Update app.py

app.py

@@ -5,6 +5,7 @@ from datetime import datetime, timedelta
 from simple_salesforce import Salesforce
 from transformers import pipeline
 from utils import fetch_salesforce_data, detect_anomalies, generate_pdf_report
+import os
 
 # Streamlit app configuration
 st.set_page_config(page_title="LabOps Dashboard", layout="wide")
@@ -14,9 +15,9 @@ st.set_page_config(page_title="LabOps Dashboard", layout="wide")
 def init_salesforce():
     try:
         return Salesforce(
-            username=st.secrets["sf_username"],
-            password=st.secrets["sf_password"],
-            security_token=st.secrets["sf_security_token"]
+            username=os.getenv("SF_USERNAME", st.secrets.get("sf_username")),
+            password=os.getenv("SF_PASSWORD", st.secrets.get("sf_password")),
+            security_token=os.getenv("SF_SECURITY_TOKEN", st.secrets.get("sf_security_token"))
         )
     except Exception as e:
         st.error(f"Failed to connect to Salesforce: {e}")
@@ -25,12 +26,16 @@ def init_salesforce():
 # Cache Hugging Face model
 @st.cache_resource
 def init_anomaly_detector():
-    return pipeline(
-        "text-classification",
-        model="distilbert-base-uncased",
-        tokenizer="distilbert-base-uncased",
-        clean_up_tokenization_spaces=True
-    )
+    try:
+        return pipeline(
+            "text-classification",
+            model="distilbert-base-uncased",
+            tokenizer="distilbert-base-uncased",
+            clean_up_tokenization_spaces=True
+        )
+    except Exception as e:
+        st.error(f"Failed to initialize anomaly detector: {e}")
+        return None
 
 # Initialize connections
 sf = init_salesforce()
@@ -53,8 +58,8 @@ def get_filtered_data(lab_site, equipment_type, date_start, date_end):
     return fetch_salesforce_data(sf, query)
 
 def main():
-    if sf is None:
-        st.error("Cannot proceed without Salesforce connection.")
+    if sf is None or anomaly_detector is None:
+        st.error("Cannot proceed without Salesforce connection or anomaly detector.")
         return
 
     st.title("Multi-Device LabOps Dashboard")
@@ -77,7 +82,8 @@ def main():
     date_start, date_end = date_range
 
     # Fetch and process data
-    data = get_filtered_data(lab_site, equipment_type, date_start, date_end)
+    with st.spinner("Fetching data..."):
+        data = get_filtered_data(lab_site, equipment_type, date_start, date_end)
     if not data:
         st.warning("No data available for the selected filters.")
         return
@@ -147,12 +153,13 @@ def main():
 
     # Export PDF
     if st.button("Export PDF Report"):
-        try:
-            pdf_file = generate_pdf_report(df, lab_site, equipment_type, [date_start, date_end])
-            with open(pdf_file, "rb") as f:
-                st.download_button("Download PDF", f, file_name="LabOps_Report.pdf", mime="application/pdf")
-        except Exception as e:
-            st.error(f"Failed to generate PDF: {e}")
+        with st.spinner("Generating PDF..."):
+            try:
+                pdf_file = generate_pdf_report(df, lab_site, equipment_type, [date_start, date_end])
+                with open(pdf_file, "rb") as f:
+                    st.download_button("Download PDF", f, file_name="LabOps_Report.pdf", mime="application/pdf")
+            except Exception as e:
+                st.error(f"Failed to generate PDF: {e}")
 
 if __name__ == "__main__":
     main()