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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Site[[:space:]]List.xlsx filter=lfs diff=lfs merge=lfs -text
+template.pptx filter=lfs diff=lfs merge=lfs -text

Site List.xlsx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a043f6d5c7757b519f69aef807f9310aa01914845c3fb9832a3592d7fce4be61
+size 8414272

app.py

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+# Import package and module
+import gradio as gr
+import pandas as pd
+from transformers import pipeline
+from g4f.client import Client
+
+
+# /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+# Initialize GPT-4 Client
+client = Client()
+
+
+# Function for answering questions using GPT-4
+def process_notes(notes):
+    questions = [
+        "Sebutkan Kendala Customer?   (Contoh jawaban yang benar -> sinyal inet tidak stabil, all app, 1-2 bar E, in/outdoor sama, no ybs saja)", # detail_complain
+        "Siapa Nama Customer?   (Contoh jawaban yang benar -> Damelia)", # customer_name
+        "Berapa Nomor MSISDN Yang Bermasalah:   (Contoh jawaban yang benar -> 6281298765432)", # msisdn
+        "Kapan Tanggal/Jam Kejadian?    (Contoh jawaban yang benar -> 20/12/2024 11:24 - 15:24)", # tanggal_kejadian
+        "Dimana Lokasi Pelanggan (alamat)?    (Contoh jawaban yang benar -> Jl. Bambu Kuning No.33, Bojonggede, Kecamatan Bojonggede, Kabupaten Bogor, Jawa Barat 16922)", # location
+        # "Apakah mode jaringan (4G/3G/2G)?", # mode_jaringan
+        # "Apakah Tier pelanggan (Silver/Gold/Platinum/Diamond)?", # tipe_pelanggan
+    ]
+
+    answers = []
+    for q in questions:
+      prompt = f"[Language: Bahasa Indonesia] Jawab singkat dan langsung: {q} {notes}"
+      response = client.chat.completions.create(model="gpt-4o-mini", messages=[{"role": "user", "content": prompt}])
+      answers.append(response.choices[0].message.content.strip())
+    return answers
+
+
+
+# Function for generating report
+def generate_report(no_ticket, detail_complain, customer_name, msisdn, tanggal_kejadian, remedy_submit_time, severity,
+                    location, long_lat, mode_jaringan, kategori_keluhan, tipe_pelanggan, device, profile_check,
+                    imsi_bcp_choice, site_name, availability, alarm_impact, accessibility_issue, high_prb_dl,
+                    high_max_user, high_ul_interference, transport_issue_pl, transport_issue_tnl, transport_issue_latency,
+                    status, av_status, orbit_byu, rsrp_rsrq, hc_site, suspect_issue, action_plan):
+
+    # Report format
+    report = f"""
+    No. Ticket: {no_ticket}
+    Detail Complaint: {detail_complain}
+    Nama: {customer_name}
+    MSISDN: {msisdn}
+    Tanggal Kejadian: {tanggal_kejadian}
+    Remedy Submit Time: {remedy_submit_time}
+    Severity: {severity}
+    ------------------
+    Location: {location}
+    Long Lat: {long_lat} (perkiraan lokasi pelanggan)
+    ------------------
+    Mode Jaringan: {mode_jaringan}
+    Kategori Keluhan: {kategori_keluhan}
+    Tipe Pelanggan: {tipe_pelanggan}
+    Device: {device}
+    ------------------
+    1. Profile Check:
+    {profile_check}
+    ------------------
+    2. Healty Check:
+    #4G: {site_name}
+    - Availability - {availability}
+    - Alarm impact service - {alarm_impact}
+    - Accessibility issue - {accessibility_issue}
+    - High PRB DL - {high_prb_dl}
+    - High Max user - {high_max_user}
+    - High Ul Interference - {high_ul_interference}
