Update app.py

app.py

@@ -5,7 +5,6 @@ import logging
 import plotly.express as px
 from sklearn.ensemble import IsolationForest  # For anomaly detection
 from transformers import pipeline
-import dask.dataframe as dd  # For handling large datasets
 
 # Configure logging for debugging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -167,11 +166,10 @@ def process_logs(file_obj, progress=gr.Progress()):
             logging.error("Unsupported file format")
             return "Unsupported file format. Please upload a CSV file.", None, None, None, None, None
 
-        # Use Dask for large CSV files to read in chunks
+        # Use pandas to load CSV (removed dask dependency)
         progress(0.05, "Loading CSV file...")
         try:
-            ddf = dd.from_pandas(pd.read_csv(file_name), npartitions=4)  # Split into 4 partitions
-            df = ddf.compute()  # Convert back to pandas after processing
+            df = pd.read_csv(file_name)
             logging.info(f"File loaded successfully with {len(df)} rows")
         except Exception as e:
             logging.error(f"Failed to load CSV: {str(e)}")
@@ -217,7 +215,7 @@ def process_logs(file_obj, progress=gr.Progress()):
         # Step 5: AMC Reminders
         amc_reminders = f"**Step 4: AMC Reminders**\n{check_amc_reminders(df, datetime.now(), progress)}\n---\n"
 
-        # Stepabba 6: Dashboard Insights
+        # Step 6: Dashboard Insights
         insights = f"**Step 5: Dashboard Insights (AI)**\n{generate_dashboard_insights(df, progress)}\n---\n"
 
         progress(1.0, "Processing complete!")
@@ -226,7 +224,7 @@ def process_logs(file_obj, progress=gr.Progress()):
         logging.error(f"Failed to process file: {str(e)}")
         return f"Failed to process file: {str(e)}", None, None, None, None, None
 
-# Gr{dimadio Interface with Step-by-Step Layout
+# Gradio Interface with Step-by-Step Layout
 try:
     logging.info("Initializing Gradio Blocks interface...")
     with gr.Blocks(css="""