add new version with inference client and fixes to datamodel

app.py

@@ -10,14 +10,12 @@ logger = logging.getLogger(__name__)
 
 app = Flask(__name__)
 
-# Configuration from environment variables
 CLIENT_ID = os.getenv("MELDRX_CLIENT_ID", "04bdc9f9a23d488a868b93d594ee5a4a")
 CLIENT_SECRET = os.getenv("MELDRX_CLIENT_SECRET", None)
 WORKSPACE_ID = os.getenv("MELDRX_WORKSPACE_ID", "09ed4f76-b5ac-42bf-92d5-496933203dbe")
 SPACE_URL = os.getenv("SPACE_URL", "https://multitransformer-tonic-discharge-guard.hf.space")
 REDIRECT_URI = f"{SPACE_URL}/auth/callback"
 
-# Initialize MeldRx API
 meldrx_api = MeldRxAPI(
     client_id=CLIENT_ID,
     client_secret=CLIENT_SECRET,
@@ -66,21 +64,23 @@ def one_click():
         last_name = request.form.get('last_name', '').strip()
         action = request.form.get('action', '')
 
-        pdf_path, status, display_summary = generate_discharge_paper_one_click(
+        pdf_path, status, basic_summary, ai_summary = generate_discharge_paper_one_click(
             meldrx_api, patient_id, first_name, last_name
         )
 
-        if action == "Display Summary" and display_summary:
+        if action == "Display Summary":
             return render_template('oneclick.html', 
-                                status=status, 
-                                summary=display_summary.replace('\n', '<br>'))
+                                status=status,
+                                basic_summary=basic_summary.replace('\n', '<br>') if basic_summary else None,
+                                ai_summary=ai_summary.replace('\n', '<br>') if ai_summary else None)
         elif action == "Generate PDF" and pdf_path:
             return send_file(pdf_path, 
                            as_attachment=True, 
                            download_name=f"discharge_summary_{patient_id or 'patient'}.pdf")
         return render_template('oneclick.html', 
-                            status=status, 
-                            summary=display_summary.replace('\n', '<br>') if display_summary else None)
+                            status=status,
+                            basic_summary=basic_summary.replace('\n', '<br>') if basic_summary else None,
+                            ai_summary=ai_summary.replace('\n', '<br>') if ai_summary else None)
 
     return render_template('oneclick.html')
 

