Update app.py

app.py

@@ -1,36 +1,95 @@
 import streamlit as st
 import pandas as pd
-from utils.load_data import load_logs
-from utils.visualize import plot_usage
-from utils.report import generate_pdf
-from models.anomaly import detect_anomalies
-from utils.amc import upcoming_amc_devices
+import plotly.express as px
+from datetime import datetime, timedelta
+from simple_salesforce import Salesforce
+from transformers import pipeline
+from reportlab.lib.pagesizes import letter
+from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph
+from reportlab.lib import colors
+from reportlab.lib.styles import getSampleStyleSheet
+from utils import fetch_salesforce_data, detect_anomalies, generate_pdf_report
 
+# Streamlit app configuration
 st.set_page_config(page_title="LabOps Dashboard", layout="wide")
-st.title("📊 Multi-Device LabOps Dashboard")
 
-uploaded_files = st.file_uploader("Upload Device Logs (CSV)", accept_multiple_files=True)
+# Salesforce authentication (replace with your credentials)
+sf = Salesforce(
+    username=st.secrets["sf_username"],
+    password=st.secrets["sf_password"],
+    security_token=st.secrets["sf_security_token"]
+)
 
-if uploaded_files:
-    df = load_logs(uploaded_files)
-    
-    st.subheader("📋 Uploaded Logs")
-    st.dataframe(df.head())
-
-    st.subheader("📈 Daily Usage Chart")
-    st.pyplot(plot_usage(df))
+# Initialize Hugging Face anomaly detection pipeline
+anomaly_detector = pipeline("text-classification", model="bert-base-uncased", tokenizer="bert-base-uncased")
 
-    st.subheader("🚨 Detected Anomalies")
-    anomalies = detect_anomalies(df)
-    st.dataframe(anomalies)
-
-    st.subheader("🛠 Upcoming AMC Devices")
-    if "amc_expiry" in df.columns:
-        amc_df = upcoming_amc_devices(df)
-        st.dataframe(amc_df)
-    else:
-        st.warning("AMC expiry column (`amc_expiry`) not found in uploaded data.")
+def main():
+    st.title("Multi-Device LabOps Dashboard")
+    
+    # Filters
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        lab_site = st.selectbox("Select Lab Site", ["All", "Lab1", "Lab2", "Lab3"])
+    with col2:
+        equipment_type = st.selectbox("Equipment Type", ["All", "Cell Analyzer", "Weight Log", "UV Verification"])
+    with col3:
+        date_range = st.date_input("Date Range", [datetime.now() - timedelta(days=7), datetime.now()])
+    
+    # Fetch data from Salesforce
+    query = f"""
+        SELECT Equipment__c, Log_Timestamp__c, Status__c, Usage_Count__c
+        FROM SmartLog__c
+        WHERE Log_Timestamp__c >= {date_range[0].strftime('%Y-%m-%d')}
+        AND Log_Timestamp__c <= {date_range[1].strftime('%Y-%m-%d')}
+    """
+    if lab_site != "All":
+        query += f" AND Lab__c = '{lab_site}'"
+    if equipment_type != "All":
+        query += f" AND Equipment_Type__c = '{equipment_type}'"
+    
+    data = fetch_salesforce_data(sf, query)
+    df = pd.DataFrame(data)
+    
+    if df.empty:
+        st.warning("No data available for the selected filters.")
+        return
+    
+    # Detect anomalies using Hugging Face
+    df["Anomaly"] = df["Status__c"].apply(lambda x: detect_anomalies(x, anomaly_detector))
+    
+    # Device Cards
+    st.subheader("Device Status")
+    for equipment in df["Equipment__c"].unique():
+        device_data = df[df["Equipment__c"] == equipment]
+        latest_log = device_data.iloc[-1]
+        anomaly = "⚠️ Anomaly" if latest_log["Anomaly"] == "POSITIVE" else "✅ Normal"
+        st.markdown(f"""
+            **{equipment}** | Health: {latest_log["Status__c"]} | Usage: {latest_log["Usage_Count__c"]} | Last Log: {latest_log["Log_Timestamp__c"]} | {anomaly}
+        """)
+    
+    # Usage Chart
+    st.subheader("Usage Trends")
+    fig = px.line(df, x="Log_Timestamp__c", y="Usage_Count__c", color="Equipment__c", title="Daily Usage Trends")
+    st.plotly_chart(fig, use_container_width=True)
+    
+    # Downtime Chart
+    downtime_df = df[df["Status__c"] == "Down"]
+    if not downtime_df.empty:
+        fig_downtime = px.histogram(downtime_df, x="Log_Timestamp__c", color="Equipment__c", title="Downtime Patterns")
+        st.plotly_chart(fig_downtime, use_container_width=True)
+    
+    # AMC Reminders
+    st.subheader("AMC Reminders")
+    amc_query = "SELECT Equipment__c, AMC_Expiry_Date__c FROM Equipment__c WHERE AMC_Expiry_Date__c <= NEXT_N_DAYS:14"
+    amc_data = fetch_salesforce_data(sf, amc_query)
+    for record in amc_data:
+        st.write(f"Equipment {record['Equipment__c']} - AMC Expiry: {record['AMC_Expiry_Date__c']}")
+    
+    # Export PDF
+    if st.button("Export PDF Report"):
+        pdf_file = generate_pdf_report(df, lab_site, equipment_type, date_range)
+        with open(pdf_file, "rb") as f:
+            st.download_button("Download PDF", f, file_name="LabOps_Report.pdf")
 
-    if st.button("📄 Generate PDF Report"):
-        generate_pdf(df)
-        st.success("PDF report generated and saved.")
+if __name__ == "__main__":
+    main()