big changes to the application flow

utils/oneclick.py

@@ -1,5 +1,6 @@
 import os
 import logging
+import traceback
 from typing import Optional, Dict, Any, Tuple
 from huggingface_hub import InferenceClient
 from utils.meldrx import MeldRxAPI
@@ -7,7 +8,11 @@ from utils.pdfutils import PDFGenerator
 from utils.responseparser import PatientDataExtractor
 from datetime import datetime
 
-logging.basicConfig(level=logging.INFO)
+# 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")
@@ -17,6 +22,7 @@ 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"
@@ -30,6 +36,8 @@ def generate_ai_discharge_summary(patient_dict: Dict[str, str]) -> Optional[str]
             f"Discharge Instructions:\n[Generated based on available data]"
         )
 
+        logger.info("Generating AI discharge summary with patient info: %s", patient_info)
+
         messages = [
             {
                 "role": "assistant",
@@ -56,10 +64,11 @@ def generate_ai_discharge_summary(patient_dict: Dict[str, str]) -> Optional[str]
             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)}")
+        logger.error("Error generating AI discharge summary: %s\n%s", str(e), traceback.format_exc())
         return None
 
 def generate_discharge_paper_one_click(
@@ -68,15 +77,21 @@ def generate_discharge_paper_one_click(
     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 or "entry" not in patient_data:
-            return None, "Error: Failed to fetch patient data.", None
+        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()
 
@@ -104,6 +119,8 @@ def generate_discharge_paper_one_click(
         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
@@ -132,5 +149,5 @@ def generate_discharge_paper_one_click(
         return None, "Error: Failed to generate PDF.", display_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("Error in one-click discharge generation: %s\n%s", str(e), traceback.format_exc())
+        return None, f"Error: {str(e)}", None