notes.py

@@ -0,0 +1,221 @@
+# app.py
+from flask import Flask, render_template, request, send_file, redirect, url_for
+import os
+import logging
+from utils.meldrx import MeldRxAPI
+from utils.oneclick import generate_discharge_paper_one_click
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = Flask(__name__)
+
+# Configuration from environment variables
+CLIENT_ID = os.getenv("MELDRX_CLIENT_ID", "04bdc9f9a23d488a868b93d594ee5a4a")
+CLIENT_SECRET = os.getenv("MELDRX_CLIENT_SECRET", None)
+WORKSPACE_ID = os.getenv("MELDRX_WORKSPACE_ID", "09ed4f76-b5ac-42bf-92d5-496933203dbe")
+SPACE_URL = os.getenv("SPACE_URL", "https://multitransformer-tonic-discharge-guard.hf.space")
+REDIRECT_URI = f"{SPACE_URL}/auth/callback"
+
+# Initialize MeldRx API
+meldrx_api = MeldRxAPI(
+    client_id=CLIENT_ID,
+    client_secret=CLIENT_SECRET,
+    workspace_id=WORKSPACE_ID,
+    redirect_uri=REDIRECT_URI
+)
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/auth', methods=['GET', 'POST'])
+def auth():
+    if request.method == 'POST':
+        auth_code = request.form.get('auth_code')
+        if auth_code and meldrx_api.authenticate_with_code(auth_code):
+            return redirect(url_for('dashboard'))
+        return render_template('auth.html', auth_url=meldrx_api.get_authorization_url(), auth_result="Authentication failed")
+    return render_template('auth.html', auth_url=meldrx_api.get_authorization_url())
+
+@app.route('/auth/callback', methods=['GET'])
+def auth_callback():
+    auth_code = request.args.get('code')
+    if auth_code and meldrx_api.authenticate_with_code(auth_code):
+        return redirect(url_for('dashboard'))
+    return render_template('auth.html', auth_url=meldrx_api.get_authorization_url(), auth_result="Callback failed")
+
+@app.route('/dashboard', methods=['GET'])
+def dashboard():
+    if not meldrx_api.access_token:
+        return redirect(url_for('auth'))
+    patients_data = meldrx_api.get_patients()
+    if not patients_data or "entry" not in patients_data:
+        return render_template('dashboard.html', error="Failed to fetch patient data")
+    patients = [entry['resource'] for entry in patients_data.get('entry', [])]
+    return render_template('dashboard.html', patients=patients, authenticated=True)
+
+@app.route('/oneclick', methods=['GET', 'POST'])
+def one_click():
+    if not meldrx_api.access_token:
+        return redirect(url_for('auth'))
+    
+    if request.method == 'POST':
+        patient_id = request.form.get('patient_id', '').strip()
+        first_name = request.form.get('first_name', '').strip()
+        last_name = request.form.get('last_name', '').strip()
+        action = request.form.get('action', '')
+
+        pdf_path, status, display_summary = generate_discharge_paper_one_click(
+            meldrx_api, patient_id, first_name, last_name
+        )
+
+        if action == "Display Summary" and display_summary:
+            return render_template('oneclick.html', 
+                                status=status, 
+                                summary=display_summary.replace('\n', '<br>'))
+        elif action == "Generate PDF" and pdf_path:
+            return send_file(pdf_path, 
+                           as_attachment=True, 
+                           download_name=f"discharge_summary_{patient_id or 'patient'}.pdf")
+        return render_template('oneclick.html', 
+                            status=status, 
+                            summary=display_summary.replace('\n', '<br>') if display_summary else None)
+
+    return render_template('oneclick.html')
+
+if __name__ == '__main__':
+    port = int(os.getenv("PORT", 7860))
+    app.run(debug=False, host='0.0.0.0', port=port)
+
+
+# utils/oneclick.py
+from typing import Tuple, Optional
+from .meldrx import MeldRxAPI
+from .responseparser import PatientDataExtractor
+from .pdfutils import PDFGenerator
+import logging
+import json
+
+logger = logging.getLogger(__name__)
+
+def generate_discharge_paper_one_click(
+    api: MeldRxAPI,
+    patient_id: str = "",
+    first_name: str = "",
+    last_name: str = ""
+) -> Tuple[Optional[str], str, Optional[str]]:
+    """
+    Generate a discharge summary PDF and upload it to MeldRx patient data.
+    
+    Args:
+        api: Initialized MeldRxAPI instance
+        patient_id: Optional patient ID filter
+        first_name: Optional first name filter
+        last_name: Optional last name filter
+    
+    Returns:
+        Tuple of (pdf_path, status_message, display_summary)
