The use of Azure Document Intelligence and its pre-built models is a well-established method to crack unstructured documents. Nevertheless, there are always documents that it is unable to perform reilable extraction with. This process attempts to extract required data points for an invoice. If those elements are not found then we fall back to other means.
- Fuzzy matching against a list of known vales
- Use of GPT models to extract data
- Python 3.11
- Azure Functions Core Tools
- Azure Document Intelligence instance with endpoint and API key
- CSV that matches format Type, Code, Name, Name 1, Name 2, City, District, Postal Code, Street, House Number, Country Key, Region
- ARTIFACT_STORAGE
- DOCUMENT_INTELLIGENCE_ENDPOINT
- DOCUMENT_INTELLIGENCE_KEY
- COMPANY_FILE_PATH
- MODEL_CONFIDENCE_THRESHHOLD=0.8
- GPT4_API_KEY
- GPT4_ENDPOINT
- APPLICATIONINSIGHTS_CONNECTION_STRING
For local dev add these to a local.settings.json file
The storage account should have three containers that the function app can write to:
- invoices-inbox
- invoices-results
- invoices-processed
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