Update app.py

app.py

@@ -36,10 +36,15 @@ client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 try:
     nlp = spacy.load("en_core_web_sm")
 except OSError:
+    # Use Streamlit's message to inform the user instead of print
     st.write("Downloading en_core_web_sm spaCy model...")
     spacy.cli.download("en_core_web_sm")
     nlp = spacy.load("en_core_web_sm")
 
+# ---------------------- Streamlit Page Configuration ---------------------------
+# This must be the first Streamlit command in the script
+st.set_page_config(page_title="AI Clinical Intelligence Hub", layout="wide")
+
 # ---------------------- Base Classes and Schemas ---------------------------
 
 class ResearchInput(BaseModel):
@@ -244,8 +249,8 @@ class ClinicalRulesEngine:
         results = {}
         for rule_name, rule in self.rules.items():
             try:
-                # Evaluate the condition using the dataframe 'df'
                 # **Warning**: Using eval can be dangerous. Ensure that user inputs are sanitized.
+                # Here, we're restricting the environment by removing built-ins.
                 rule_matched = eval(rule.condition, {"__builtins__": None}, {"df": data})
                 results[rule_name] = {
                     "rule_matched": rule_matched,
@@ -280,10 +285,11 @@ class ClinicalKPIMonitoring:
             try:
                 # **Warning**: Using eval can be dangerous. Ensure that user inputs are sanitized.
                 kpi_value = eval(kpi.calculation, {"__builtins__": None}, {"df": data})
+                status = self.evaluate_threshold(kpi_value, kpi.threshold)
                 results[kpi_name] = {
                     "value": kpi_value,
                     "threshold": kpi.threshold,
-                    "status": self.evaluate_threshold(kpi_value, kpi.threshold)
+                    "status": status
                 }
             except Exception as e:
                 results[kpi_name] = {"error": str(e)}
@@ -448,7 +454,7 @@ class SimpleMedicalKnowledge(MedicalKnowledgeBase):
 
             response = f"**Based on your query:** {best_match_info}\n\n"
 
-            if "No abstracts found for this query on PubMed" not in pubmed_result:
+            if "No abstracts found for this query on PubMed." not in pubmed_result:
                 response += f"**PubMed Abstract:**\n{pubmed_result}"
             else:
                 response += f"{pubmed_result}"
@@ -468,7 +474,7 @@ class SimpleMedicalKnowledge(MedicalKnowledgeBase):
                     if st.button("Bad Result", key=f"bad_{feedback_key}"):
                         st.session_state[feedback_key]["feedback"] = "negative"
                         st.error("Thank you for the feedback!")
-            
+
             return response
         except Exception as e:
             return f"Medical Knowledge Search Failed: {e}"
@@ -652,7 +658,6 @@ class DataModelling:
 
 def main():
     """Main function to run the Streamlit app."""
-    st.set_page_config(page_title="AI Clinical Intelligence Hub", layout="wide")
     st.title("🏥 AI-Powered Clinical Intelligence Hub")
 
     # Initialize Session State
@@ -775,6 +780,8 @@ def dataset_metadata_section():
             "Size": f"{data.memory_usage().sum() / 1e6:.2f} MB"
         }
         st.json(metadata)
+        # Store the selected dataset key in session state for use in analysis
+        st.session_state.selected_data_key = selected_data_key
 
 def main_tabs_section():
     """Creates and manages the main tabs in the application."""