Update callbackmanager.py (#1)

- Update callbackmanager.py (a791755f777bb8de77d9d4e859c442022ff3f14b)

callbackmanager.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from meldrx import MeldRxAPI  
+from meldrx import MeldRxAPI
 import json
 import os
 import tempfile
@@ -14,6 +14,30 @@ logger = logging.getLogger(__name__)
 # Import PDF utilities
 from pdfutils import PDFGenerator, generate_discharge_summary
 
+# Import necessary libraries for new file types and AI analysis functions
+import pydicom  # For DICOM
+import hl7  # For HL7
+from xml.etree import ElementTree # For XML and CCDA
+from pypdf import PdfReader # For PDF
+import csv # For CSV
+# Assuming your AI analysis functions are in the same script or imported
+# For now, let's define placeholder AI analysis functions for Gradio context
+def analyze_dicom_file_with_ai(dicom_file):
+    return "DICOM Analysis Report (Placeholder - Real AI integration needed)"
+
+def analyze_hl7_file_with_ai(hl7_file):
+    return "HL7 Analysis Report (Placeholder - Real AI integration needed)"
+
+def analyze_cda_xml_file_with_ai(cda_xml_file):
+    return "CCDA/XML Analysis Report (Placeholder - Real AI integration needed)"
+
+def analyze_pdf_file_with_ai(pdf_file):
+    return "PDF Analysis Report (Placeholder - Real AI integration needed)"
+
+def analyze_csv_file_with_ai(csv_file):
+    return "CSV Analysis Report (Placeholder - Real AI integration needed)"
+
+
 class CallbackManager:
     def __init__(self, redirect_uri: str, client_secret: str = None):
         client_id = os.getenv("APPID")
@@ -42,7 +66,7 @@ class CallbackManager:
             if not self.access_token:
                 logger.warning("Not authenticated when getting patient data")
                 return "Not authenticated. Please provide a valid authorization code first."
-            
+
             # For demo purposes, if there's no actual API connected, return mock data
             # Remove this in production and use the real API call
             if not hasattr(self.api, 'get_patients') or self.api.get_patients is None:
@@ -101,7 +125,7 @@ class CallbackManager:
                     ]
                 }
                 return json.dumps(mock_data, indent=2)
-                
+
             # Real implementation with API call
             logger.info("Calling Meldrx API to get patients")
             patients = self.api.get_patients()
@@ -117,7 +141,7 @@ class CallbackManager:
         """Fetch patient documents from MeldRx"""
         if not self.access_token:
             return "Not authenticated. Please provide a valid authorization code first."
-        
+
         try:
             # This would call the actual MeldRx API to get documents for a specific patient
             # For demonstration, we'll return mock document data
@@ -139,7 +163,7 @@ class CallbackManager:
             ]
         except Exception as e:
             return f"Error retrieving patient documents: {str(e)}"
-        
+
 def display_form(
     first_name, last_name, middle_initial, dob, age, sex, address, city, state, zip_code,
     doctor_first_name, doctor_last_name, doctor_middle_initial, hospital_name, doctor_address,
@@ -173,10 +197,10 @@ def generate_pdf_from_form(
     diagnosis, procedures, medications, preparer_name, preparer_job_title
 ):
     """Generate a PDF discharge form using the provided data"""
-    
+
     # Create PDF generator
     pdf_gen = PDFGenerator()
-    
+
     # Format data for PDF generation
     patient_info = {
         "first_name": first_name,
@@ -190,7 +214,7 @@ def generate_pdf_from_form(
         "state": state,
         "zip": zip_code
     }
-    
+
     discharge_info = {
         "date_of_admission": admission_date,
         "date_of_discharge": discharge_date,
