Update src/app_job_copy_1.py

src/app_job_copy_1.py

@@ -377,6 +377,205 @@ def main():
         st.error(f"Error processing files or data: {e}")
     st.divider()
     
+# def display_job_selection(jobs_df, candidates_df, sh):
+#     st.subheader("Select a job to view potential matches")
+#     job_options = [f"{row['Role']} at {row['Company']}" for _, row in jobs_df.iterrows()]
+
+#     if 'last_selected_job_index' not in st.session_state:
+#         st.session_state.last_selected_job_index = 0
+
+#     selected_job_index = st.selectbox(
+#         "Jobs:",
+#         range(len(job_options)),
+#         format_func=lambda x: job_options[x],
+#         key="job_selectbox"
+#     )
+
+#     if selected_job_index != st.session_state.last_selected_job_index:
+#         old_job_key = st.session_state.last_selected_job_index
+#         job_processed_key = f"job_{old_job_key}_processed_successfully"
+#         job_is_processing_key = f"job_{old_job_key}_is_currently_processing"
+
+#         if job_processed_key in st.session_state:
+#             st.session_state.pop(job_processed_key)
+#         if job_is_processing_key in st.session_state:
+#             st.session_state.pop(job_is_processing_key)
+
+#         if 'Selected_Candidates' in st.session_state and old_job_key in st.session_state.Selected_Candidates:
+#             st.session_state.Selected_Candidates.pop(old_job_key)
+
+#         st.session_state.last_selected_job_index = selected_job_index
+#         st.session_state.stop_processing_flag = False
+#         st.cache_data.clear()
+#         st.rerun()
+
+#     job_row = jobs_df.iloc[selected_job_index]
+#     job_row_stack = parse_tech_stack(job_row["Tech Stack"])
+
+#     col_job_details_display, _ = st.columns([2, 1])
+#     with col_job_details_display:
+#         st.subheader(f"Job Details: {job_row['Role']}")
+#         job_details_dict = {
+#             "Company": job_row["Company"],
+#             "Role": job_row["Role"],
+#             "Description": job_row.get("One liner", "N/A"),
+#             "Locations": job_row.get("Locations", "N/A"),
+#             "Industry": job_row.get("Industry", "N/A"),
+#             "Tech Stack": display_tech_stack(job_row_stack)
+#         }
+#         for key, value in job_details_dict.items():
+#             st.markdown(f"**{key}:** {value}")
+
+#     job_processed_key = f"job_{selected_job_index}_processed_successfully"
+#     job_is_processing_key = f"job_{selected_job_index}_is_currently_processing"
+#     st.session_state.setdefault(job_processed_key, False)
+#     st.session_state.setdefault(job_is_processing_key, False)
+
+#     sheet_name = f"{job_row['Role']} at {job_row['Company']}".strip()[:100]
+#     worksheet_exists = False
+#     existing_candidates_from_sheet = []
+#     try:
+#         cand_ws = sh.worksheet(sheet_name)
+#         worksheet_exists = True
+#         data = cand_ws.get_all_values()
+#         if len(data) > 1:
+#             existing_candidates_from_sheet = data
+#     except Exception:
+#         pass
+
+#     if not st.session_state[job_processed_key] or existing_candidates_from_sheet:
+#         col_find, col_stop = st.columns(2)
+#         with col_find:
+#             if st.button("Find Matching Candidates for this Job", key=f"find_btn_{selected_job_index}",
+#                          disabled=st.session_state[job_is_processing_key]):
+#                 if not os.environ.get("OPENAI_API_KEY") or st.session_state.llm_chain is None:
+#                     st.error("OpenAI API key not set or LLM not initialized.")
+#                 else:
+#                     st.session_state[job_is_processing_key] = True
+#                     st.session_state.stop_processing_flag = False
+#                     st.session_state.Selected_Candidates[selected_job_index] = []
+#                     st.session_state[job_processed_key] = False
+#                     st.rerun()
+#         with col_stop:
+#             if st.session_state[job_is_processing_key]:
+#                 if st.button("STOP Processing", key=f"stop_btn_{selected_job_index}"):
+#                     st.session_state.stop_processing_flag = True
+#                     st.cache_data.clear()
+#                     st.warning("Stop request sent. Processing will halt shortly.")
+#                     st.rerun()
+
+#     if st.session_state[job_is_processing_key]:
+#         with st.spinner(f"Processing candidates for {job_row['Role']} at {job_row['Company']}..."):
+#             processed_list = process_candidates_for_job(job_row, candidates_df, st.session_state.llm_chain)
+#         st.session_state[job_is_processing_key] = False
+
+#         if not st.session_state.get('stop_processing_flag', False):
+#             if processed_list:
+#                 processed_list.sort(key=lambda x: x.get("Fit Score", 0.0), reverse=True)
+#                 st.session_state.Selected_Candidates[selected_job_index] = processed_list
+#                 st.session_state[job_processed_key] = True
+#                 try:
+#                     target_ws = sh.worksheet(sheet_name) if worksheet_exists else sh.add_worksheet(
+#                         title=sheet_name, rows=max(100, len(processed_list)+10), cols=20)
+#                     headers = list(processed_list[0].keys())
+#                     rows = [headers] + [[str(c.get(h, "")) for h in headers] for c in processed_list]
+#                     target_ws.clear()