+    - Transport issue based on PL - {transport_issue_pl}
+    - Transport issue based on TNL - {transport_issue_tnl}
+    - Transport issue based on latency - {transport_issue_latency}
+    ------------------
+    3. Parameter Check:
+    - {site_name}, Status: {status}, Av. Status: {av_status}
+    - All Parameter Standard and Proper
+    ------------------
+    4. Finding:
+    - Pelanggan {orbit_byu}HVC {tipe_pelanggan} berkendala {detail_complain}
+    - Site terdekat dengan pelanggan adalah {site_name}
+    {imsi_bcp(imsi_bcp_choice, site_name)}
+    - {rsrp_rsrq}
+    - Hasil HC {site_name} {hc_site}
+    ------------------
+    5. Suspect Issue :
+    - {suspect_issue}
+    ------------------
+    6. Action Plan:
+    - {action_plan}
+    ------------------
+    Terima kasih
+    """
+    # Remove extra spaces in the output
+    return "\n".join([line.strip() for line in report.splitlines() if line.strip()])
+
+
+
+# Function for determining IMSI or BCP
+def imsi_bcp(imsi_bcp_choice, site_name):
+    # Simplified conditional return
+    return (
+        f"- Hasil IMSI tercover {site_name}" if imsi_bcp_choice == "IMSI" else
+        f"- Hasil IMSI no record\n- Hasil BCP tercover {site_name}" if imsi_bcp_choice == "BCP (IMSI no record)" else
+        f"- Hasil IMSI tercover {site_name}\n- Hasil BCP tercover {site_name}" if imsi_bcp_choice == "IMSI & BCP" else ""
+    )
+
+
+
+# Interface for tab 1
+with gr.Blocks() as tab1:
+    # Input for notes
+    notes = gr.Textbox(label="Notes", max_lines = 5)
+    # Submit button for notes
+    with gr.Row():
+        reset1 = gr.ClearButton(components=[notes], value="Reset")
+        submit1 = gr.Button("Submit Notes", variant="primary")
+
+    # Input for generate report
+    with gr.Row():
+        with gr.Column():
+            no_ticket = gr.Textbox(label="No. Ticket", placeholder="INCxxx", lines=1)
+            detail_complain = gr.Textbox(label="Detail Complaint", placeholder="Internet Lambat")
+            customer_name = gr.Textbox(label="Nama", placeholder="Damelia", lines=1)
+            msisdn = gr.Textbox(label="MSISDN", placeholder="62xxx", lines=1)
+            tanggal_kejadian = gr.Textbox(label="Tanggal Kejadian", placeholder="1 Januari 2001", lines=1)
+            remedy_submit_time = gr.Textbox(label="Remedy Submit Time", placeholder="01/01/2001 01:00:00 AM", lines=1)
+            severity = gr.Radio(["Low", "Medium", "High"], label="Severity", value="Low")
+            orbit_byu = gr.Radio(["", "ORBIT ", "BYU "], label="ORBIT / BYU", value="")
+
+        with gr.Column():
+            location = gr.Textbox(label="Location", placeholder="Jalan xxx No.1 RT/RW")
+            long_lat = gr.Textbox(label="Long Lat", placeholder="-6.123456, 106.123456", lines=1)
+            mode_jaringan = gr.Radio(["4G", "3G", "2G"], label="Mode Jaringan", value="4G")
+            kategori_keluhan = gr.Radio(["Data", "Coverage", "Voice"], label="Kategori Keluhan", value="Data")
+            tipe_pelanggan = gr.Radio(["Silver", "Gold", "Platinum", "Diamond"], label="Tipe Pelanggan", value="Gold")
+            device = gr.Textbox(label="Device", placeholder="iPhone 15 Pro Max", value="-")
+            profile_check = gr.Textbox(label="Profile Check", value="* SIM Capability : USIM\n* Barring Status PS : No Barring\n* Barring Status CS : No Barring\n* Quota Status : OK", max_lines=5)
+
+    with gr.Row():
+        with gr.Column():