@@ -198,25 +222,25 @@ def generate_pdf_from_form(
         "mode_of_admission": admission_method,
         "discharge_against_advice": "Yes" if discharge_reason == "Discharge Against Advice" else "No"
     }
-    
+
     diagnosis_info = {
         "diagnosis": diagnosis,
         "operation_procedure": procedures,
         "treatment": "",  # Not collected in the form
         "follow_up": ""   # Not collected in the form
     }
-    
+
     medication_info = {
         "medications": [medications] if medications else [],
         "instructions": ""  # Not collected in the form
     }
-    
+
     prepared_by = {
         "name": preparer_name,
         "title": preparer_job_title,
         "signature": ""  # Not collected in the form
     }
-    
+
     # Generate PDF
     pdf_buffer = pdf_gen.generate_discharge_form(
         patient_info,
@@ -225,13 +249,13 @@ def generate_pdf_from_form(
         medication_info,
         prepared_by
     )
-    
+
     # Create temporary file to save the PDF
     temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.pdf')
     temp_file.write(pdf_buffer.read())
     temp_file_path = temp_file.name
     temp_file.close()
-    
+
     return temp_file_path
 
 def generate_pdf_from_meldrx(patient_data):
@@ -242,17 +266,17 @@ def generate_pdf_from_meldrx(patient_data):
             patient_data = json.loads(patient_data)
         except:
             return None, "Invalid patient data format"
-    
+
     if not patient_data:
         return None, "No patient data available"
-    
+
     try:
         # For demonstration, we'll use the first patient in the list if it's a list
         if isinstance(patient_data, list) and len(patient_data):
             patient = patient_data[0]
         else:
             patient = patient_data
-            
+
         # Extract patient info
         patient_info = {
             "name": f"{patient.get('name', {}).get('given', [''])[0]} {patient.get('name', {}).get('family', '')}",
@@ -261,7 +285,7 @@ def generate_pdf_from_meldrx(patient_data):
             "admission_date": datetime.now().strftime("%Y-%m-%d"),  # Mock data
             "physician": "Dr. Provider"  # Mock data
         }
-        
+
         # Mock LLM-generated content
         llm_content = {
             "diagnosis": "Diagnosis information would be generated by LLM",
@@ -270,16 +294,35 @@ def generate_pdf_from_meldrx(patient_data):
             "follow_up": "Follow-up instructions would be generated by LLM",
             "special_instructions": "Special instructions would be generated by LLM"
         }
-        
+
         # Create discharge summary
         output_dir = tempfile.mkdtemp()
         pdf_path = generate_discharge_summary(patient_info, llm_content, output_dir)
-        
+
         return pdf_path, "PDF generated successfully"
-        
+
     except Exception as e:
         return None, f"Error generating PDF: {str(e)}"
 
+def generate_discharge_paper_one_click():
+    """One-click function to fetch patient data and generate discharge paper."""
+    patient_data_str = CALLBACK_MANAGER.get_patient_data()
+    if patient_data_str.startswith("Not authenticated") or patient_data_str.startswith("Failed") or patient_data_str.startswith("Error"):
+        return None, patient_data_str # Return error message if authentication or data fetch fails
+
+    try:
+        patient_data = json.loads(patient_data_str)
+        pdf_path, status_message = generate_pdf_from_meldrx(patient_data)
+        if pdf_path:
+            return pdf_path, status_message
+        else:
+            return None, status_message # Return status message if PDF generation fails
+    except json.JSONDecodeError:
+        return None, "Error: Patient data is not in valid JSON format."
