Update src/app_job_copy_1.py

src/app_job_copy_1.py

@@ -377,205 +377,6 @@ 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()]