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DocumentStudy

Backlog

  1. EPIC: Process documents using Document Intelligence SDK (layout model)
    • TASK: build app/service to run analyze from DocIntel SDK
    • TASK: implement configuration options for document intelligence endpoint (and key?), and model name
    • TASK: implement configuration options for "raw" and "cooked" blob storage
    • TASK: implement request object with string parameter for specific file (blob storage url)
    • TASK: implement request object with bool parameter for markdown format (only works with layout model)
    • TASK: implement request object with list parameter for list of entity names with descriptions (primarily for use with LLM)
    • TASK: capture model output: text lines
    • TASK: capture model output: signatures
    • TASK: capture model output: tables
    • TASK: capture model output: checkbox / selection marks
    • TASK: capture model output: bounding boxes & page layout metadata
    • TASK: implement error handling
    • TASK: implement logging and monitoring of requests / responses
    • TASK: write results back to "cooked" blob storage (or other option)
  2. EPIC: Evaluate results
    • TASK: build app/service to run evaluation tests
    • TASK: implement configuration option for actual entities (ground truth)
    • TASK: implement test logic for accuracy
    • TASK: implement test logic to capture performance
    • TASK: implement logic to write test results to repository (file, database, other)
    • TASK: run test
    • TASK: generate evaluation report (summary + detailed mismatches)
  3. EPIC: Process documents using Document Intelligence SDK (layout model w/ key/value pairs features parameter)
    • TASK: build app/service to run analyze from DocIntel SDK
    • TASK: implement configuration options for document intelligence endpoint (and key?), and model name
    • TASK: implement configuration options for raw and cooked blob storage
    • TASK: implement request object with parameters for specific file (blob storage url)
    • TASK: implement request object with list of entity names with descriptions (primarily for use with LLM)
    • TASK: capture model output: entity key-value pairs
  4. EPIC: Process documents using Document Intelligence SDK (read model)
    • TASK: implement code changes to accommodate 'read model'
    • TASK: capture model output: handwriting
  5. EPIC: Process documents using Document Intelligence SDK + LLM
    • TASK: implement prompt template with rules
    • TASK: implement prompt template with placeholders for entities & descriptions (e.g. semantic synonyms)
    • TASK: implement prompt template with placeholder for doc intel text output
    • TASK: implement prompt template with desired output format (JSON schema?)
    • TASK: implement call to LLM

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