Update app.py

app.py

@@ -1,5 +1,5 @@
 # app.py
-# Modern Dark Mode Streamlit Application for AI Talent Screening (FINAL - Logic Fix for DataFrame Renaming)
+# Modern Dark Mode Streamlit Application for AI Talent Screening (FINAL - Remove Coloring, Increase Max Profiles to 7)
 
 import streamlit as st
 # Import necessary libraries
@@ -12,7 +12,6 @@ import time
 import pandas as pd
 import PyPDF2
 from docx import Document
-# The matplotlib import is correctly REMOVED
 import plotly.express as px # Import Plotly for stable charting
 
 # Set page config with modern dark theme and wide layout
@@ -318,7 +317,7 @@ def classify_and_summarize_batch(resume, job_description, _bert_tokenized, _t5_i
         elif detected_skills: final_summary = f"Key Skills: {', '.join(detected_skills)}"
         else: final_summary = f"Experience: {exp_match.group(0).capitalize() if exp_match else 'Unknown'}"
         
-        # Color codes based on theme
+        # Color codes based on theme (STILL NEEDED for the scorecards/tiles and CSV)
         if suitability == "Relevant": color = "#4CAF50"
         elif suitability == "Irrelevant": color = "#F44336"
         else: color = "#FFC107"
@@ -400,7 +399,7 @@ def render_sidebar():
                 - Enter the **Job Description** (JD). Be clear about required skills and experience (e.g., '5 years+').
                 
                 **2. Upload Candidates (Tab 2)**:
-                - Upload or paste up to **5 Candidate Profiles** (PDF/DOCX/Text).
+                - Upload or paste up to **7 Candidate Profiles** (PDF/DOCX/Text).  <-- **UPDATED TO 7**
                 - Profiles must contain key technical skills and explicit experience.
                 
                 **3. Run Screening**:
@@ -454,7 +453,7 @@ def main():
             
     # --- TAB 2: Manage Resumes ---
     with tab_resumes:
-        st.markdown(f"## 📁 Upload Candidate Profiles ({len(st.session_state.resumes)}/5)")
+        st.markdown(f"## 📁 Upload Candidate Profiles ({len(st.session_state.resumes)}/7)") # <-- **UPDATED TO 7**
         st.info("Upload or paste candidate text below. The AI requires **key technical skills and experience statements** to function.")
 
         # Manage resume inputs
@@ -499,7 +498,7 @@ def main():
         st.markdown("<br>", unsafe_allow_html=True)
         col_add, col_remove, _ = st.columns([1, 1, 3])
         with col_add:
-            if st.button("➕ Add Candidate Slot", use_container_width=True) and len(st.session_state.resumes) < 5:
+            if st.button("➕ Add Candidate Slot", use_container_width=True) and len(st.session_state.resumes) < 7: # <-- **UPDATED TO 7**
                 st.session_state.resumes.append("")
                 st.rerun()
         with col_remove:
@@ -642,37 +641,23 @@ def main():
             # --- Detailed Report Table ---
             st.markdown("### 📋 Detailed Screening Results")
             
-            # 1. Define the styling function.
-            def style_suitability_row(row):
-                color_column = 'Suitability_Color' 
-                if row[color_column] == '#4CAF50': # Relevant - Green
-                    return ['background-color: rgba(76, 175, 80, 0.15)'] * len(row)
-                elif row[color_column] == '#F44336': # Irrelevant/Error - Red
-                    return ['background-color: rgba(244, 67, 54, 0.15)'] * len(row)
-                elif row[color_column] == '#FFC107': # Uncertain - Yellow
-                    return ['background-color: rgba(255, 193, 7, 0.15)'] * len(row)
-                else:
-                    return [''] * len(row)
-            
-            # 2. **FIX**: Rename columns on the DataFrame before applying style.
-            display_df = results_df.rename(
+            # **FIX**: Explicitly drop the 'Suitability_Color' column to ensure it is not displayed, 
+            # and remove all cell coloring logic.
+            display_df = results_df.drop(columns=['Suitability_Color'])
+
+            # Rename columns for professional display
+            display_df = display_df.rename(
                 columns={
-                    'Data/Tech Related Skills Summary': 'PROFILE SUMMARY', 
-                    'Warning': 'FLAGGING REASON', 
-                    'Resume': 'PROFILE ID',
-                    'Suitability': 'SUITABILITY' 
+                    'Data/Tech Related Skills Summary': '**PROFILE SUMMARY**', 
+                    'Warning': '**FLAGGING REASON**', 
+                    'Resume': '**PROFILE ID**',
+                    'Suitability': '**SUITABILITY**' 
                 }
             )
 
-            # 3. Apply row styling to the renamed DataFrame.
-            styled_df = display_df.style.apply(style_suitability_row, axis=1)
-
-            # 4. Remove the internal color column from display (Fix for visible color column)
-            styled_df = styled_df.hide(subset=['Suitability_Color'], axis=1)
-
-            # 5. Display the styled DataFrame.
+            # Display the simple, unstyled DataFrame
             st.dataframe(
-                styled_df,
+                display_df,
                 use_container_width=True
             )
             
@@ -698,8 +683,7 @@ def main():
                     if st.session_state.valid_resumes:
                         fig = generate_skill_pie_chart(st.session_state.valid_resumes)
                         if fig:
-                            # Use st.plotly_chart for flicker-free display
-                            st.plotly_chart(fig, use_container_width=True) 
+                            st.plotly_chart(fig, use_container_width=True)
                         else:
                             st.info("No recognized technical skills found in the profiles for charting.")
                     else: