Update app.py

app.py

@@ -8,52 +8,20 @@ from reportlab.pdfgen import canvas
 
 REQUIRED_COLUMNS = ['DeviceID', 'Lab', 'Type', 'Timestamp', 'Status', 'UsageCount']
 
-# ----------------------------
-# Helper to extract file content correctly for HF Spaces and local
-# ----------------------------
-def get_file_content(file_obj):
-    if file_obj is None:
-        return None
-
-    if hasattr(file_obj, "read"):
-        content = file_obj.read()
-        if isinstance(content, bytes):
-            return content
-        else:
-            return content.encode('utf-8')
-
-    if isinstance(file_obj, dict) and 'data' in file_obj:
-        data = file_obj['data']
-        if isinstance(data, str):
-            import base64
-            if data.startswith("data:"):
-                data = data.split(",")[1]
-            return base64.b64decode(data)
-        elif isinstance(data, bytes):
-            return data
-        else:
-            raise ValueError("Unexpected data format in file upload dict")
-
-    if isinstance(file_obj, str):
-        with open(file_obj, "rb") as f:
-            return f.read()
-
-    raise ValueError("Unsupported file object format")
-
 # ----------------------------
 # Load Logs Safely
 # ----------------------------
 def load_logs(file_obj):
     try:
         if file_obj is not None:
-            content_bytes = get_file_content(file_obj)
-            content_str = content_bytes.decode('utf-8')
-            df = pd.read_csv(io.StringIO(content_str))
+            # file_obj is a NamedTemporaryFile, get file path to read with pandas directly
+            df = pd.read_csv(file_obj.name)
             if not all(col in df.columns for col in REQUIRED_COLUMNS):
                 raise ValueError(f"CSV must contain columns: {', '.join(REQUIRED_COLUMNS)}")
             df['Timestamp'] = pd.to_datetime(df['Timestamp'], errors='coerce')
             df.dropna(subset=['Timestamp'], inplace=True)
         else:
+            # Default sample data
             df = pd.DataFrame({
                 'DeviceID': ['D001', 'D002', 'D003'],
                 'Lab': ['Lab A', 'Lab B', 'Lab A'],
@@ -69,15 +37,14 @@ def load_logs(file_obj):
         raise ValueError(f"Failed to load CSV: {e}")
 
 # ----------------------------
-# Filter DataFrame by Lab and Type
+# Filter dataframe by Lab and Type
 # ----------------------------
-def filter_df(df, selected_lab, selected_type):
-    filtered = df.copy()
-    if selected_lab and selected_lab != "All":
-        filtered = filtered[filtered['Lab'] == selected_lab]
-    if selected_type and selected_type != "All":
-        filtered = filtered[filtered['Type'] == selected_type]
-    return filtered
+def filter_data(df, lab, dev_type):
+    if lab != "All":
+        df = df[df['Lab'] == lab]
+    if dev_type != "All":
+        df = df[df['Type'] == dev_type]
+    return df
 
 # ----------------------------
 # Summarize Log Data
@@ -91,12 +58,12 @@ def summarize_logs(df):
 # ----------------------------
 # Generate Chart
 # ----------------------------
-def generate_chart(df, selected_lab, selected_type):
-    filtered = filter_df(df, selected_lab, selected_type)
-    summary = summarize_logs(filtered)
+def generate_chart(df, lab, dev_type):
+    filtered_df = filter_data(df, lab, dev_type)
+    summary = summarize_logs(filtered_df)
     if summary.empty:
-        fig, ax = plt.subplots(figsize=(8, 4))
-        ax.text(0.5, 0.5, 'No data for selected filters', ha='center', va='center', fontsize=14)
+        fig, ax = plt.subplots()
+        ax.text(0.5, 0.5, "No data for selected filters", ha='center', va='center')
         ax.axis('off')
         return fig
     fig, ax = plt.subplots(figsize=(8, 4))
@@ -111,9 +78,9 @@ def generate_chart(df, selected_lab, selected_type):
 # ----------------------------
 # Export PDF using ReportLab
 # ----------------------------
-def export_pdf(df, selected_lab, selected_type):
-    filtered = filter_df(df, selected_lab, selected_type)
-    summary = summarize_logs(filtered)
+def export_pdf(df, lab, dev_type):
+    filtered_df = filter_data(df, lab, dev_type)
+    summary = summarize_logs(filtered_df)
     buffer = io.BytesIO()
     pdf = canvas.Canvas(buffer, pagesize=letter)
     width, height = letter
@@ -122,8 +89,9 @@ def export_pdf(df, selected_lab, selected_type):
     pdf.drawCentredString(width / 2, height - 40, "LabOps Dashboard Summary Report")
     pdf.setFont("Helvetica", 10)
     pdf.drawCentredString(width / 2, height - 60, f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+    pdf.drawCentredString(width / 2, height - 80, f"Filters - Lab: {lab}, Type: {dev_type}")
 
-    y = height - 100
+    y = height - 110
     pdf.setFont("Helvetica-Bold", 10)
     pdf.drawString(50, y, "Lab")
     pdf.drawString(150, y, "Device Type")
@@ -132,9 +100,9 @@ def export_pdf(df, selected_lab, selected_type):
     y -= 20
     pdf.setFont("Helvetica", 10)
 
-    for (lab, dev_type), row in summary.iterrows():
-        pdf.drawString(50, y, str(lab))
-        pdf.drawString(150, y, str(dev_type))
+    for (lab_name, dev_type_name), row in summary.iterrows():
+        pdf.drawString(50, y, str(lab_name))
+        pdf.drawString(150, y, str(dev_type_name))
         pdf.drawString(300, y, str(int(row.get('OK', 0))))
         pdf.drawString(350, y, str(int(row.get('DOWN', 0))))
         y -= 20
@@ -147,79 +115,61 @@ def export_pdf(df, selected_lab, selected_type):
     return ("LabOps_Summary.pdf", buffer.read())
 