+            imsi_bcp_choice = gr.Radio(["IMSI", "BCP (IMSI no record)", "IMSI & BCP"], label="Trace dari IMSI / BCP", value="IMSI")
+            site_name = gr.Textbox(label="Site Name", placeholder="X_JXX000MXX_Nama-DXX_MX00")
+            status = gr.Radio(["Enable", "Disable", "Unknown"], label="Status", value="Enable")
+            av_status = gr.Radio(["Normal", "Invalid", "Unknown"], label="Av. Status", value="Normal")
+            rsrp_rsrq = gr.Textbox(label="RSRP & RSRQ", value="RSRP -106 dBm & RSRQ -12 dB")
+
+        with gr.Column():
+            availability = gr.Radio(["Safe", "Not Safe"], label="Availability", value="Safe")
+            alarm_impact = gr.Radio(["Safe", "Not Safe"], label="Alarm Impact", value="Safe")
+            accessibility_issue = gr.Radio(["Safe", "Not Safe"], label="Accessibility Issue", value="Safe")
+            high_prb_dl = gr.Radio(["Safe", "Not Safe"], label="High PRB DL", value="Safe")
+            high_max_user = gr.Radio(["Safe", "Not Safe"], label="High Max User", value="Safe")
+
+        with gr.Column():
+            high_ul_interference = gr.Radio(["Safe", "Not Safe"], label="High UL Interference", value="Safe")
+            transport_issue_pl = gr.Radio(["Safe", "Not Safe"], label="Transport Issue PL", value="Safe")
+            transport_issue_tnl = gr.Radio(["Safe", "Not Safe"], label="Transport Issue TNL", value="Safe")
+            transport_issue_latency = gr.Radio(["Safe", "Not Safe"], label="Transport Issue Latency", value="Safe")
+            hc_site = gr.Textbox(label="HC Site", value="dalam kondisi KPI normal")
+
+    with gr.Row():
+        suspect_issue = gr.Dropdown(["Low coverage", "Quality Problem", "No Dominant Coverage", "High PRB", "Availability Problem", "Trans TNL", "Trans Packet Loss", "Alarm Problem", "Trans Alarm", "High UL Interference", "High VSWR", "Site Dismantle", "IT Problem", "Others"], label="Suspect Issue", value="Low coverage")
+        action_plan = gr.Dropdown(["Optimasi", "Troubleshoot", "User Education", "Reengineering", "ESCALATED TO HQ"], label="Action Plan", value="Optimasi")
+
+    # Inputs list of generate report
+    fields_generate_report = [no_ticket, detail_complain, customer_name, msisdn, tanggal_kejadian, remedy_submit_time, severity,
+                              location, long_lat, mode_jaringan, kategori_keluhan, tipe_pelanggan, device, profile_check,
+                              imsi_bcp_choice, site_name, availability, alarm_impact, accessibility_issue, high_prb_dl,
+                              high_max_user, high_ul_interference, transport_issue_pl, transport_issue_tnl, transport_issue_latency,
+                              status, av_status, orbit_byu, rsrp_rsrq, hc_site, suspect_issue, action_plan]
+
+    # Submit button for generate report
+    with gr.Row():
+        reset2 = gr.ClearButton(components=[*fields_generate_report], value="Reset")
+        submit2 = gr.Button("Generate Report", variant="primary")
+
+    # For showing the output
+    output = gr.Textbox(label="Report", interactive=True, lines=0)
+
+    # Function for PPT
+    download_button = gr.File(label="Download Template PPT", value="template.pptx")
+
+    # Process button for notes using GPT-4
+    submit1.click(process_notes, inputs=notes, outputs=[detail_complain, customer_name, msisdn, tanggal_kejadian, location])
+    # submit1.click(process_notes, inputs=notes, outputs=[detail_complain, customer_name, msisdn, tanggal_kejadian, location, mode_jaringan, tipe_pelanggan])
