Simple Chat Application currently allows users to upload documents in various formats—such as PDFs, Word documents, and images—and processes them using Azure Document Intelligence for text extraction. However, the application lacks support for processing tabular data found in documents like spreadsheets or CSV files.
Adding support for tabular data would enable the AI to extract, understand, and utilize structured data from tables, enhancing the application's ability to provide more accurate and detailed responses during chats. This feature would be particularly beneficial for users who rely on data presented in tables for insights, reports, or decision-making processes.
Motivation
Enhanced Data Retrieval: Tables often contain critical information that isn't easily captured through plain text extraction. Supporting tabular data ensures users can retrieve and interact with all relevant information in their documents.
Improved AI Responses: With access to structured data, the AI can generate more precise answers, perform calculations, and provide data-driven insights, leading to a richer user experience.
Broader Document Support: Many business documents include tables or are entirely tabular (like Excel files). Supporting these formats expands the application's utility and appeal.
Tasks
Research and Development:
Determine the best practices for handling and storing tabular data.
Pipeline Modification:
Update the document ingestion pipeline to extract and process tables.
Data Schema Update:
Determine best method for storing data (cosmos, sql, ai search (by row? new index?)
Interface and Experience:
Update the front-end to display tables or summaries when responding to user queries.
Ensure the UI remains clean and user-friendly, even when presenting complex data.
Testing and Validation:
Test with various documents containing tables to ensure accurate extraction and retrieval.
Validate that the AI provides correct and helpful responses when tabular data is involved.
Security and Compliance:
Review data handling procedures to ensure compliance with data protection regulations, especially when dealing with potentially sensitive structured data.
Simple Chat Application currently allows users to upload documents in various formats—such as PDFs, Word documents, and images—and processes them using Azure Document Intelligence for text extraction. However, the application lacks support for processing tabular data found in documents like spreadsheets or CSV files.
Adding support for tabular data would enable the AI to extract, understand, and utilize structured data from tables, enhancing the application's ability to provide more accurate and detailed responses during chats. This feature would be particularly beneficial for users who rely on data presented in tables for insights, reports, or decision-making processes.
Motivation
Enhanced Data Retrieval: Tables often contain critical information that isn't easily captured through plain text extraction. Supporting tabular data ensures users can retrieve and interact with all relevant information in their documents.
Improved AI Responses: With access to structured data, the AI can generate more precise answers, perform calculations, and provide data-driven insights, leading to a richer user experience.
Broader Document Support: Many business documents include tables or are entirely tabular (like Excel files). Supporting these formats expands the application's utility and appeal.
Tasks
Research and Development:
Pipeline Modification:
Data Schema Update:
Interface and Experience:
Testing and Validation:
Security and Compliance:
Future?