+    except Exception as e:
+        return None, f"Error during discharge paper generation: {str(e)}"
+
+
 # Create a simplified interface to avoid complex component interactions
 CALLBACK_MANAGER = CallbackManager(
     redirect_uri="https://multitransformer-discharge-guard.hf.space/callback",
@@ -288,8 +331,8 @@ CALLBACK_MANAGER = CallbackManager(
 
 # Create the UI
 with gr.Blocks() as demo:
-    gr.Markdown("# Patient Discharge Form with MeldRx Integration")
-    
+    gr.Markdown("# Patient Discharge Form with MeldRx & Medical File Analysis")
+
     with gr.Tab("Authenticate with MeldRx"):
         gr.Markdown("## SMART on FHIR Authentication")
         auth_url_output = gr.Textbox(label="Authorization URL", value=CALLBACK_MANAGER.get_auth_url(), interactive=False)
@@ -297,41 +340,41 @@ with gr.Blocks() as demo:
         auth_code_input = gr.Textbox(label="Authorization Code")
         auth_submit = gr.Button("Submit Code")
         auth_result = gr.Textbox(label="Authentication Result")
-        
+
         patient_data_button = gr.Button("Fetch Patient Data")
         patient_data_output = gr.Textbox(label="Patient Data", lines=10)
-        
+
         # Add button to generate PDF from MeldRx data
         meldrx_pdf_button = gr.Button("Generate PDF from MeldRx Data")
         meldrx_pdf_status = gr.Textbox(label="PDF Generation Status")
         meldrx_pdf_download = gr.File(label="Download Generated PDF")
-        
+
         auth_submit.click(fn=CALLBACK_MANAGER.set_auth_code, inputs=auth_code_input, outputs=auth_result)
-    
+
     with gr.Tab("Patient Dashboard"):
         gr.Markdown("## Patient Data")
         dashboard_output = gr.HTML("<p>Fetch patient data from the Authentication tab first.</p>")
-        
+
         refresh_btn = gr.Button("Refresh Data")
-        
+
         # Simple function to update dashboard based on fetched data
         def update_dashboard():
             try:
                 data = CALLBACK_MANAGER.get_patient_data()
                 if data.startswith("Not authenticated") or data.startswith("Failed") or data.startswith("Error"):
                     return f"<p>{data}</p>"
-                    
+
                 try:
                     # Parse the data
                     patients_data = json.loads(data)
                     patients = []
-                    
+
                     # Extract patients from bundle
                     for entry in patients_data.get("entry", []):
                         resource = entry.get("resource", {})
                         if resource.get("resourceType") == "Patient":
                             patients.append(resource)
-                    
+
                     # Generate HTML for each patient
                     html = "<h3>Patients</h3>"
                     for patient in patients:
@@ -339,11 +382,11 @@ with gr.Blocks() as demo:
                         name = patient.get("name", [{}])[0]
                         given = " ".join(name.get("given", ["Unknown"]))
                         family = name.get("family", "Unknown")
-                        
+
                         # Extract other details
                         gender = patient.get("gender", "unknown").capitalize()
                         birth_date = patient.get("birthDate", "Unknown")
-                        
+
                         # Generate HTML card
                         html += f"""
                         <div style="border: 1px solid #ddd; padding: 10px; margin: 10px 0; border-radius: 5px;">
@@ -353,13 +396,13 @@ with gr.Blocks() as demo:
                             <p><strong>ID:</strong> {patient.get("id", "Unknown")}</p>
                         </div>
                         """
-                    
+
                     return html
                 except Exception as e:
                     return f"<p>Error parsing patient data: {str(e)}</p>"
             except Exception as e:
                 return f"<p>Error fetching patient data: {str(e)}</p>"
-    
+
     with gr.Tab("Discharge Form"):
         gr.Markdown("## Patient Details")
         with gr.Row():
@@ -404,16 +447,16 @@ with gr.Blocks() as demo:
         with gr.Row():
             preparer_name = gr.Textbox(label="Name")
             preparer_job_title = gr.Textbox(label="Job Title")
-        
+
         # Add buttons for both display form and generate PDF
         with gr.Row():
             submit_display = gr.Button("Display Form")
             submit_pdf = gr.Button("Generate PDF")
-        
+