 # ----------------------------
-# Update dropdown options based on uploaded file
+# UI Functions
 # ----------------------------
-def update_dropdown_options(file_obj):
-    try:
-        df = load_logs(file_obj)
-        labs = sorted(df['Lab'].dropna().unique().tolist())
-        types = sorted(df['Type'].dropna().unique().tolist())
-        labs = ["All"] + labs
-        types = ["All"] + types
-        return labs, types, gr.update(visible=True)
-    except Exception as e:
-        return ["All"], ["All"], gr.update(visible=False)
 
-# ----------------------------
-# Dashboard Display with filters
-# ----------------------------
-def dashboard(file_obj, selected_lab, selected_type):
-    try:
-        df = load_logs(file_obj)
-        fig = generate_chart(df, selected_lab, selected_type)
-        return fig, gr.update(visible=False)
-    except Exception as e:
-        return None, gr.update(value=f"❌ Error: {e}", visible=True)
+def get_unique_labs_types(df):
+    labs = ["All"] + sorted(df['Lab'].unique().tolist())
+    types = ["All"] + sorted(df['Type'].unique().tolist())
+    return labs, types
 
-# ----------------------------
-# PDF Generator with filters
-# ----------------------------
-def generate_pdf_button(file_obj, selected_lab, selected_type):
+def on_file_load(file_obj):
+    df = load_logs(file_obj)
+    labs, types = get_unique_labs_types(df)
+    fig = generate_chart(df, "All", "All")
+    return fig, gr.Dropdown.update(choices=labs, value="All"), gr.Dropdown.update(choices=types, value="All"), ""
+
+def on_filter_change(file_obj, lab, dev_type):
+    df = load_logs(file_obj)
+    fig = generate_chart(df, lab, dev_type)
+    return fig
+
+def on_generate_pdf(file_obj, lab, dev_type):
+    df = load_logs(file_obj)
     try:
-        df = load_logs(file_obj)
-        filename, pdf_bytes = export_pdf(df, selected_lab, selected_type)
-        return gr.File.update(value=(filename, pdf_bytes), visible=True), gr.Textbox.update(visible=False)
+        filename, pdf_bytes = export_pdf(df, lab, dev_type)
+        return gr.File.update(value=(filename, pdf_bytes), visible=True), ""
     except Exception as e:
-        return gr.File.update(visible=False), gr.Textbox.update(value=f"❌ Error: {e}", visible=True)
+        return gr.File.update(visible=False), f"❌ Error generating PDF: {e}"
 
 # ----------------------------
 # Gradio Interface
 # ----------------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## 🧪 LabOps Dashboard")
-    gr.Markdown("Upload lab device logs to visualize uptime/downtime & generate PDF reports.")
+    gr.Markdown("## 🧪 LabOps Dashboard with Filters")
+    gr.Markdown("Upload lab device logs, filter by Lab and Equipment Type, visualize uptime/downtime & generate PDF reports.")
 
     with gr.Row():
         file_input = gr.File(label="Upload Log CSV", file_types=[".csv"])
-        lab_dropdown = gr.Dropdown(label="Select Lab", choices=["All"], value="All", interactive=True)
-        type_dropdown = gr.Dropdown(label="Select Equipment Type", choices=["All"], value="All", interactive=True)
+    with gr.Row():
+        lab_dropdown = gr.Dropdown(label="Select Lab", choices=["All"], value="All")
+        type_dropdown = gr.Dropdown(label="Select Equipment Type", choices=["All"], value="All")
+
+    plot_output = gr.Plot()
+    error_output = gr.Textbox(visible=False, interactive=False, label="Errors", lines=1)
+
+    with gr.Row():
         download_button = gr.Button("Download PDF Summary")
         download_file = gr.File(label="Download PDF", visible=False)
 
-    plot_output = gr.Plot()
-    error_output = gr.Textbox(visible=False, label="Errors")
-
-    # Update dropdowns on file upload
-    file_input.change(
-        fn=update_dropdown_options,
-        inputs=file_input,
-        outputs=[lab_dropdown, type_dropdown, error_output]
-    )
-
-    # Update plot when file or dropdowns change
-    inputs_for_dashboard = [file_input, lab_dropdown, type_dropdown]
-    for input_component in inputs_for_dashboard:
-        input_component.change(
-            fn=dashboard,
-            inputs=inputs_for_dashboard,
-            outputs=[plot_output, error_output]
-        )
-
-    # Generate PDF on button click
-    download_button.click(
-        fn=generate_pdf_button,
-        inputs=[file_input, lab_dropdown, type_dropdown],
-        outputs=[download_file, error_output]
-    )
+    # Load file -> update dropdowns & plot
+    file_input.change(fn=on_file_load, inputs=file_input, outputs=[plot_output, lab_dropdown, type_dropdown, error_output])
+
+    # When filters change -> update plot only
+    lab_dropdown.change(fn=on_filter_change, inputs=[file_input, lab_dropdown, type_dropdown], outputs=plot_output)
+    type_dropdown.change(fn=on_filter_change, inputs=[file_input, lab_dropdown, type_dropdown], outputs=plot_output)
+
+    # Generate PDF button
+    download_button.click(fn=on_generate_pdf, inputs=[file_input, lab_dropdown, type_dropdown], outputs=[download_file, error_output])
 
 demo.launch()