Update app.py

app.py

@@ -1,5 +1,4 @@
-import sys
-import streamlit as st
+import gradio as gr
 import pandas as pd
 from utils.load_data import load_logs
 from utils.visualize import plot_usage
@@ -7,66 +6,105 @@ from utils.report import generate_pdf
 from models.anomaly import detect_anomalies
 from utils.amc import upcoming_amc_devices
 import logging
+import os
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 logger = logging.getLogger(__name__)
 
-# Streamlit app setup
-try:
-    st.set_page_config(page_title="LabOps Dashboard", layout="wide")
-    logger.info("Streamlit page configuration set successfully.")
-except Exception as e:
-    logger.error(f"Failed to configure Streamlit: {e}")
-    raise
-
-st.title("📊 Multi-Device LabOps Dashboard")
-
-# File uploader
-try:
-    uploaded_files = st.file_uploader("Upload Device Logs (CSV)", accept_multiple_files=True, type=["csv"])
+def process_files(*uploaded_files):
+    """Process uploaded CSV files and generate dashboard outputs."""
     logger.info(f"Received {len(uploaded_files)} uploaded files.")
-except Exception as e:
-    logger.error(f"File uploader error: {e}")
-    st.error(f"Failed to initialize file uploader: {e}")
-
-if uploaded_files:
     try:
+        if not uploaded_files:
+            return "Please upload at least one CSV file.", None, None, None, None
+
+        # Load data
         df = load_logs(uploaded_files)
         logger.info(f"Loaded {len(df)} log records from uploaded files.")
 
-        st.subheader("📋 Uploaded Logs")
-        st.dataframe(df.head())
+        # Log table
+        log_table = df.head().to_dict(orient="records")
 
-        st.subheader("📈 Daily Usage Chart")
+        # Usage chart
         fig = plot_usage(df)
-        st.pyplot(fig)
 
-        st.subheader("🚨 Detected Anomalies")
+        # Anomalies
         anomalies = detect_anomalies(df)
-        st.dataframe(anomalies)
+        anomaly_table = anomalies.to_dict(orient="records") if not anomalies.empty else "No anomalies detected."
 
-        st.subheader("🛠 Upcoming AMC Devices")
+        # AMC expiries
+        amc_table = None
         if "amc_expiry" in df.columns:
             amc_df = upcoming_amc_devices(df)
-            st.dataframe(amc_df)
+            amc_table = amc_df.to_dict(orient="records") if not amc_df.empty else "No upcoming AMC expiries."
         else:
-            st.info("Column `amc_expiry` not found in uploaded data.")
+            amc_table = "Column `amc_expiry` not found in uploaded data."
             logger.warning("Missing `amc_expiry` column in data.")
 
-        if st.button("📄 Generate PDF Report"):
-            pdf_path = generate_pdf(df)
-            with open(pdf_path, "rb") as f:
-                st.download_button("Download PDF", f, file_name="labops_report.pdf", mime="application/pdf")
-            logger.info("PDF report generated and offered for download.")
+        return log_table, fig, anomaly_table, amc_table, df
 
+def generate_pdf_report(df):
+    """Generate and return path to PDF report."""
+    if df is None:
+        return "Please upload CSV files first."
+    logger.info("Generating PDF report...")
+    try:
+        pdf_path = generate_pdf(df)
+        return pdf_path
     except Exception as e:
-        logger.error(f"Error processing uploaded files: {e}")
-        st.error(f"Failed to process data: {e}")
+        logger.error(f"Failed to generate PDF: {e}")
+        return f"Error generating PDF: {e}"
+
+with gr.Blocks(title="Multi-Device LabOps Dashboard") as demo:
+    gr.Markdown("# 📊 Multi-Device LabOps Dashboard")
+    
+    with gr.Row():
+        file_input = gr.File(file_count="multiple", file_types=[".csv"], label="Upload Device Logs (CSV)")
+    
+    with gr.Row():
+        submit_btn = gr.Button("Process Files")
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("## 📋 Uploaded Logs")
+            log_output = gr.Dataframe()
+        with gr.Column():
+            gr.Markdown("## 📈 Daily Usage Chart")
+            chart_output = gr.Plot()
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("## 🚨 Detected Anomalies")
+            anomaly_output = gr.Dataframe()
+        with gr.Column():
+            gr.Markdown("## 🛠 Upcoming AMC Devices")
+            amc_output = gr.Dataframe()
+    
+    with gr.Row():
+        pdf_btn = gr.Button("📄 Generate PDF Report")
+        pdf_output = gr.File(label="Download PDF Report")
+    
+    # State to store dataframe
+    df_state = gr.State()
+
+    # Connect inputs to outputs
+    submit_btn.click(
+        fn=process_files,
+        inputs=[file_input],
+        outputs=[log_output, chart_output, anomaly_output, amc_output, df_state]
+    )
+    
+    pdf_btn.click(
+        fn=generate_pdf_report,
+        inputs=[df_state],
+        outputs=[pdf_output]
+    )
 
 if __name__ == "__main__":
     try:
         logger.info("Application starting...")
+        demo.launch(server_name="0.0.0.0", server_port=7860)
     except Exception as e:
         logger.error(f"Application failed to start: {e}")
         raise