+    """
+    try:
+        # Get patient data from MeldRx API
+        patients_data = api.get_patients()
+        if not patients_data or "entry" not in patients_data:
+            return None, "Failed to fetch patient data", None
+
+        # Create PatientDataExtractor instance
+        extractor = PatientDataExtractor(patients_data, "json")
+        
+        # Filter patients based on input
+        matching_patients = []
+        matching_indices = []
+        for i in range(len(extractor.patients)):
+            extractor.set_patient_by_index(i)
+            patient_data = extractor.get_patient_dict()
+            
+            if (not patient_id or patient_data["id"] == patient_id) and \
+               (not first_name or patient_data["first_name"].lower() == first_name.lower()) and \
+               (not last_name or patient_data["last_name"].lower() == last_name.lower()):
+                matching_patients.append(patient_data)
+                matching_indices.append(i)
+
+        if not matching_patients:
+            return None, "No matching patients found", None
+        
+        # Use the first matching patient
+        patient_data = matching_patients[0]
+        patient_index = matching_indices[0]
+        extractor.set_patient_by_index(patient_index)
+        
+        # Format the discharge summary text
+        summary_text = format_discharge_summary(patient_data)
+        
+        # Generate PDF
+        pdf_gen = PDFGenerator()
+        filename = f"discharge_{patient_data['id'] or 'summary'}_{patient_data['last_name']}.pdf"
+        pdf_path = pdf_gen.generate_pdf_from_text(summary_text, filename)
+        
+        # Prepare and upload discharge summary to MeldRx
+        if pdf_path:
+            # Convert summary to escaped JSON
+            discharge_summary_json = json.dumps(summary_text)
+            
+            # Get the original patient resource
+            patient_resource = extractor.patients[patient_index]
+            
+            # Add discharge_summary as an extension
+            if "extension" not in patient_resource:
+                patient_resource["extension"] = []
+            
+            patient_resource["extension"].append({
+                "url": "http://example.com/fhir/StructureDefinition/discharge-summary",
+                "valueString": discharge_summary_json
+            })
+            
+            # Update the patient in MeldRx
+            update_success = api.update_fhir_patient(patient_data["id"], patient_resource)
+            
+            status_message = "Discharge summary generated and uploaded successfully" if update_success \
+                else "Discharge summary generated but failed to upload to MeldRx"
+            
+            return pdf_path, status_message, summary_text
+        
+        return None, "Failed to generate PDF", summary_text
+
+    except Exception as e:
+        logger.error(f"Error in one-click discharge generation: {str(e)}")
+        return None, f"Error: {str(e)}", None
+
+def format_discharge_summary(patient_data: dict) -> str:
+    """Format patient data into a discharge summary text."""
+    summary = [
+        "DISCHARGE SUMMARY",
+        "",
+        "PATIENT INFORMATION",
+        f"Name: {patient_data['name_prefix']} {patient_data['first_name']} {patient_data['last_name']}",
+        f"Date of Birth: {patient_data['dob']}",
+        f"Age: {patient_data['age']}",
+        f"Gender: {patient_data['sex']}",
+        f"Patient ID: {patient_data['id']}",
+        "",
+        "CONTACT INFORMATION",
+        f"Address: {patient_data['address']}",
+        f"City: {patient_data['city']}, {patient_data['state']} {patient_data['zip_code']}",
+        f"Phone: {patient_data['phone']}",
+        "",
+        "ADMISSION INFORMATION",
+        f"Admission Date: {patient_data['admission_date']}",
+        f"Discharge Date: {patient_data['discharge_date']}",
+        f"Diagnosis: {patient_data['diagnosis']}",
+        "",
+        "MEDICATIONS",
+        f"{patient_data['medications']}",
+        "",
+        "PHYSICIAN INFORMATION",
+        f"Physician: Dr. {patient_data['doctor_first_name']} {patient_data['doctor_last_name']}",
+        f"Hospital: {patient_data['hospital_name']}",
+        f"Address: {patient_data['doctor_address']}",
+        f"City: {patient_data['doctor_city']}, {patient_data['doctor_state']} {patient_data['doctor_zip']}",
+    ]
+    
+    return "\n".join(line for line in summary if line.strip() or line == "")