+    # Process button for generating report
+    submit2.click(generate_report, inputs=fields_generate_report, outputs=output)
+
+
+# /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+# Function for creating HTML imsi table
+def imsi_df_style(df, table_id="imsi-table"):
+    # Convert DataFrame to HTML table with custom classes
+    html = df.to_html(classes='table table-bordered',
+                      border=0,
+                      index=False,
+                      table_id=table_id)
+
+    # Custom CSS for the table
+    custom_css = """
+    <style>
+    body {
+        font-family: 'Calibri', sans-serif;
+        font-size: 5px;
+    }
+    #table-container {
+        max-height: 600px;
+        overflow-y: auto;
+        position: relative;
+    }
+    #imsi-table {
+        width: 100%;
+        border-collapse: collapse;
+    }
+    #imsi-table th {
+        position: sticky;
+        top: 0;
+        background-color: #FFFF00;
+        color: black;
+        padding: 2px;
+        font-weight: normal;
+        border: 1px solid #d6d6d6;
+        z-index: 1;
+    }
+    #imsi-table td {
+        background-color: white;
+        color: black;
+        padding: 2px;
+        border: 1px solid #d6d6d6;
+    }
+    </style>
+    """
+
+    # Wrap the table in a container
+    wrapped_html = f'<div id="table-container">{html}</div>'
+    return custom_css + wrapped_html
+
+
+
+# OOP for tab 2: IMSI Trace
+# class IMSIReportStyler:
+#     def __init__(self, df, table_id="imsi-table"):
+#         self.df = df
+#         self.table_id = table_id
+#         self.html = None
+
+#     def generate_html(self):
+#         self.html = self.df.to_html(
+#             classes='table table-bordered',
+#             border=0,
+#             index=False,
+#             table_id=self.table_id
+#         )
+
+#     def apply_css(self):
+#         custom_css = """
+#         <style>
+#         body {
+#             font-family: 'Calibri', sans-serif;
+#             font-size: 5px;
+#         }
+#         #table-container {
+#             max-height: 600px;
+#             overflow-y: auto;
+#             position: relative;
+#         }
+#         #imsi-table {
+#             width: 100%;
+#             border-collapse: collapse;
+#         }
+#         #imsi-table th {
+#             position: sticky;
+#             top: 0;
+#             background-color: #FFFF00;
+#             color: black;
+#             padding: 2px;
+#             font-weight: normal;
+#             border: 1px solid #d6d6d6;
+#             z-index: 1;
+#         }
+#         #imsi-table td {
+#             background-color: white;
+#             color: black;
+#             padding: 2px;
+#             border: 1px solid #d6d6d6;
+#         }
+#         </style>
+#         """
+#         self.html = custom_css + f'<div id="table-container">{self.html}</div>'
+
+#     def style_report(self):
+#         self.generate_html()
+#         self.apply_css()
+#         return self.html
+
+
+
+# Function for tab 2: IMSI Trace
+def imsi_trace(file):
+    # Load IMSI data
+    imsi = pd.read_csv(file.name).sort_values('Start Time', ascending=False)
+
+    # Group and calculate statistics
+    count_df = imsi.groupby('Start Cell Name').size().reset_index(name='Count of Start Cell Name').sort_values(by='Count of Start Cell Name', ascending=False)
+    avg_df = imsi.groupby('Start Cell Name')[['Start RxLev/RSCP/RSRP (dBm)', 'Start RxQual/ECN0/RSRQ (dB)']].mean().reset_index()
