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  • function clean_text

    Cleans and normalizes text content by removing HTML tags, normalizing whitespace, and stripping markdown formatting elements.

    File: /tf/active/vicechatdev/improved_convert_disclosures_to_table.py

    text-processing text-cleaning normalization html-removal markdown-removal

  • function extract_warranty_data_improved

    Parses markdown-formatted warranty documentation to extract structured warranty data including IDs, titles, sections, disclosure text, and reference citations.

    File: /tf/active/vicechatdev/improved_convert_disclosures_to_table.py

    markdown-parsing text-extraction warranty-processing document-parsing regex

  • function create_csv_report_improved

    Creates two CSV reports from warranty data: a summary report with key fields and a detailed report with all fields including full disclosures.

    File: /tf/active/vicechatdev/improved_convert_disclosures_to_table.py

    csv report-generation file-io warranty data-export

  • function create_excel_report_improved

    Creates a multi-sheet Excel report from warranty data, including main report, summary view, complete data, references, and statistics sheets with auto-formatted columns.

    File: /tf/active/vicechatdev/improved_convert_disclosures_to_table.py

    excel reporting data-export pandas multi-sheet

  • function main_v9

    Orchestrates the conversion of an improved markdown file containing warranty disclosures into multiple tabular formats (CSV, Excel, Word) with timestamp-based file naming.

    File: /tf/active/vicechatdev/improved_convert_disclosures_to_table.py

    file-conversion markdown-processing warranty-data csv-export excel-export

  • class RegulatoryExtractor

    A class for extracting structured metadata from regulatory guideline PDF documents using LLM-based analysis and storing the results in an Excel tracking spreadsheet.

    File: /tf/active/vicechatdev/reg_extractor.py

    pdf-extraction regulatory-documents llm-extraction ocr data-extraction

  • function extract_warranty_data

    Parses markdown-formatted warranty documentation to extract structured warranty information including IDs, titles, sections, source document counts, warranty text, and disclosure content.

    File: /tf/active/vicechatdev/convert_disclosures_to_table.py

    markdown-parsing data-extraction warranty-processing text-processing regex

  • function main_v16

    Converts a markdown file containing warranty disclosure data into multiple tabular formats (CSV, Excel, Word) with timestamped output files.

    File: /tf/active/vicechatdev/convert_disclosures_to_table.py

    markdown-conversion data-extraction report-generation csv-export excel-export

  • function extract_total_references

    Extracts the total count of references from markdown-formatted content by first checking for a header line with the total, then falling back to manually counting reference entries.

    File: /tf/active/vicechatdev/enhanced_word_converter_fixed.py

    markdown parsing text-processing references bibliography

  • class OneCo_hybrid_RAG

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG copy.py

    class oneco_hybrid_rag

  • class FixedProjectVictoriaGenerator

    Fixed Project Victoria Disclosure Generator that properly handles all warranty sections.

    File: /tf/active/vicechatdev/fixed_project_victoria_generator.py

    class fixedprojectvictoriagenerator

  • class PatternBasedExtractor

    Extract flocks based on farm-level In-Ovo usage patterns.

    File: /tf/active/vicechatdev/pattern_based_extraction.py

    class patternbasedextractor

  • function main_v4

    Command-line interface function that orchestrates pattern-based extraction of poultry flock data, including data loading, pattern classification, geocoding, and export functionality.

    File: /tf/active/vicechatdev/pattern_based_extraction.py

    cli command-line-interface data-extraction poultry-data pattern-analysis

  • function quick_clean

    Cleans flock data by identifying and removing flocks that have treatment records with timing inconsistencies (treatments administered outside the flock's start/end date range).

    File: /tf/active/vicechatdev/quick_cleaner.py

    data-cleaning data-quality flock-management livestock poultry

  • class pathobrowser_base

    Base class that contains all static elements of the app Parameters ---------- image : str An Image UID which may be passed on app startup. Immediately redirects to said image Attributes ---------- current_user : Userclass A class containing various information on the user workspace : panel.layout.Column The main container of the app sidebar : panel.layout.Column Container showing items on the side of the app head : panel.layout.Row The header of the app modal : panel.layout.Column The container for the modal window of the app

    File: /tf/active/vicechatdev/datacapture_integrated.py

    class pathobrowser_base

  • class OneCo_hybrid_RAG_v1

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG_old.py

    class oneco_hybrid_rag

  • function select_dataset

    Interactive command-line function that prompts users to select between original, cleaned, or comparison of flock datasets for analysis.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    user-interface dataset-selection interactive command-line data-loading