+#                     target_ws.update('A1', rows)
+#                     st.success(f"Results saved to Google Sheet: '{sheet_name}'")
+#                 except Exception as e:
+#                     st.error(f"Error writing to Google Sheet '{sheet_name}': {e}")
+#             else:
+#                 st.info("No suitable candidates found after processing.")
+#                 st.session_state.Selected_Candidates[selected_job_index] = []
+#                 st.session_state[job_processed_key] = True
+#         else:
+#             st.info("Processing was stopped by user.")
+#             st.session_state[job_processed_key] = False
+#             st.session_state.Selected_Candidates[selected_job_index] = []
+#         st.session_state.pop('stop_processing_flag', None)
+#         st.rerun()
+
+#     should_display = False
+#     final_candidates = []
+#     if not st.session_state[job_is_processing_key]:
+#         if st.session_state[job_processed_key]:
+#             should_display = True
+#             final_candidates = st.session_state.Selected_Candidates.get(selected_job_index, [])
+#         elif existing_candidates_from_sheet:
+#             should_display = True
+#             headers = existing_candidates_from_sheet[0]
+#             for row in existing_candidates_from_sheet[1:]:
+#                 cand = {headers[i]: row[i] if i < len(row) else None for i in range(len(headers))}
+#                 try: cand['Fit Score'] = float(cand.get('Fit Score',0))
+#                 except: cand['Fit Score'] = 0.0
+#                 final_candidates.append(cand)
+#             final_candidates.sort(key=lambda x: x.get('Fit Score',0.0), reverse=True)
+            
+#             if not st.session_state[job_processed_key]:
+#                 st.info(f"Displaying: '{sheet_name}'.")
+#                 time.sleep(10)
+
+#     if should_display:
+#         col_title, col_copyall = st.columns([3,1])
+#         with col_title:
+#             st.subheader("Selected Candidates")
+#         with col_copyall:
+#             combined_text = ""
+#             for cand in final_candidates:
+#                 combined_text += f"Name: {cand.get('Name','N/A')}\nLinkedIn URL: {cand.get('LinkedIn','N/A')}\n\n"
+
+#             import json
+#             html = f'''
+#             <button id="copy-all-btn">📋 Copy All</button>
+#             <script>
+#             const combinedText = {json.dumps(combined_text)};
+#             document.getElementById("copy-all-btn").onclick = () => {{
+#                 navigator.clipboard.writeText(combinedText);
+#             }};
+#             </script>
+#             '''
+#             st.components.v1.html(html, height=60)
+
+#         if st.session_state.get(job_processed_key) and (
+#            st.session_state.get('total_input_tokens',0) > 0 or st.session_state.get('total_output_tokens',0) > 0):
+#             display_token_usage()
+
+#         for i, candidate in enumerate(final_candidates):
+#             score = candidate.get('Fit Score',0.0)
+#             score_display = f"{score:.3f}" if isinstance(score,(int,float)) else score
+#             exp_title = f"{i+1}. {candidate.get('Name','N/A')} (Score: {score_display})"
+#             with st.expander(exp_title):
+#                 text_copy = f"Candidate: {candidate.get('Name','N/A')}\nLinkedIn: {candidate.get('LinkedIn','N/A')}\n"
+#                 btn = f"copy_btn_job{selected_job_index}_cand{i}"
+#                 js = f'''
+#                 <script>
+#                 function copyToClipboard_{btn}() {{ navigator.clipboard.writeText(`{text_copy}`); }}
+#                 </script>
+#                 <button onclick="copyToClipboard_{btn}()">📋 Copy Details</button>
+#                 '''
+#                 cols = st.columns([0.82,0.18])
+#                 with cols[1]: st.components.v1.html(js, height=40)
+#                 with cols[0]:
+#                     st.markdown(f"**Summary:** {candidate.get('summary','N/A')}")
+#                     st.markdown(f"**Current:** {candidate.get('Current Title & Company','N/A')}")
+#                     st.markdown(f"**Education:** {candidate.get('Educational Background','N/A')}")
+#                     st.markdown(f"**Experience:** {candidate.get('Years of Experience','N/A')}")
+#                     st.markdown(f"**Location:** {candidate.get('Location','N/A')}")
+#                     if candidate.get('LinkedIn'):
+#                         st.markdown(f"**[LinkedIn Profile]({candidate['LinkedIn']})**")
+#                     if candidate.get('justification'):
+#                         st.markdown("**Justification:**")
+#                         st.info(candidate['justification'])
+
+#         if st.button("Reset and Process Again", key=f"reset_btn_{selected_job_index}"):
+#             st.session_state[job_processed_key] = False
+#             st.session_state.pop(job_is_processing_key, None)
+#             st.session_state.Selected_Candidates.pop(selected_job_index, None)
+#             st.cache_data.clear()
+#             try: sh.worksheet(sheet_name).clear()
+#             except: pass
+#             st.rerun()
+
 def display_job_selection(jobs_df, candidates_df, sh):
     st.subheader("Select a job to view potential matches")
     job_options = [f"{row['Role']} at {row['Company']}" for _, row in jobs_df.iterrows()]
@@ -391,22 +590,29 @@ def display_job_selection(jobs_df, candidates_df, sh):
         key="job_selectbox"
     )
 