+    result_df = pd.merge(count_df, avg_df, on='Start Cell Name', how='inner')
+
+    # Select columns for filtered data
+    filtered_imsi = imsi[['Start Time', 'MSISDN', 'Technology', 'Call Type', 'Start Cell Name', 'Start Latitude', 'Start Longtitude', 'Start RxLev/RSCP/RSRP (dBm)', 'Start RxQual/ECN0/RSRQ (dB)']]
+
+    # Write to Excel with colored headers
+    writer = pd.ExcelWriter('hasil_imsi.xlsx', engine='xlsxwriter')
+    filtered_imsi.to_excel(writer, sheet_name='Data IMSI', index=False)
+    workbook = writer.book
+    worksheet = writer.sheets['Data IMSI']
+
+    # Define header format
+    header_format = workbook.add_format({'valign': 'center', 'fg_color': '#FFFF00', 'font_color': "black", 'border': 1})
+
+    # Apply header format using list comprehension
+    [worksheet.write(0, col_num, value, header_format) for col_num, value in enumerate(filtered_imsi.columns)]
+
+    writer.close()
+
+    # Convert to HTML table with custom CSS
+    imsi_output = imsi_df_style(filtered_imsi)
+
+    # styler = IMSIReportStyler(filtered_imsi)
+    # imsi_output = styler.style_report()
+
+    return result_df, imsi_output, "hasil_imsi.xlsx"
+
+
+
+# Interface for tab 2
+with gr.Blocks() as tab2:
+    with gr.Row():
+        with gr.Column(scale=1/4):
+            file_input = gr.File(label="Upload CSV")
+            with gr.Row():
+                submit_btn = gr.Button("Submit", variant="primary")
+                reset_btn = gr.ClearButton([file_input], value="Reset")
+            dw_filtered_imsi = gr.File(label="Download Filtered IMSI")
+        with gr.Column(scale=3/4):
+            pivoted_imsi = gr.Dataframe(label="Pivoted Data")
+    filtered_imsi = gr.HTML(label="Filtered Data")
+
+    submit_btn.click(fn=imsi_trace, inputs=file_input, outputs=[pivoted_imsi, filtered_imsi, dw_filtered_imsi])
+
+
+# /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+# Function for creating HTML imsi table
+def bcp_df_style(df, table_id="bcp-table"):
+    # Convert DataFrame to HTML table with custom classes
+    html = df.to_html(classes='table table-bordered',
+                      border=0,
+                      index=False,
+                      table_id=table_id)
+
+    # Custom CSS for the table
+    custom_css = """
+    <style>
+    body {
+        font-family: 'Calibri', sans-serif;
+        font-size: 5px;
+    }
+    #table-container {
+        max-height: 600px;
+        overflow-y: auto;
+        position: relative;
+    }
+    #bcp-table {
+        width: 100%;
+        border-collapse: collapse;
+    }
+    #bcp-table th {
+        position: sticky;
+        top: 0;
+        background-color: #2f75b5;
+        color: white;
+        padding: 2px;
+        font-weight: bold;
+        border: 1px solid #d6d6d6;
+        z-index: 1;
+        text-align: center;
+    }
+    #bcp-table th:nth-last-child(2),
+    #bcp-table th:nth-last-child(1) {
+        background-color: #ffd966;
+    }
+    #bcp-table td {
+        background-color: white;
+        color: black;
+        padding: 2px;
+        border: 1px solid #d6d6d6;
+        white-space: nowrap;
+        overflow: hidden;
+    }
+    #bcp-table td:nth-child(n+3):nth-child(-n+12) {
+      overflow: hidden;
+      text-overflow: ellipsis;
+      max-width: 120px;
+    }
+    </style>
+    """
+
+    # Wrap the table in a container
+    wrapped_html = f'<div id="table-container">{html}</div>'
