add new version

app.py

@@ -1,3 +1,4 @@
+# app.py
 from flask import Flask, render_template, request, send_file, redirect, url_for
 import os
 import logging
@@ -32,10 +33,9 @@ def index():
 def auth():
     if request.method == 'POST':
         auth_code = request.form.get('auth_code')
-        if auth_code:
-            if 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")
+        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'])
@@ -59,10 +59,11 @@ def dashboard():
 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', '')
-        first_name = request.form.get('first_name', '')
-        last_name = request.form.get('last_name', '')
+        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(
@@ -70,10 +71,16 @@ def one_click():
         )
 
         if action == "Display Summary" and display_summary:
-            return render_template('oneclick.html', status=status, summary=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="discharge_summary.pdf")
-        return render_template('oneclick.html', status=status, summary=display_summary)
+            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')
 

old/app.py

@@ -0,0 +1,82 @@
+from flask import Flask, render_template, request, send_file, redirect, url_for
+import os
+import logging
+from utils.meldrx import MeldRxAPI
+from old.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:
+            if 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', '')
+        first_name = request.form.get('first_name', '')
+        last_name = request.form.get('last_name', '')
+        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)
+        elif action == "Generate PDF" and pdf_path:
+            return send_file(pdf_path, as_attachment=True, download_name="discharge_summary.pdf")
+        return render_template('oneclick.html', status=status, summary=display_summary)
+
+    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)

old/oneclick.py

@@ -0,0 +1,153 @@
+import os
+import logging
+import traceback
+from typing import Optional, Dict, Any, Tuple
+from huggingface_hub import InferenceClient
+from utils.meldrx import MeldRxAPI
+from utils.pdfutils import PDFGenerator
+from utils.responseparser import PatientDataExtractor
+from datetime import datetime
+
+# Set up logging with detailed output
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+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)
+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:
+        patient_info = (
+            f"Patient Name: {patient_dict['first_name']} {patient_dict['last_name']}\n"
+            f"Gender: {patient_dict['sex']}\n"
+            f"Age: {patient_dict['age']}\n"
+            f"Date of Birth: {patient_dict['dob']}\n"
+            f"Admission Date: {patient_dict['admission_date']}\n"
+            f"Discharge Date: {patient_dict['discharge_date']}\n\n"
+            f"Diagnosis:\n{patient_dict['diagnosis']}\n\n"
+            f"Medications:\n{patient_dict['medications']}\n\n"
+            f"Discharge Instructions:\n[Generated based on available data]"
+        )
+
+        logger.info("Generating AI discharge summary with patient info: %s", patient_info)
+
+        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": patient_info}
+        ]
+
+        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("Error generating AI discharge summary: %s\n%s", str(e), traceback.format_exc())
+        return None
+
+def generate_discharge_paper_one_click(
+    meldrx_api: MeldRxAPI,
+    patient_id: str = None,
+    first_name: str = None,
+    last_name: str = None
+) -> Tuple[Optional[str], str, Optional[str]]:
+    """Generate a discharge paper with AI content in one click."""
+    try:
+        if not meldrx_api.access_token:
+            if not meldrx_api.authenticate():
+                return None, "Error: Authentication failed. Please authenticate first.", None
+
+        logger.info("Fetching patient data from MeldRx API")
+        patient_data = meldrx_api.get_patients()
+        if not patient_data:
+            return None, "Error: No patient data returned from MeldRx API.", None
+        if "entry" not in patient_data:
+            logger.error("Invalid patient data format: %s", patient_data)
+            return None, "Error: Patient data is not in expected FHIR Bundle format.", None
+
+        logger.info("Extracting patient data")
+        extractor = PatientDataExtractor(patient_data, format_type="json")
+        patients = extractor.get_all_patients()
+
+        if not patients:
+            return None, "Error: No patients found in the workspace.", None
+
+        patient_dict = None
+        if patient_id:
+            for p in patients:
+                extractor.set_patient_by_index(patients.index(p))
+                if extractor.get_id() == patient_id:
+                    patient_dict = p
+                    break
+            if not patient_dict:
+                return None, f"Error: Patient with ID {patient_id} not found.", None
+        elif first_name and last_name:
+            patient_dict = next(
+                (p for p in patients if
+                 p["first_name"].lower() == first_name.lower() and
+                 p["last_name"].lower() == last_name.lower()),
+                None
+            )
+            if not patient_dict:
+                return None, f"Error: Patient with name {first_name} {last_name} not found.", None
+        else:
+            patient_dict = patients[0]
+
+        logger.info("Selected patient: %s %s", patient_dict['first_name'], patient_dict['last_name'])
+
+        ai_content = generate_ai_discharge_summary(patient_dict)
+        if not ai_content:
+            return None, "Error: Failed to generate AI discharge summary.", None
+
+        display_summary = (
+            f"<div style='color:#00FFFF; font-family: monospace;'>"
+            f"<strong>Discharge Summary Preview</strong><br>"
+            f"- Name: {patient_dict['first_name']} {patient_dict['last_name']}<br>"
+            f"- DOB: {patient_dict['dob']}, Age: {patient_dict['age']}, Sex: {patient_dict['sex']}<br>"
+            f"- Address: {patient_dict['address']}, {patient_dict['city']}, {patient_dict['state']} {patient_dict['zip_code']}<br>"
+            f"- Admission Date: {patient_dict['admission_date']}<br>"
+            f"- Discharge Date: {patient_dict['discharge_date']}<br>"
+            f"- Diagnosis: {patient_dict['diagnosis']}<br>"
+            f"- Medications: {patient_dict['medications']}<br>"
+            f"</div>"
+        )
+
+        pdf_generator = PDFGenerator()
+        pdf_path = pdf_generator.generate_pdf_from_text(
+            ai_content,
+            f"discharge_summary_{patient_id or 'unknown'}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"
+        )
+
+        if pdf_path:
+            return pdf_path, f"Success: Discharge paper generated for {patient_dict['first_name']} {patient_dict['last_name']}", display_summary
+        return None, "Error: Failed to generate PDF.", display_summary
+
+    except Exception as e:
+        logger.error("Error in one-click discharge generation: %s\n%s", str(e), traceback.format_exc())
+        return None, f"Error: {str(e)}", None

