original state

Author: brown9804

src/function_app.py

@@ -8,12 +8,6 @@
 import uuid
 import json
 
-# For image conversion and vision API
-from typing import List
-from io import BytesIO
-import requests  # For REST API to Vision
-from pdf2image import convert_from_bytes  # For PDF to image conversion
-
 app = func.FunctionApp(http_auth_level=func.AuthLevel.FUNCTION)
 
 ## DEFINITIONS 
@@ -41,14 +35,13 @@ def analyze_pdf(form_recognizer_client, pdf_bytes):
     logging.info(f"Document has {len(result.pages)} page(s), {len(result.tables)} table(s), and {len(result.styles)} style(s).")
     return result
 
-def extract_layout_data(result, visual_cues: List[dict] = None):
+def extract_layout_data(result):
     logging.info("Extracting layout data from analysis result.")
 
     layout_data = {
         "id": str(uuid.uuid4()),
         "pages": []
     }
-    visual_cues = visual_cues or []  # List of dicts with visual cue info per cell
 
     # Log styles
     for idx, style in enumerate(result.styles):
@@ -95,16 +88,12 @@ def extract_layout_data(result, visual_cues: List[dict] = None):
 
             for cell in table.cells:
                 content = cell.content.strip()
-                # Find matching visual cue for this cell (if any)
-                cue = next((vc for vc in visual_cues if vc.get("page_number") == page.page_number and vc.get("row_index") == cell.row_index and vc.get("column_index") == cell.column_index), None)
-                cell_info = {
+                table_data["cells"].append({
                     "row_index": cell.row_index,
                     "column_index": cell.column_index,
-                    "content": content,
-                    "visual_cue": cue["cue_type"] if cue else None
-                }
-                table_data["cells"].append(cell_info)
-                logging.info(f"Cell[{cell.row_index}][{cell.column_index}]: '{content}', visual_cue: {cell_info['visual_cue']}")
+                    "content": content
+                })
+                logging.info(f"Cell[{cell.row_index}][{cell.column_index}]: '{content}'")
 
             page_data["tables"].append(table_data)
 
@@ -167,31 +156,6 @@ def save_layout_data_to_cosmos(layout_data):
 ## MAIN 
 @app.blob_trigger(arg_name="myblob", path="pdfinvoices/{name}",
                   connection="invoicecontosostorage_STORAGE")
-def call_vision_api(image_bytes, subscription_key, endpoint):
-    vision_url = endpoint + "/vision/v3.2/analyze"
-    headers = {
-        'Ocp-Apim-Subscription-Key': subscription_key,
-        'Content-Type': 'application/octet-stream'
-    }
-    params = {
-        'visualFeatures': 'Objects,Color',  # Add more features if needed
-    }
-    response = requests.post(vision_url, headers=headers, params=params, data=image_bytes)
-    response.raise_for_status()
-    return response.json()
-
-def extract_visual_cues_from_vision(vision_result, page_number):
-    # Example: Detect gray fills, checkmarks, hand-drawn marks
-    cues = []
-    # This is a placeholder. You need to parse vision_result for your cues.
-    # For example, if vision_result['objects'] contains a 'checkmark' or color info for gray fill
-    # cues.append({"page_number": page_number, "row_index": ..., "column_index": ..., "cue_type": "gray_fill"})
-    return cues
-
-def convert_pdf_to_images(pdf_bytes):
-    images = convert_from_bytes(pdf_bytes)
-    return images
-
 def BlobTriggerContosoPDFLayoutsDocIntelligence(myblob: func.InputStream):
     logging.info(f"Python blob trigger function processed blob\n"
                  f"Name: {myblob.name}\n"
@@ -212,26 +176,9 @@ def BlobTriggerContosoPDFLayoutsDocIntelligence(myblob: func.InputStream):
         logging.error(f"Error analyzing PDF: {e}")
         return
 
-    # --- Step: Convert PDF to image and call Azure AI Vision ---
-    visual_cues = []
-    try:
-        images = convert_pdf_to_images(pdf_bytes)
-        vision_key = os.getenv("VISION_API_KEY")
-        vision_endpoint = os.getenv("VISION_API_ENDPOINT")
-        for page_num, image in enumerate(images, start=1):
-            img_bytes_io = BytesIO()
-            image.save(img_bytes_io, format='JPEG')
-            img_bytes = img_bytes_io.getvalue()
-            vision_result = call_vision_api(img_bytes, vision_key, vision_endpoint)
-            cues = extract_visual_cues_from_vision(vision_result, page_num)
-            visual_cues.extend(cues)
-        logging.info(f"Visual cues extracted: {visual_cues}")
-    except Exception as e:
-        logging.error(f"Error processing visual cues with AI Vision: {e}")
-
     try:
-        layout_data = extract_layout_data(result, visual_cues)
-        logging.info("Successfully extracted and merged layout data.")
+        layout_data = extract_layout_data(result)
+        logging.info("Successfully extracted layout data.")
     except Exception as e:
         logging.error(f"Error extracting layout data: {e}")
         return

terraform-infrastructure/README.md

@@ -5,7 +5,7 @@ Costa Rica
 [![GitHub](https://img.shields.io/badge/--181717?logo=github&logoColor=ffffff)](https://github.com/)
 [brown9804](https://github.com/brown9804)
 
-Last updated: 2025-07-21
+Last updated: 2025-07-16
 
 ----------
 
@@ -109,7 +109,7 @@ graph TD;
 
