Update app.py

app.py

@@ -7,6 +7,26 @@ from reportlab.lib.pagesizes import letter
 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
 from reportlab.lib import colors
+from simple_salesforce import Salesforce
+import os
+from dotenv import load_dotenv
+import base64
+import io
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Salesforce credentials
+SF_USERNAME = os.getenv('SF_USERNAME')
+SF_PASSWORD = os.getenv('SF_PASSWORD')
+SF_SECURITY_TOKEN = os.getenv('SF_SECURITY_TOKEN')
+
+# Initialize Salesforce connection
+try:
+    sf = Salesforce(username=SF_USERNAME, password=SF_PASSWORD, security_token=SF_SECURITY_TOKEN)
+except Exception as e:
+    sf = None
+    print(f"Failed to connect to Salesforce: {str(e)}")
 
 # Load BLIP model and processor
 processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
@@ -70,13 +90,41 @@ def save_dpr_to_pdf(dpr_text, filename):
         
         # Build the PDF
         doc.build(flowables)
-        return f"PDF saved successfully as {filename}"
+        return f"PDF saved successfully as {filename}", filename
     except Exception as e:
-        return f"Error saving PDF: {str(e)}"
+        return f"Error saving PDF: {str(e)}", None
 
-# Function to generate the daily progress report (DPR) text and save as PDF
+# Function to upload a file to Salesforce as ContentVersion
+def upload_file_to_salesforce(file_path, filename, sf_connection, field_name):
+    try:
+        # Read file content and encode in base64
+        with open(file_path, 'rb') as f:
+            file_content = f.read()
+        file_content_b64 = base64.b64encode(file_content).decode('utf-8')
+        
+        # Create ContentVersion
+        content_version = sf_connection.ContentVersion.create({
+            'Title': filename,
+            'PathOnClient': filename,
+            'VersionData': file_content_b64,
+            'Description': f'Uploaded for {field_name}'
+        })
+        
+        # Get ContentDocumentId
+        content_version_id = content_version['id']
+        content_document = sf_connection.query(
+            f"SELECT ContentDocumentId FROM ContentVersion WHERE Id = '{content_version_id}'"
+        )
+        content_document_id = content_document['records'][0]['ContentDocumentId']
+        
+        return content_document_id, f"File {filename} uploaded successfully for {field_name}"
+    except Exception as e:
+        return None, f"Error uploading {filename} to Salesforce for {field_name}: {str(e)}"
+
+# Function to generate the daily progress report (DPR), save as PDF, and upload to Salesforce
 def generate_dpr(files):
     dpr_text = []
+    captions = []
     current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     
     # Add header to the DPR
@@ -85,13 +133,14 @@ def generate_dpr(files):
     # Process each uploaded file (image)
     for file in files:
         # Open the image from file path
-        image = Image.open(file.name)  # Using file.name for filepath
+        image = Image.open(file.name)
         
         if image.mode != "RGB":
             image = image.convert("RGB")
         
         # Dynamically generate a caption based on the image
         caption = generate_captions_from_image(image)
+        captions.append(caption)
         
         # Generate DPR section for this image with dynamic caption
         dpr_section = f"\nImage: {file.name}\nDescription: {caption}\n"
@@ -104,22 +153,73 @@ def generate_dpr(files):
     pdf_filename = f"DPR_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.pdf"
     
     # Save DPR text to PDF
-    pdf_result = save_dpr_to_pdf(dpr_output, pdf_filename)
+    pdf_result, pdf_filepath = save_dpr_to_pdf(dpr_output, pdf_filename)
+    
+    # Salesforce upload
+    salesforce_result = ""
+    if sf and pdf_filepath:
+        try:
+            # Create Daily_Progress_Reports__c record
+            report_description = "; ".join(captions)[:255]  # Concatenate captions, limit to 255 chars
+            dpr_record = sf.Daily_Progress_Reports__c.create({
+                'Report_Date__c': current_time,
+                'Report_Description__c': report_description
+            })
+            dpr_record_id = dpr_record['id']
+            salesforce_result += f"Created Daily_Progress_Reports__c record with ID: {dpr_record_id}\n"
+            
+            # Upload PDF to Salesforce for Report_PDF__c
+            pdf_content_document_id, pdf_upload_result = upload_file_to_salesforce(
+                pdf_filepath, pdf_filename, sf, 'Report_PDF__c'
+            )
+            salesforce_result += pdf_upload_result + "\n"
+            
+            # Link PDF to DPR record
+            if pdf_content_document_id:
+                sf.ContentDocumentLink.create({
+                    'ContentDocumentId': pdf_content_document_id,
+                    'LinkedEntityId': dpr_record_id,
+                    'ShareType': 'V'
+                })
+            
+            # Upload images to Salesforce for Site_Images__c
+            for file in files:
+                image_filename = os.path.basename(file.name)
+                image_content_document_id, image_upload_result = upload_file_to_salesforce(
+                    file.name, image_filename, sf, 'Site_Images__c'
+                )
+                salesforce_result += image_upload_result + "\n"
+                
+                # Link image to DPR record
+                if image_content_document_id:
+                    sf.ContentDocumentLink.create({
+                        'ContentDocumentId': image_content_document_id,
+                        'LinkedEntityId': dpr_record_id,
+                        'ShareType': 'V'
+                    })
+            
+        except Exception as e:
+            salesforce_result += f"Error interacting with Salesforce: {str(e)}\n"
+    else:
+        salesforce_result = "Salesforce connection not available or PDF generation failed.\n"
     
-    # Return the DPR text and the PDF file path for download
-    return dpr_output + f"\n\n{pdf_result}", pdf_filename
+    # Return DPR text, PDF file, and Salesforce upload status
+    return (
+        dpr_output + f"\n\n{pdf_result}\n\nSalesforce Upload Status:\n{salesforce_result}",
+        pdf_filepath
+    )
 
 # Gradio interface for uploading multiple files, displaying DPR, and downloading PDF
 iface = gr.Interface(
     fn=generate_dpr,
-    inputs=gr.Files(type="filepath", label="Upload Site Photos"),  # Handle batch upload of images
+    inputs=gr.Files(type="filepath", label="Upload Site Photos"),
     outputs=[
-        gr.Textbox(label="Daily Progress Report"),  # Display DPR text
-        gr.File(label="Download PDF")  # Provide PDF download link
+        gr.Textbox(label="Daily Progress Report"),
+        gr.File(label="Download PDF")
     ],
     title="Daily Progress Report Generator",
-    description="Upload up to 10 site photos. The AI model will dynamically detect construction activities, materials, and progress and generate a text-based Daily Progress Report (DPR). The DPR will also be saved as a PDF, which you can download.",
-    allow_flagging="never"  # Optional: Disable flagging
+    description="Upload up to 10 site photos. The AI model will generate a text-based Daily Progress Report (DPR), save it as a PDF, and upload the PDF to Report_PDF__c and images to Site_Images__c in Salesforce under Daily_Progress_Reports__c. Download the PDF locally if needed.",
+    allow_flagging="never"
 )
 
 if __name__ == "__main__":