requirements.txt

@@ -11,4 +11,5 @@ pypdf
 flask
 gradio
 huggingface_hub
-lxml
+lxml
+reportlab

templates/oneclick.html

@@ -4,14 +4,39 @@
 <form method="POST">
     <input type="text" name="patient_id" placeholder="Patient ID (Optional)">
     <input type="text" name="first_name" placeholder="First Name (Optional)">
-    <input type="text" name="last_name" placeholder="Last Name (Optional)"><br>
+    <input type="text" name="last_name" placeholder="Last Name (Optional)"><br><br>
     <input type="submit" name="action" value="Display Summary" class="cyberpunk-button">
     <input type="submit" name="action" value="Generate PDF" class="cyberpunk-button">
 </form>
+
 {% if status %}
-<div>{{ status }}</div>
+<div class="status-message">{{ status }}</div>
 {% endif %}
+
 {% if summary %}
-<div>{{ summary | safe }}</div>
+<div class="summary-container">
+    <h3>Discharge Summary Preview</h3>
+    <div class="summary-content">{{ summary | safe }}</div>
+</div>
 {% endif %}
+
+<style>
+    .status-message {
+        margin: 20px 0;
+        padding: 10px;
+        border: 1px solid #ccc;
+        border-radius: 5px;
+    }
+    .summary-container {
+        margin: 20px 0;
+        padding: 15px;
+        border: 1px solid #ddd;
+        border-radius: 5px;
+        background-color: #f9f9f9;
+    }
+    .summary-content {
+        white-space: pre-wrap;
+        font-family: 'Courier New', Courier, monospace;
+    }
+</style>
 {% endblock %}

utils/oneclick.py

@@ -1,153 +1,103 @@
-import os
+# utils/oneclick.py
+from typing import Tuple, Optional
+from .meldrx import MeldRxAPI
+from .responseparser import PatientDataExtractor
+from .pdfutils import PDFGenerator
 import logging
-import traceback
-from typing import Optional, Dict, Any, Tuple
-from huggingface_hub import InferenceClient
-from utils.meldrx import MeldRxAPI
-from utils.pdfutils import PDFGenerator
-from utils.responseparser import PatientDataExtractor
-from datetime import datetime
 