 <!-- START BADGE -->
 <div align="center">
-  <img src="https://img.shields.io/badge/Total%20views-180-limegreen" alt="Total views">
-  <p>Refresh Date: 2025-07-21</p>
+  <img src="https://img.shields.io/badge/Total%20views-55-limegreen" alt="Total views">
+  <p>Refresh Date: 2025-07-16</p>
 </div>
 <!-- END BADGE -->

terraform-infrastructure/main.tf

@@ -289,7 +289,6 @@ resource "azurerm_role_assignment" "contributor" {
   ]
 }
 
-
 # Azure Form Recognizer (Document Intelligence)
 resource "azurerm_cognitive_account" "form_recognizer" {
   name                = var.form_recognizer_name
@@ -300,27 +299,12 @@ resource "azurerm_cognitive_account" "form_recognizer" {
 
   depends_on = [azurerm_resource_group.rg]
 
+  # Output the Form Recognizer name
   provisioner "local-exec" {
     command = "echo Form Recognizer: ${self.name}"
   }
 }
 
-# Azure AI Vision (Cognitive Services)
-resource "azurerm_cognitive_account" "ai_vision" {
-  name                = var.ai_vision_name
-  location            = azurerm_resource_group.rg.location
-  resource_group_name = azurerm_resource_group.rg.name
-  kind                = "CognitiveServices"
-  sku_name            = var.ai_vision_sku
-  tags                = var.ai_vision_tags
-
-  depends_on = [azurerm_resource_group.rg]
-
-  provisioner "local-exec" {
-    command = "echo AI Vision: ${self.name}"
-  }
-}
-
 # We need to assign custom or built-in Cosmos DB SQL roles 
 # (like Cosmos DB Built-in Data Reader, etc.) at the data plane level, 
 # which is not currently supported directly in Terraform as of now.
@@ -389,10 +373,6 @@ resource "azurerm_linux_function_app" "function_app" {
 
     "APPINSIGHTS_INSTRUMENTATIONKEY"        = azurerm_application_insights.appinsights.instrumentation_key
     "APPLICATIONINSIGHTS_CONNECTION_STRING" = azurerm_application_insights.appinsights.connection_string
-
-    # Azure AI Vision settings
-    "VISION_API_ENDPOINT" = azurerm_cognitive_account.ai_vision.endpoint
-    "VISION_API_KEY"      = azurerm_cognitive_account.ai_vision.primary_access_key
   }
 
   depends_on = [

terraform-infrastructure/terraform.tfvars

@@ -1,30 +1,21 @@
 # Sample values 
-subscription_id     = "407f4106-0fd3-42e0-9348-3686dd1e7347"                                        # "your-subscription_id"
-resource_group_name = "RG-PDFLayout-Processing-DocIntelligence" # "your-resource-group-name"
-location            = "West US"                                 # "your-location"
+subscription_id       = "" # "your-subscription_id"
+resource_group_name   = "RG-PDFLayout-Processing-DocIntelligence" # "your-resource-group-name"
+location              = "West US" # "your-location"
 # Storage Account
-storage_account_name         = "storageaccbrownpdfix2" # "your-storage-account-name"
+storage_account_name  = "storageaccbrownpdfix2" # "your-storage-account-name"
 storage_account_name_runtime = "runtimestorebrownix2"  # "your-runtime-storage-account-name"
 # Function App
-function_app_name = "fapdfbrownix2" # "your-function-app-name"
+function_app_name     = "fapdfbrownix2" # "your-function-app-name"
 # App Service Plan
 app_service_plan_name = "asppdfbrownix2" # "your-app-service-plan-name"
 # Application Insights
-app_insights_name = "apppdfbrownix2" # "your-app-insights-name"
+app_insights_name     = "apppdfbrownix2" # "your-app-insights-name"
 # Log Analytics Workspace
 log_analytics_workspace_name = "logwspdfbrownix2" # "your-log-analytics-workspace-name"
 # Key Vault
-key_vault_name = "kvpdfrbrownrix2" # "your-key-vault-name"
+key_vault_name        = "kvpdfrbrownix2" # "your-key-vault-name"
 # CosmosDB
 cosmosdb_account_name = "cosmospdfbrownix2" # "your-cosmosdb-account-name"
 # Form Recognizer -> Document Intelligence 
-form_recognizer_name = "docintelligt01ix2" # "your-document-intelligence-name"
-
-# AI Vision Service
-ai_vision_name = "aivisionpdfrbrownix2" # "your-ai-vision-name"
-ai_vision_sku  = "S0"
-ai_vision_tags = {
-  Environment = "Development"
-  Project     = "PDF Processing"
-  Service     = "AI Vision"
-}
+form_recognizer_name  = "docintelligt01ix2" # "your-document-intelligence-name"

terraform-infrastructure/variables.tf

@@ -48,26 +48,6 @@ variable "key_vault_name" {
   description = "The name of the Key Vault"
   type        = string
 }
-
-variable "ai_vision_name" {
-  description = "The name of the AI Vision Cognitive Services account"
-  type        = string
-}
-
-variable "ai_vision_sku" {
-  description = "The SKU of the AI Vision Cognitive Services account"
-  type        = string
-  default     = "S0"
-}
-
-variable "ai_vision_tags" {
-  description = "Tags to be applied to the AI Vision resource"
-  type        = map(string)
-  default     = {
-    Environment = "Development"
-    Service     = "AI Vision"
-  }
-}
 variable "cosmosdb_account_name" {
   description = "The name of the CosmosDB account."
   type        = string