         # Output areas
         form_output = gr.Markdown()
         pdf_output = gr.File(label="Download PDF")
-        
+
         # Connect the display form button
         submit_display.click(
             display_form,
@@ -426,7 +469,7 @@ with gr.Blocks() as demo:
             ],
             outputs=form_output
         )
-        
+
         # Connect the generate PDF button
         submit_pdf.click(
             generate_pdf_from_form,
@@ -439,28 +482,87 @@ with gr.Blocks() as demo:
             ],
             outputs=pdf_output
         )
-    
+
+    with gr.Tab("Medical File Analysis"):
+        gr.Markdown("## Analyze Medical Files with DocuNexus AI")
+        with gr.Column():
+            dicom_file = gr.File(file_types=['.dcm'], label="Upload DICOM File (.dcm)")
+            dicom_ai_output = gr.Textbox(label="DICOM Analysis Report", lines=5)
+            analyze_dicom_button = gr.Button("Analyze DICOM with AI")
+
+            hl7_file = gr.File(file_types=['.hl7'], label="Upload HL7 File (.hl7)")
+            hl7_ai_output = gr.Textbox(label="HL7 Analysis Report", lines=5)
+            analyze_hl7_button = gr.Button("Analyze HL7 with AI")
+
+            xml_file = gr.File(file_types=['.xml'], label="Upload XML File (.xml)")
+            xml_ai_output = gr.Textbox(label="XML Analysis Report", lines=5)
+            analyze_xml_button = gr.Button("Analyze XML with AI")
+
+            ccda_file = gr.File(file_types=['.xml', '.cda', '.ccd'], label="Upload CCDA File (.xml, .cda, .ccd)")
+            ccda_ai_output = gr.Textbox(label="CCDA Analysis Report", lines=5)
+            analyze_ccda_button = gr.Button("Analyze CCDA with AI")
+
+            ccd_file = gr.File(file_types=['.ccd'], label="Upload CCD File (.ccd)") # Redundant, as CCDA also handles .ccd, but kept for clarity
+            ccd_ai_output = gr.Textbox(label="CCD Analysis Report", lines=5) # Redundant
+            analyze_ccd_button = gr.Button("Analyze CCD with AI") # Redundant
+
+
+        # Connect AI Analysis Buttons (using placeholder functions for now)
+        analyze_dicom_button.click(
+            lambda file: analyze_dicom_file_with_ai(file.name) if file else "No DICOM file uploaded",
+            inputs=dicom_file, outputs=dicom_ai_output
+        )
+        analyze_hl7_button.click(
+            lambda file: analyze_hl7_file_with_ai(file.name) if file else "No HL7 file uploaded",
+            inputs=hl7_file, outputs=hl7_ai_output
+        )
+        analyze_xml_button.click(
+            lambda file: analyze_cda_xml_file_with_ai(file.name) if file else "No XML file uploaded", # Using CCDA/XML analyzer for generic XML for now
+            inputs=xml_file, outputs=xml_ai_output
+        )
+        analyze_ccda_button.click(
+            lambda file: analyze_cda_xml_file_with_ai(file.name) if file else "No CCDA file uploaded", # Using CCDA/XML analyzer
+            inputs=ccda_file, outputs=ccda_ai_output
+        )
+        analyze_ccd_button.click( # Redundant button, but kept for UI if needed
+            lambda file: analyze_cda_xml_file_with_ai(file.name) if file else "No CCD file uploaded", # Using CCDA/XML analyzer
+            inputs=ccd_file, outputs=ccd_ai_output
+        )
+
+    with gr.Tab("One-Click Discharge Paper"): # New Tab for One-Click Discharge Paper
+        gr.Markdown("## One-Click Medical Discharge Paper Generation")
+        one_click_pdf_button = gr.Button("Generate Discharge Paper (One-Click)")
+        one_click_pdf_status = gr.Textbox(label="Discharge Paper Generation Status")
+        one_click_pdf_download = gr.File(label="Download Discharge Paper")
+
+        one_click_pdf_button.click(
+            generate_discharge_paper_one_click,
+            inputs=[],
+            outputs=[one_click_pdf_download, one_click_pdf_status]
+        )
+
+
     # Connect the patient data buttons
     patient_data_button.click(
         fn=CALLBACK_MANAGER.get_patient_data,
         inputs=None,
         outputs=patient_data_output
     )
-    
+
     # Connect refresh button to update dashboard
     refresh_btn.click(
         fn=update_dashboard,
         inputs=None,
         outputs=dashboard_output
     )
-    
+
     # Add functionality for PDF generation from MeldRx data
     meldrx_pdf_button.click(
         fn=generate_pdf_from_meldrx,
         inputs=patient_data_output,
         outputs=[meldrx_pdf_download, meldrx_pdf_status]
     )
-    
+
     # Connect patient data updates to dashboard
     patient_data_button.click(
         fn=update_dashboard,