-# Set up logging with detailed output
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-)
 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)
-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:
-        patient_info = (
-            f"Patient Name: {patient_dict['first_name']} {patient_dict['last_name']}\n"
-            f"Gender: {patient_dict['sex']}\n"
-            f"Age: {patient_dict['age']}\n"
-            f"Date of Birth: {patient_dict['dob']}\n"
-            f"Admission Date: {patient_dict['admission_date']}\n"
-            f"Discharge Date: {patient_dict['discharge_date']}\n\n"
-            f"Diagnosis:\n{patient_dict['diagnosis']}\n\n"
-            f"Medications:\n{patient_dict['medications']}\n\n"
-            f"Discharge Instructions:\n[Generated based on available data]"
-        )
-
-        logger.info("Generating AI discharge summary with patient info: %s", patient_info)
-
-        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": patient_info}
-        ]
-
-        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("Error generating AI discharge summary: %s\n%s", str(e), traceback.format_exc())
-        return None
-
 def generate_discharge_paper_one_click(
-    meldrx_api: MeldRxAPI,
-    patient_id: str = None,
-    first_name: str = None,
-    last_name: str = None
+    api: MeldRxAPI,
+    patient_id: str = "",
+    first_name: str = "",
+    last_name: str = ""
 ) -> Tuple[Optional[str], str, Optional[str]]:
-    """Generate a discharge paper with AI content in one click."""
+    """
+    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)
+    """
     try:
-        if not meldrx_api.access_token:
-            if not meldrx_api.authenticate():
-                return None, "Error: Authentication failed. Please authenticate first.", None
-
-        logger.info("Fetching patient data from MeldRx API")
-        patient_data = meldrx_api.get_patients()
-        if not patient_data:
-            return None, "Error: No patient data returned from MeldRx API.", None
-        if "entry" not in patient_data:
-            logger.error("Invalid patient data format: %s", patient_data)
-            return None, "Error: Patient data is not in expected FHIR Bundle format.", None
-
-        logger.info("Extracting patient data")
-        extractor = PatientDataExtractor(patient_data, format_type="json")
-        patients = extractor.get_all_patients()
-
-        if not patients:
-            return None, "Error: No patients found in the workspace.", None
-
-        patient_dict = None
-        if patient_id:
-            for p in patients:
-                extractor.set_patient_by_index(patients.index(p))
-                if extractor.get_id() == patient_id:
-                    patient_dict = p
-                    break
-            if not patient_dict:
-                return None, f"Error: Patient with ID {patient_id} not found.", None
-        elif first_name and last_name:
-            patient_dict = next(
-                (p for p in patients if
-                 p["first_name"].lower() == first_name.lower() and
-                 p["last_name"].lower() == last_name.lower()),
-                None
-            )
-            if not patient_dict:
-                return None, f"Error: Patient with name {first_name} {last_name} not found.", None
-        else:
-            patient_dict = patients[0]
-
-        logger.info("Selected patient: %s %s", patient_dict['first_name'], patient_dict['last_name'])
-
-        ai_content = generate_ai_discharge_summary(patient_dict)
-        if not ai_content:
-            return None, "Error: Failed to generate AI discharge summary.", None
-
-        display_summary = (
-            f"<div style='color:#00FFFF; font-family: monospace;'>"
-            f"<strong>Discharge Summary Preview</strong><br>"
-            f"- Name: {patient_dict['first_name']} {patient_dict['last_name']}<br>"
-            f"- DOB: {patient_dict['dob']}, Age: {patient_dict['age']}, Sex: {patient_dict['sex']}<br>"
-            f"- Address: {patient_dict['address']}, {patient_dict['city']}, {patient_dict['state']} {patient_dict['zip_code']}<br>"
-            f"- Admission Date: {patient_dict['admission_date']}<br>"
-            f"- Discharge Date: {patient_dict['discharge_date']}<br>"
-            f"- Diagnosis: {patient_dict['diagnosis']}<br>"
-            f"- Medications: {patient_dict['medications']}<br>"
-            f"</div>"
-        )
-
-        pdf_generator = PDFGenerator()
-        pdf_path = pdf_generator.generate_pdf_from_text(
-            ai_content,
-            f"discharge_summary_{patient_id or 'unknown'}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"
-        )
-
+        # 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 = []
+        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)
+
+        if not matching_patients:
+            return None, "No matching patients found", None
+        
+        # Use the first matching patient
+        patient_data = matching_patients[0]
+        extractor.set_patient_by_index(0)  # Reset to first patient for consistency
+        
+        # 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)
+        
         if pdf_path:
-            return pdf_path, f"Success: Discharge paper generated for {patient_dict['first_name']} {patient_dict['last_name']}", display_summary
-        return None, "Error: Failed to generate PDF.", display_summary
+            return pdf_path, "Discharge summary generated successfully", summary_text
+        return None, "Failed to generate PDF", summary_text
 
     except Exception as e:
-        logger.error("Error in one-click discharge generation: %s\n%s", str(e), traceback.format_exc())
-        return None, f"Error: {str(e)}", None
+        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 == "")