+    return custom_css + wrapped_html
+
+
+
+# Function for tab 3: BCP Trace
+def bcp_trace(file):
+    # Load site list and BCP data
+    bcp_site_list = pd.read_excel("Site List.xlsx", sheet_name="Site List")
+    # bcp = pd.read_csv(file.name, sep=",").iloc[:, :-1].sort_values('Timestamp ', ascending=False)
+    bcp = pd.read_csv(file.name, sep=",").sort_values('Timestamp ', ascending=False)
+    bcp['RAT '] = bcp['RAT '].replace('5G-NSA', '4G')
+
+    # Calculate LAC-CI
+    bcp['LAC-CI'] = bcp.apply(lambda row: int(row['CGI '][11:17] + row['CGI '][-2:]) if row['RAT '] == '4G' else int(row['CGI '][-9:]), axis=1)
+
+    # Map site names
+    dict_site_name = bcp_site_list.set_index('LACCI')['cellname'].to_dict()
+    bcp['SITE NAME'] = bcp['LAC-CI'].map(dict_site_name)
+
+    # Select and sort columns
+    bcp = bcp[['Timestamp ', 'Source ', 'CGI ', 'RAT ', 'Village ', 'LAC ', 'CI/ECI ', 'City ', 'Province ', 'Region ', 'Geolocation ', 'Country ', 'LAC-CI', 'SITE NAME']]
+
+    # Write to Excel with colored headers
+    writer = pd.ExcelWriter('hasil_bcp.xlsx', engine='xlsxwriter')
+    bcp.to_excel(writer, sheet_name='Data BCP', index=False)
+    workbook = writer.book
+    worksheet = writer.sheets['Data BCP']
+
+    # Define header colors
+    header_format_1 = workbook.add_format({'bold': True, 'valign': 'center', 'fg_color': '#2f75b5', 'font_color': "#FFFFFF", 'border': 1})
+    header_format_2 = workbook.add_format({'bold': True, 'valign': 'center', 'fg_color': '#ffd966', 'font_color': "#FFFFFF", 'border': 1})
+
+    # Apply header colors using list comprehension
+    [worksheet.write(0, col_num, value, header_format_1 if value in ['Timestamp ', 'Source ', 'CGI ', 'RAT ', 'Village ', 'LAC ', 'CI/ECI ', 'City ', 'Province ', 'Region ', 'Geolocation ', 'Country '] else header_format_2) for col_num, value in enumerate(bcp.columns)]
+
+    writer.close()
+
+    # Group and count site names
+    count_df = bcp.groupby('SITE NAME').size().reset_index(name='Count of SITE NAME').sort_values(by='Count of SITE NAME', ascending=False)
+
+    # Convert to HTML table with custom CSS
+    bcp_output = bcp_df_style(bcp)
+
+    return count_df, bcp_output, "hasil_bcp.xlsx"
+
+
+
+# Interface for tab 3
+with gr.Blocks() as tab3:
+    with gr.Row():
+        with gr.Column(scale=1/4):
+            file_input = gr.File(label="Upload CSV")
+            with gr.Row():
+                submit_btn = gr.Button("Submit", variant="primary")
+                reset_btn = gr.ClearButton([file_input], value="Reset")
+            dw_filtered_bcp = gr.File(label="Download Filtered BCP")
+        with gr.Column(scale=3/4):
+            pivoted_bcp = gr.Dataframe(label="Pivoted Data")
+    filtered_bcp = gr.HTML(label="Filtered Data")
+
+    submit_btn.click(fn=bcp_trace, inputs=file_input, outputs=[pivoted_bcp, filtered_bcp, dw_filtered_bcp])
+
+
+# /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+# Fuction for VIP and Non-Remedy
+
+
+# /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+# Combine all tabs
+demo = gr.TabbedInterface(
+          [tab1, tab2, tab3],
+          ["Generate Report", "IMSI Trace", "BCP Trace"],
+          # theme=gr.themes.Glass(),
+        )
+demo.launch(share=True)
+

requirements.txt

@@ -0,0 +1,7 @@
+gradio
+pandas
+transformers
+torch
+openpyxl
+xlsxwriter
+g4f[all]

template.pptx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b5f75aba8296c6706c5de0fe83ce3740dd05a7cdc6fb73baa8c83f99717359aa
+size 151363