  • function load_analysis_data

    Loads CSV dataset(s) into pandas DataFrames based on dataset configuration, supporting both single dataset loading and comparison mode with two datasets.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-loading csv pandas file-io data-analysis

  • function create_data_quality_dashboard_v1

    Creates an interactive data quality dashboard for analyzing treatment timing issues in poultry flock management data by loading and processing CSV files containing timing anomalies.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality dashboard visualization poultry-management treatment-timing

  • function create_data_quality_dashboard

    Creates an interactive command-line dashboard for analyzing data quality issues in treatment timing data, specifically focusing on treatments administered outside of flock lifecycle dates.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality dashboard interactive menu-driven timing-analysis

  • function show_critical_errors

    Displays critical data quality errors in treatment records, focusing on date anomalies including 1900 dates, extreme future dates, and extreme past dates relative to flock lifecycles.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality validation error-reporting date-validation data-cleaning

  • function analyze_flock_type_patterns

    Analyzes and prints timing pattern statistics for flock data by categorizing issues that occur before start time and after end time, grouped by flock type.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-analysis pandas timing-patterns flock-management aggregation

  • function analyze_problematic_products

    Analyzes and prints statistical information about products involved in severe timing issues, including product frequency counts and their associated diagnostic classes.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-analysis healthcare medical-products timing-issues diagnostic-analysis

  • function show_problematic_flocks

    Analyzes and displays problematic flocks from a dataset by identifying those with systematic timing issues in their treatment records, categorizing them by severity and volume.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality reporting diagnostics livestock-management data-validation

  • function analyze_temporal_trends

    Analyzes and prints temporal trends in timing issues for treatments that occur before flock start dates or after flock end dates, breaking down occurrences by year and month.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    temporal-analysis data-quality time-series reporting data-validation

  • function generate_action_report

    Generates a comprehensive corrective action report for data quality issues in treatment records, categorizing actions by urgency and providing impact assessment.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality reporting veterinary treatment-records data-validation

  • function compare_datasets

    Analyzes and compares two pandas DataFrames containing flock data (original vs cleaned), printing detailed statistics about removed records, type distributions, and impact assessment.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality comparison analysis reporting statistics

  • class QueryBasedExtractor_v2

    A class that performs targeted information extraction from text using LLM-based query-guided extraction, with support for handling long documents through chunking and token management.

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG.py

    information-extraction text-processing llm openai query-based

  • class OneCo_hybrid_RAG_v2

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG.py

    class oneco_hybrid_rag

  • class ExtensiveSearchManager

    Manages extensive search functionality including full document retrieval, summarization, and enhanced context gathering.

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG.py

    class extensivesearchmanager

  • function generate_neo4j_schema_report

    Generates a comprehensive schema report of a Neo4j graph database, including node labels, relationships, properties, constraints, indexes, and sample data, outputting multiple file formats (JSON, HTML, Python snippets, Cypher examples).

    File: /tf/active/vicechatdev/neo4j_schema_report.py

    neo4j graph-database schema-analysis database-introspection documentation-generation

  • class ProjectVictoriaDisclosureGenerator

    Main class for generating Project Victoria disclosures from warranty claims.

    File: /tf/active/vicechatdev/project_victoria_disclosure_generator.py

    class projectvictoriadisclosuregenerator

  • function main_v29

    Entry point function that orchestrates the Project Victoria disclosure analysis by initializing the generator, running the complete analysis, and displaying results with next steps.

    File: /tf/active/vicechatdev/project_victoria_disclosure_generator.py

    main-entry-point cli disclosure-analysis legal-documentation project-victoria

  • class pathobrowser_base_v1

    Base class that contains all static elements of the app Parameters ---------- image : str An Image UID which may be passed on app startup. Immediately redirects to said image Attributes ---------- current_user : Userclass A class containing various information on the user workspace : panel.layout.Column The main container of the app sidebar : panel.layout.Column Container showing items on the side of the app head : panel.layout.Row The header of the app modal : panel.layout.Column The container for the modal window of the app

    File: /tf/active/vicechatdev/datacapture.py

    class pathobrowser_base

  • function extract_previous_reports_summary

    Extracts and summarizes key information from previous meeting report files using document extraction and OpenAI's GPT-4o-mini model to provide context for upcoming meetings.

