replace form recognizer with doc intelligence (#686)

* Adding anchors

* replace form recognizer with doc intelligence

* Port to doc intelligence

* Revert changes

* Reword printed text

---------

Co-authored-by: Pamela Fox <[email protected]>
Co-authored-by: Pamela Fox <[email protected]>

Author: Dybe

README.md

@@ -85,12 +85,12 @@ However, you can try the [Azure pricing calculator](https://azure.com/e/8ffbe5b1
 
 - Azure App Service: Basic Tier with 1 CPU core, 1.75 GB RAM. Pricing per hour. [Pricing](https://azure.microsoft.com/pricing/details/app-service/linux/)
 - Azure OpenAI: Standard tier, ChatGPT and Ada models. Pricing per 1K tokens used, and at least 1K tokens are used per question. [Pricing](https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/)
-- Form Recognizer: SO (Standard) tier using pre-built layout. Pricing per document page, sample documents have 261 pages total. [Pricing](https://azure.microsoft.com/pricing/details/form-recognizer/)
+- Azure AI Document Intelligence: SO (Standard) tier using pre-built layout. Pricing per document page, sample documents have 261 pages total. [Pricing](https://azure.microsoft.com/pricing/details/form-recognizer/)
 - Azure AI Search: Standard tier, 1 replica, free level of semantic search. Pricing per hour.[Pricing](https://azure.microsoft.com/pricing/details/search/)
 - Azure Blob Storage: Standard tier with ZRS (Zone-redundant storage). Pricing per storage and read operations. [Pricing](https://azure.microsoft.com/pricing/details/storage/blobs/)
 - Azure Monitor: Pay-as-you-go tier. Costs based on data ingested. [Pricing](https://azure.microsoft.com/pricing/details/monitor/)
 
-To reduce costs, you can switch to free SKUs for Azure App Service and Form Recognizer by changing the parameters file under the `infra` folder. There are some limits to consider; for example, the free Form Recognizer resource only analyzes the first 2 pages of each document. You can also reduce costs associated with the Form Recognizer by reducing the number of documents in the `data` folder, or by removing the postprovision hook in `azure.yaml` that runs the `prepdocs.py` script.
+To reduce costs, you can switch to free SKUs for Azure App Service and Azure AI Document Intelligence by changing the parameters file under the `infra` folder. There are some limits to consider; for example, the free Azure AI Document Intelligence resource only analyzes the first 2 pages of each document. You can also reduce costs associated with the Azure AI Document Intelligence by reducing the number of documents in the `data` folder, or by removing the postprovision hook in `azure.yaml` that runs the `prepdocs.py` script.
 
 ⚠️ To avoid unnecessary costs, remember to take down your app if it's no longer in use,
 either by deleting the resource group in the Portal or running `azd down`.
@@ -203,7 +203,7 @@ You can also customize the search service (new or existing) for non-English sear
 
 #### Other existing Azure resources
 
-You can also use existing Form Recognizer and Storage Accounts. See `./infra/main.parameters.json` for list of environment variables to pass to `azd env set` to configure those existing resources.
+You can also use existing Azure AI Document Intelligence and Storage Accounts. See `./infra/main.parameters.json` for list of environment variables to pass to `azd env set` to configure those existing resources.
 
 #### Provision remaining resources
 

scripts/prepdocs.py

@@ -40,10 +40,10 @@ def setup_file_strategy(credential: AsyncTokenCredential, args: Any) -> FileStra
     if args.localpdfparser:
         pdf_parser = LocalPdfParser()
     else:
-        # check if Azure Form Recognizer credentials are provided
+        # check if Azure Document Intelligence credentials are provided
         if args.formrecognizerservice is None:
             print(
-                "Error: Azure Form Recognizer service is not provided. Please provide formrecognizerservice or use --localpdfparser for local pypdf parser."
+                "Error: Azure Document Intelligence service is not provided. Please provide --formrecognizerservice or use --localpdfparser for local pypdf parser."
             )
             exit(1)
         formrecognizer_creds: Union[AsyncTokenCredential, AzureKeyCredential] = (
@@ -228,17 +228,17 @@ async def main(strategy: Strategy, credential: AsyncTokenCredential, args: Any):
     parser.add_argument(
         "--localpdfparser",
         action="store_true",
-        help="Use PyPdf local PDF parser (supports only digital PDFs) instead of Azure Form Recognizer service to extract text, tables and layout from the documents",
+        help="Use PyPdf local PDF parser (supports only digital PDFs) instead of Azure Document Intelligence service to extract text, tables and layout from the documents",
     )
     parser.add_argument(
         "--formrecognizerservice",
         required=False,
-        help="Optional. Name of the Azure Form Recognizer service which will be used to extract text, tables and layout from the documents (must exist already)",
+        help="Optional. Name of the Azure Document Intelligence service which will be used to extract text, tables and layout from the documents (must exist already)",
     )
     parser.add_argument(
         "--formrecognizerkey",
         required=False,
-        help="Optional. Use this Azure Form Recognizer account key instead of the current user identity to login (use az login to set current user for Azure)",
+        help="Optional. Use this Azure Document Intelligence account key instead of the current user identity to login (use az login to set current user for Azure)",
     )
 
     parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")

scripts/prepdocslib/pdfparser.py

@@ -73,7 +73,7 @@ def __init__(
 
     async def parse(self, content: IO) -> AsyncGenerator[Page, None]:
         if self.verbose:
-            print(f"Extracting text from '{content.name}' using Azure Form Recognizer")
+            print(f"Extracting text from '{content.name}' using Azure Document Intelligence")
 
         async with DocumentAnalysisClient(
             endpoint=self.endpoint, credential=self.credential, headers={"x-ms-useragent": USER_AGENT}