+    # Clear previous job state when a new job is selected
     if selected_job_index != st.session_state.last_selected_job_index:
         old_job_key = st.session_state.last_selected_job_index
+
+        # Clear job-specific session state
         job_processed_key = f"job_{old_job_key}_processed_successfully"
         job_is_processing_key = f"job_{old_job_key}_is_currently_processing"
 
-        if job_processed_key in st.session_state:
-            st.session_state.pop(job_processed_key)
-        if job_is_processing_key in st.session_state:
-            st.session_state.pop(job_is_processing_key)
+        for key in [job_processed_key, job_is_processing_key, 'stop_processing_flag', 'total_input_tokens', 'total_output_tokens']:
+            if key in st.session_state:
+                del st.session_state[key]
 
+        # Clear selected candidates for the old job
         if 'Selected_Candidates' in st.session_state and old_job_key in st.session_state.Selected_Candidates:
-            st.session_state.Selected_Candidates.pop(old_job_key)
+            del st.session_state.Selected_Candidates[old_job_key]
 
-        st.session_state.last_selected_job_index = selected_job_index
-        st.session_state.stop_processing_flag = False
+        # Clear cached data
         st.cache_data.clear()
+
+        # Update last selected job index
+        st.session_state.last_selected_job_index = selected_job_index
+
+        # Force rerun to refresh UI
         st.rerun()
 
     job_row = jobs_df.iloc[selected_job_index]
@@ -454,7 +660,6 @@ def display_job_selection(jobs_df, candidates_df, sh):
                     st.session_state[job_is_processing_key] = True
                     st.session_state.stop_processing_flag = False
                     st.session_state.Selected_Candidates[selected_job_index] = []
-                    st.session_state[job_processed_key] = False
                     st.rerun()
         with col_stop:
             if st.session_state[job_is_processing_key]:
@@ -510,10 +715,6 @@ def display_job_selection(jobs_df, candidates_df, sh):
                 except: cand['Fit Score'] = 0.0
                 final_candidates.append(cand)
             final_candidates.sort(key=lambda x: x.get('Fit Score',0.0), reverse=True)
-            
-            if not st.session_state[job_processed_key]:
-                st.info(f"Displaying: '{sheet_name}'.")
-                time.sleep(10)
 
     if should_display:
         col_title, col_copyall = st.columns([3,1])