortgage Objection to Claim", | |
| "Mortgage Processing and Underwriting Doc Set", | |
| "Mortgage Objection to Motion for Relief", | |
| "Mortgage Affidavit of Occupancy", | |
| "Mortgage Occupancy Agreement", | |
| "Mortgage Occupancy Termination Agreement", | |
| "Mortgage Ombudsman Documents", | |
| "Mortgage Owner Affidavit", | |
| "Mortgage Ownership and Encumbrances Report", | |
| "Mortgage Pay History External", | |
| "Mortgage Paystub", | |
| "Mortgage Payoff Demand Statement", | |
| "Mortgage PMI Certificate", | |
| "Mortgage Post Petition Fee Notices", | |
| "Mortgage Post Sale Documents", | |
| "Mortgage Power of Attorney-Recorded", | |
| "Mortgage Power of Attorney-Unrecorded", | |
| "Mortgage Closing Instructions", | |
| "Mortgage Preliminary Modification", | |
| "Mortgage Merged-Privacy Policy Notice-Title Policy - Privacy Policy-1098 Privacy Policy", | |
| "Mortgage Probate Court Order", | |
| "Mortgage Proof of Claim", | |
| "Mortgage Property Legal and Vesting Report", | |
| "Mortgage Property Management Agreement", | |
| "Mortgage Property Notices", | |
| "Mortgage Public Assistance", | |
| "Mortgage Record Owner and Lien Certificate", | |
| "Mortgage Recorded Satisfaction", | |
| "Mortgage Regfore Affidavit Executed", | |
| "Mortgage Release of Lis Pendens", | |
| "Mortgage REO Bids", | |
| "Mortgage REO Other", | |
| "Mortgage Form 26-1820 Report and Certificate of Loan Disbursement", | |
| "Mortgage Request for Verification of Rent or Mortgage", | |
| "Mortgage Request for Waiver of R.E. Tax Escrow Requirements", | |
| "Mortgage 1003", | |
| "Mortgage RMA Package", | |
| "Mortgage Sale Postponement", | |
| "Mortgage Sale or Milestone Rescission", | |
| "Mortgage Satisfaction of Judgement Tax Mortgage Liens", | |
| "Mortgage Security Agreement", | |
| "Mortgage Separation Agreement", | |
| "Mortgage Servicing Acquisition", | |
| "Mortgage Servicing Disclosure Statement", | |
| "Mortgage Short Payoffs", | |
| "Mortgage Signature-Name Affidavit", | |
| "Mortgage Assumption of Mortgage", | |
| "Mortgage SCRA Related Documents", | |
| "Mortgage Social Security Card or Customer ID", | |
| "Mortgage Soft Delete", | |
| "Mortgage Flood Hazard Determination Form", | |
| "Mortgage Stipulated Agreement", | |
| "Mortgage Subordination Agreement", | |
| "Mortgage Subordination Request Form", | |
| "Mortgage Appointment of Substitute Trustee", | |
| "Mortgage Merged-Real Estate Taxes-Tax Bill-Tax Certificate", | |
| "Mortgage Tax Certificate", | |
| "Mortgage Tax Record Information Sheet", | |
| "Mortgage Tax Liens", | |
| "Mortgage Tax Search", | |
| "Mortgage Third Party Authorization", | |
| "Mortgage Title Commitment-Equity or Property Report", | |
| "Mortgage Title Policy", | |
| "Mortgage Title Policy Endorsement", | |
| "Mortgage Title Search", | |
| "Mortgage Title Insurance Other", | |
| "Mortgage Transfer of Claim", | |
| "Mortgage Uniform Underwriting and Transmittal Summary", | |
| "Mortgage Trustee Sale Guarantee", | |
| "Mortgage UCC-1 Financing Statement", | |
| "Mortgage Others", | |
| "Mortgage Unknown", | |
| "Mortgage Utility Bill", | |
| "Mortgage Valuation Orders", | |
| "Mortgage Verification Document Set", | |
| "Mortgage Verification of Service for Military Home Buyers", | |
| "Mortgage W2", | |
| "Mortgage W9", | |
| "Mortgage Wire Transfer Instructions", | |
| "Mortgage Workmens Compensation", | |
| "Mortgage Writ of Possession", | |
| "Mortgage Cover Page", | |
| "Mortgage Barcode Page", | |
| "Mortgage Wisconsin Tax Escrow Option Notice", | |
| "Mortgage Hazard Insurance Declaration", | |
| "Mortgage Flood Insurance Declaration", | |
| "Mortgage Quitclaim Deed", | |
| "Mortgage Tax Deed", | |
| "Mortgage Warranty Deed", | |
| "Mortgage ALTA Settlement Statement", | |
| "Mortgage Home Inspection Waiver", | |
| "Mortgage Insurance Disclosure" | |
| ] | |
| document_type_for_questionset = gr.Dropdown(choices=document_types, label="Select the Document Type") | |
| tag_for_questionset = gr.Textbox(label="Please provide a name for the question set. Ex: rwikd-dot-basic-questionset-20230707.") | |
| csv_file = gr.File(label="Load a csv - 2 columns with the headers as field, question", file_types=['.csv'], type='file') | |
| with gr.Row(): | |
| status_for_loading_csv = gr.Textbox(label="Status", placeholder="", interactive=False) | |
| load_csv = gr.Button("Upload data into the database").style(full_width=False) | |
| load_pdf.click(load_pdf_and_generate_embeddings, inputs=[pdf_doc, open_ai_key, relevant_pages], outputs=status) | |
| summarize_pdf.click(summarize_contents, outputs=summary) | |
| load_csv.click(load_csv_and_store_questionset_into_sqlite, inputs=[csv_file, document_type_for_questionset, tag_for_questionset], outputs=status_for_loading_csv) | |
| load_questionsets.click(retrieve_document_type_and_questionsettag_from_sqlite, outputs=questionsets) | |
| load_fields_and_questions.click(retrieve_fields_and_questions, questionsets, fields_and_questions) | |
| answers_for_predefined_question_set.click(answer_predefined_questions, questionsets, answers) | |
| convert_into_ocr.click(ocr_converter, image_pdf, ocr_pdf) | |
| submit_query.click(answer_query, input, output) | |
| # Use this flavor of demo.launch if you need the app to have an admin page. | |
| demo.launch(debug=True) | |