    File: /tf/active/vicechatdev/leexi/app.py

    meeting-analysis document-extraction text-summarization llm openai

  • function test_attendee_extraction_comprehensive

    A comprehensive test function that validates the attendee extraction logic from meeting transcripts, comparing actual speakers versus mentioned names, and demonstrating integration with meeting minutes generation.

    File: /tf/active/vicechatdev/leexi/test_attendee_comprehensive.py

    testing attendee-extraction meeting-minutes transcript-parsing speaker-identification

  • function parse_log_line

    Parses a structured log line string and extracts timestamp, logger name, log level, and message components into a dictionary.

    File: /tf/active/vicechatdev/SPFCsync/monitor.py

    logging parsing regex text-processing log-analysis

  • function analyze_logs

    Parses and analyzes log files to extract synchronization statistics, error counts, and performance metrics for a specified time period.

    File: /tf/active/vicechatdev/SPFCsync/monitor.py

    log-analysis file-synchronization monitoring statistics parsing

  • function main_v33

    Command-line interface entry point for monitoring SharePoint to FileCloud synchronization logs, providing status analysis, log tailing, and real-time watching capabilities.

    File: /tf/active/vicechatdev/SPFCsync/monitor.py

    cli command-line-interface log-monitoring sharepoint filecloud

  • class SyncDiagnostics

    A diagnostic class that analyzes and reports on synchronization issues between SharePoint and FileCloud, identifying missing files and root causes of sync failures.

    File: /tf/active/vicechatdev/SPFCsync/deep_diagnostics.py

    diagnostics sync-analysis sharepoint filecloud troubleshooting

  • function main_v17

    Executes a diagnostic analysis for file synchronization issues, analyzes missing files, and saves the results to a JSON file.

    File: /tf/active/vicechatdev/SPFCsync/deep_diagnostics.py

    diagnostics file-synchronization sharepoint filecloud analysis

  • function search_and_locate

    Searches for specific numbered folders (01-08) in a SharePoint site and traces their locations, contents, and file distributions by type.

    File: /tf/active/vicechatdev/SPFCsync/search_detailed.py

    sharepoint search diagnostic folder-discovery microsoft-graph

  • function dry_run_test

    Performs a dry run test of SharePoint to FileCloud synchronization, analyzing up to a specified number of documents without actually transferring files.

    File: /tf/active/vicechatdev/SPFCsync/dry_run_test.py

    dry-run testing sharepoint filecloud sync

  • function check_site_vs_channels

    Diagnostic function that analyzes and compares SharePoint site structure, specifically examining the main site document library versus Teams channel document libraries to identify the correct library for synchronization.

    File: /tf/active/vicechatdev/SPFCsync/check_site_library.py

    sharepoint diagnostic microsoft-graph document-library teams-channels

  • function analyze_structure

    Analyzes and reports on the folder structure of a SharePoint site, displaying folder paths, file counts, and searching for expected folder patterns.

    File: /tf/active/vicechatdev/SPFCsync/analyze_structure.py

    sharepoint analysis folder-structure microsoft-graph audit

  • function extensive_mode_example

    Demonstrates the usage of DocChatRAG's extensive mode for detailed document analysis with a sample query about methodologies.

    File: /tf/active/vicechatdev/docchat/example_usage.py

    example demo RAG retrieval-augmented-generation extensive-mode

  • function full_reading_example

    Demonstrates the full reading mode of a RAG (Retrieval-Augmented Generation) system by processing all documents to answer a comprehensive query about key findings.

    File: /tf/active/vicechatdev/docchat/example_usage.py

    example demonstration RAG retrieval-augmented-generation full-reading

  • function get_instruction_templates

    Flask API endpoint that returns a dictionary of predefined instruction templates for different document types including SOPs, work instructions, quality forms, and document comparison guidelines.

    File: /tf/active/vicechatdev/docchat/app.py

    flask api endpoint templates instructions

  • class DocChatRAG

    Main RAG engine with three operating modes: 1. Basic RAG (similarity search) 2. Extensive (full document retrieval with preprocessing) 3. Full Reading (process all documents)

    File: /tf/active/vicechatdev/docchat/rag_engine.py

    class docchatrag

  • function test_docx_file

    Tests the ability to open and read a Microsoft Word (.docx) document file, validating file existence, size, and content extraction capabilities.

    File: /tf/active/vicechatdev/docchat/test_problematic_files.py

    document-testing file-validation docx word-document diagnostic

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