Update app.py

app.py

@@ -1,8 +1,10 @@
 import gradio as gr
 import pandas as pd
-import re
 
-# Mapping dictionary
+# Load your data (replace with your actual file path if local or URL if remote)
+df = pd.read_excel("your_file.xlsx")
+
+# Mapping for AG column
 mapping = {
     "obs_commercial_purpose_commercial": "Commercial",
     "obs_commercial_purpose_issue": "SIP",
@@ -15,97 +17,77 @@ mapping = {
     "obs_immigration_global": "Immigration",
     "obs_crime_global": "Crime",
     "obs_guns_global": "Guns",
-    "obs_education_global": "Education",
+    "obs_education_global": "Education"
 }
 
-def process_tags(tags):
-    if not isinstance(tags, str):
-        return ""
-    
-    raw_tags = [t.strip() for t in tags.split(",") if t.strip()]
-    
-    # Rule 1: If Commercial exists → only output Commercial
-    if "obs_commercial_purpose_commercial" in raw_tags:
-        return "Commercial"
+def process_row(name, job_id, col_r, col_af, col_ag, col_cc):
+    # Handle TM (col_r)
+    tm_value = mapping.get(col_r, "NT") if pd.notna(col_r) else "NT"
     
-    # Otherwise map normally
-    mapped = []
-    sip_flag = False
-    for tag in raw_tags:
-        if tag == "obs_commercial_purpose_issue":
-            sip_flag = True  # store SIP to add later
-        elif tag in mapping:
-            mapped.append(mapping[tag])
-    
-    # Add SIP at the end if exists
-    if sip_flag:
-        mapped.append("SIP")
-    
-    return ", ".join(mapped)
+    # Handle Auditor (col_af + col_ag)
+    auditor_tags = []
+    if pd.notna(col_af):
+        auditor_tags.append(mapping.get(col_af, "NT"))
+    else:
+        auditor_tags.append("NT")
+    if pd.notna(col_ag):
+        if col_ag == "obs_commercial_purpose_commercial":
+            auditor_tags = [mapping[col_ag]]  # only "Commercial"
+        else:
+            auditor_tags.append(mapping.get(col_ag, ""))
+    auditor_value = ", ".join([x for x in auditor_tags if x])
 
-def process_sheet(sheet_url):
-    # Convert Google Sheets share link to CSV export
-    match = re.search(r"/d/([a-zA-Z0-9-_]+)", sheet_url)
-    if not match:
-        return "❌ Invalid Google Sheets link."
-    
-    sheet_id = match.group(1)
-    csv_url = f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv"
-    
-    try:
-        df = pd.read_csv(csv_url)
-    except Exception as e:
-        return f"❌ Error reading sheet: {e}"
+    # Special rule: SIP always at end
+    if "SIP" in auditor_tags and len(auditor_tags) > 1:
+        auditor_tags = [x for x in auditor_tags if x != "SIP"] + ["SIP"]
+        auditor_value = ", ".join(auditor_tags)
+
+    # Highlighting logic
+    if tm_value == auditor_value:
+        tm_display = f'<span style="color:green;font-weight:bold">{tm_value}</span>'
+        auditor_display = f'<span style="color:green;font-weight:bold">{auditor_value}</span>'
+    else:
+        tm_display = f'<span style="color:red;font-weight:bold">{tm_value}</span>'
+        auditor_display = f'<span style="color:red;font-weight:bold">{auditor_value}</span>'
+
+    # Rationale (col_cc)
+    rationale = col_cc if pd.notna(col_cc) else ""
+
+    # Format final output
+    output = (
+        f"{name}<br>"
+        f"job id: #{job_id}<br>"
+        f"TM: {tm_display}<br>"
+        f"Auditor: {auditor_display}<br><br>"
+        f"Rationale: {rationale}"
+    )
+    return output
+
+def generate_output(selected_name):
+    person_data = df[df["BX"] == selected_name]  # column BX = Names
+    results = []
+    for _, row in person_data.iterrows():
+        result = process_row(
+            row["BX"],   # Name
+            row["A"],    # Job ID
+            row["R"],    # TM column
+            row["AF"],   # Auditor column
+            row["AG"],   # Auditor issue/commercial
+            row["CC"]    # Rationale
+        )
+        results.append(result)
+    return "<br><br>".join(results)
 
-    outputs = []
-    for _, row in df.iterrows():
-        name = row.get("Full Name", "")
-        job_id = row.get("job_id", "")
-        
-        # TM (from R)
-        tm = process_tags(row.get("Combined", ""))
-        
-        # Auditor: gather all AF–AW columns
-        auditor_tags = []
-        for col in df.columns:
-            if col.startswith("A"):  # AF, AG, AH...
-                auditor_tags.append(str(row[col]))
-        auditor = process_tags(", ".join(auditor_tags))
-        
-        # Rule: if both TM and Auditor are blank → NT
-        if not tm.strip():
-            tm = "NT"
-        if not auditor.strip():
-            auditor = "NT"
-        
-        # Column CC = rationale (fixed index approach)
-        # CC = 81st column (A=0, B=1, ..., CC=80)
-        rationale = ""
-        try:
-            rationale = row.iloc[80]  # 0-based index for CC
-        except Exception:
-            rationale = ""
-        
-        rationale_text = f"\n\nRationale: {rationale}" if pd.notna(rationale) and str(rationale).strip() else ""
-        
-        # Final formatted text
-        text = f"""{name}
-job id: {job_id}
-TM: {tm}
-Auditor: {auditor}{rationale_text}"""
-        
-        outputs.append(text)
+# Gradio Interface
+names = df["BX"].dropna().unique().tolist()
 
-    return "\n\n---\n\n".join(outputs)
+with gr.Blocks() as demo:
+    gr.Markdown("### Job Review Tool")
+    with gr.Row():
+        name_dropdown = gr.Dropdown(choices=names, label="Select Name")
+    output_html = gr.HTML()
 
-# Gradio App
-demo = gr.Interface(
-    fn=process_sheet,
-    inputs=gr.Textbox(label="Google Sheets Link", placeholder="Paste Google Sheets link here"),
-    outputs=gr.Textbox(label="Formatted Output", lines=25),
-    title="Google Sheets Formatter",
-    description="Paste your Google Sheets link (make sure it's shared as 'Anyone with the link can view')."
-)
+    name_dropdown.change(fn=generate_output, inputs=name_dropdown, outputs=output_html)
 
 if __name__ == "__main__":
     demo.launch()