templates/oneclick.html

@@ -13,10 +13,17 @@
 <div class="status-message">{{ status }}</div>
 {% endif %}
 
-{% if summary %}
+{% if basic_summary %}
 <div class="summary-container">
-    <h3>Discharge Summary Preview</h3>
-    <div class="summary-content">{{ summary | safe }}</div>
+    <h3>Basic Discharge Summary Preview</h3>
+    <div class="summary-content">{{ basic_summary | safe }}</div>
+</div>
+{% endif %}
+
+{% if ai_summary %}
+<div class="summary-container">
+    <h3>AI-Generated Discharge Summary Preview</h3>
+    <div class="summary-content">{{ ai_summary | safe }}</div>
 </div>
 {% endif %}
 

utils/oneclick.py

@@ -1,80 +1,152 @@
 # utils/oneclick.py
-from typing import Tuple, Optional
+from typing import Tuple, Optional, Dict
 from .meldrx import MeldRxAPI
 from .responseparser import PatientDataExtractor
 from .pdfutils import PDFGenerator
 import logging
+from huggingface_hub import InferenceClient
 
 logger = logging.getLogger(__name__)
 
+HF_TOKEN = os.getenv("HF_TOKEN")
+if not HF_TOKEN:
+    raise ValueError("HF_TOKEN environment variable not set.")
+client = InferenceClient(api_key=HF_TOKEN)client = InferenceClient()  # Initialize the xAI client (adjust initialization as needed)
+MODEL_NAME = "meta-llama/Llama-3.3-70B-Instruct"
+
+def generate_ai_discharge_summary(patient_dict: Dict[str, str]) -> Optional[str]:
+    """Generate a discharge summary using AI based on extracted patient data."""
+    try:
+        # Use the formatted summary as input
+        formatted_summary = format_discharge_summary(patient_dict)
+        
+        logger.info("Generating AI discharge summary with patient info: %s", formatted_summary)
+
+        messages = [
+            {
+                "role": "assistant",
+                "content": (
+                    "You are a senior medical practitioner tasked with creating discharge summaries. "
+                    "Generate a complete discharge summary based on the provided patient information."
+                )
+            },
+            {"role": "user", "content": formatted_summary}
+        ]
+
+        stream = client.chat.completions.create(
+            model=MODEL_NAME,
+            messages=messages,
+            temperature=0.4,
+            max_tokens=3584,
+            top_p=0.7,
+            stream=True
+        )
+
+        discharge_summary = ""
+        for chunk in stream:
+            content = chunk.choices[0].delta.content
+            if content:
+                discharge_summary += content
+
+        logger.info("AI discharge summary generated successfully")
+        return discharge_summary.strip()
+
+    except Exception as e:
+        logger.error(f"Error generating AI discharge summary: {str(e)}", exc_info=True)
+        return None
+
 def generate_discharge_paper_one_click(
     api: MeldRxAPI,
     patient_id: str = "",
     first_name: str = "",
     last_name: str = ""
-) -> Tuple[Optional[str], str, Optional[str]]:
+) -> Tuple[Optional[str], str, Optional[str], Optional[str]]:
     """
     Generate a discharge summary PDF with one click using MeldRx API data.
     
-    Args:
-        api: Initialized MeldRxAPI instance
-        patient_id: Optional patient ID filter
-        first_name: Optional first name filter
-        last_name: Optional last name filter
-    
     Returns:
-        Tuple of (pdf_path, status_message, display_summary)
+        Tuple of (pdf_path, status_message, basic_summary, ai_summary)
     """
     try:
-        # Get patient data from MeldRx API
         patients_data = api.get_patients()
         if not patients_data or "entry" not in patients_data:
-            return None, "Failed to fetch patient data", None
+            return None, "Failed to fetch patient data from MeldRx API", None, None
 
-        # Create PatientDataExtractor instance
         extractor = PatientDataExtractor(patients_data, "json")
         
-        # Filter patients based on input
+        if not extractor.patients:
+            return None, "No patients found in the data", None, None
+
         matching_patients = []
         for i in range(len(extractor.patients)):
             extractor.set_patient_by_index(i)
             patient_data = extractor.get_patient_dict()
             
-            if (not patient_id or patient_data["id"] == patient_id) and \
-               (not first_name or patient_data["first_name"].lower() == first_name.lower()) and \
-               (not last_name or patient_data["last_name"].lower() == last_name.lower()):
+            patient_data.setdefault('id', 'unknown')
+            patient_data.setdefault('first_name', '')
+            patient_data.setdefault('last_name', '')
+            
+            if (not patient_id or patient_data.get("id", "") == patient_id) and \
+               (not first_name or patient_data.get("first_name", "").lower() == first_name.lower()) and \
+               (not last_name or patient_data.get("last_name", "").lower() == last_name.lower()):
                 matching_patients.append(patient_data)
 
         if not matching_patients:
-            return None, "No matching patients found", None
+            return None, "No matching patients found with the provided criteria", None, None
         
-        # Use the first matching patient
         patient_data = matching_patients[0]
-        extractor.set_patient_by_index(0)  # Reset to first patient for consistency
+        extractor.set_patient_by_index(0)
         
-        # Format the discharge summary text
-        summary_text = format_discharge_summary(patient_data)
+        # Generate both basic and AI summaries
+        basic_summary = format_discharge_summary(patient_data)
+        ai_summary = generate_ai_discharge_summary(patient_data)
         
-        # Generate PDF
+        if not ai_summary:
+            return None, "Failed to generate AI summary", basic_summary, None
+            
         pdf_gen = PDFGenerator()
-        filename = f"discharge_{patient_data['id'] or 'summary'}_{patient_data['last_name']}.pdf"
-        pdf_path = pdf_gen.generate_pdf_from_text(summary_text, filename)
+        filename = f"discharge_{patient_data.get('id', 'unknown')}_{patient_data.get('last_name', 'patient')}.pdf"
+        pdf_path = pdf_gen.generate_pdf_from_text(ai_summary, filename)
         
         if pdf_path:
-            return pdf_path, "Discharge summary generated successfully", summary_text
-        return None, "Failed to generate PDF", summary_text
+            return pdf_path, "Discharge summary generated successfully", basic_summary, ai_summary
+        return None, "Failed to generate PDF file", basic_summary, ai_summary
 
     except Exception as e:
-        logger.error(f"Error in one-click discharge generation: {str(e)}")
-        return None, f"Error: {str(e)}", None
+        logger.error(f"Error in one-click discharge generation: {str(e)}", exc_info=True)
+        return None, f"Error generating discharge summary: {str(e)}", None, None
 
 def format_discharge_summary(patient_data: dict) -> str:
     """Format patient data into a discharge summary text."""
+    patient_data.setdefault('name_prefix', '')
+    patient_data.setdefault('first_name', '')
+    patient_data.setdefault('last_name', '')
+    patient_data.setdefault('dob', 'Unknown')
+    patient_data.setdefault('age', 'Unknown')
+    patient_data.setdefault('sex', 'Unknown')
+    patient_data.setdefault('id', 'Unknown')
+    patient_data.setdefault('address', 'Unknown')
+    patient_data.setdefault('city', 'Unknown')
+    patient_data.setdefault('state', 'Unknown')
+    patient_data.setdefault('zip_code', 'Unknown')
+    patient_data.setdefault('phone', 'Unknown')
+    patient_data.setdefault('admission_date', 'Unknown')
+    patient_data.setdefault('discharge_date', 'Unknown')
+    patient_data.setdefault('diagnosis', 'Unknown')
+    patient_data.setdefault('medications', 'None specified')
+    patient_data.setdefault('doctor_first_name', 'Unknown')
+    patient_data.setdefault('doctor_last_name', 'Unknown')
+    patient_data.setdefault('hospital_name', 'Unknown')
+    patient_data.setdefault('doctor_address', 'Unknown')
+    patient_data.setdefault('doctor_city', 'Unknown')
+    patient_data.setdefault('doctor_state', 'Unknown')
+    patient_data.setdefault('doctor_zip', 'Unknown')
+
     summary = [
         "DISCHARGE SUMMARY",
         "",
         "PATIENT INFORMATION",
-        f"Name: {patient_data['name_prefix']} {patient_data['first_name']} {patient_data['last_name']}",
+        f"Name: {patient_data['name_prefix']} {patient_data['first_name']} {patient_data['last_name']}".strip(),
         f"Date of Birth: {patient_data['dob']}",
         f"Age: {patient_data['age']}",
         f"Gender: {patient_data['sex']}",
@@ -94,7 +166,7 @@ def format_discharge_summary(patient_data: dict) -> str:
         f"{patient_data['medications']}",
         "",
         "PHYSICIAN INFORMATION",
-        f"Physician: Dr. {patient_data['doctor_first_name']} {patient_data['doctor_last_name']}",
+        f"Physician: Dr. {patient_data['doctor_first_name']} {patient_data['doctor_last_name']}".strip(),
         f"Hospital: {patient_data['hospital_name']}",
         f"Address: {patient_data['doctor_address']}",
         f"City: {patient_data['doctor_city']}, {patient_data['doctor_state']} {patient_data['doctor_zip']}",