Floke/Brancheneinstufung2
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data_processor.py aktualisiert

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Floke
2025-08-04 17:52:51 +00:00
parent f5034ecf7a
commit f2ced4f312
1 changed files with 8 additions and 12 deletions
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data_processor.py
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@@ -492,30 +492,26 @@ class DataProcessor:
f"Zeile {row_num_in_sheet}: Fuehre CHATGPT Evaluationen & Plausi aus (Grund: {grund_message_chat})...")
# --- 3a. Branchen-Einstufung ---
self.logger.info(f" Zeile {row_num_in_sheet}: Starte Branchen-Einstufung ueber ChatGPT...")
self.logger.info(f" Zeile {row_num_in_sheet}: Starte Branchen-Einstufung 2.0 ueber ChatGPT...")
try:
# schema_data wird hier aus der Instanz-Variable übergeben
# Rufe die neue, kontextbasierte Funktion mit den korrekten Parametern auf
branch_result = evaluate_branche_chatgpt(
crm_branche,
crm_beschreibung,
final_wiki_data.get('branche', 'k.A.'),
final_wiki_data.get('categories', 'k.A.'),
website_summary,
schema_data=self.schema_data
company_name=company_name,
website_summary=website_summary,
wiki_absatz=final_wiki_data.get('first_paragraph', 'k.A.')
)
# Das Ergebnis von Version 2.0 ist bereits ein sauberes Dictionary
updates.append({'range': f'{_get_col_letter(get_col_idx("Chat Vorschlag Branche") + 1)}{row_num_in_sheet}', 'values': [[branch_result.get('branch', 'FEHLER')]]})
updates.append({'range': f'{_get_col_letter(get_col_idx("Chat Branche Konfidenz") + 1)}{row_num_in_sheet}', 'values': [[branch_result.get('confidence', 'N/A')]]})
updates.append({'range': f'{_get_col_letter(get_col_idx("Chat Konsistenz Branche") + 1)}{row_num_in_sheet}', 'values': [[branch_result.get('consistency', 'error')]]})
updates.append({'range': f'{_get_col_letter(get_col_idx("Chat Konsistenz Branche") + 1)}{row_num_in_sheet}', 'values': [['V2.0']]}) # Markierung, dass V2.0 lief
updates.append({'range': f'{_get_col_letter(get_col_idx("Chat Begruendung Abweichung Branche") + 1)}{row_num_in_sheet}', 'values': [[branch_result.get('justification', 'k.A.')]]})
except Exception as e_branch_eval:
self.logger.error(f"FEHLER bei Branchen-Einstufung für Zeile {row_num_in_sheet}: {e_branch_eval}")
# Fehlerwerte in die Spalten schreiben
self.logger.error(f"FEHLER bei Branchen-Einstufung für Zeile {row_num_in_sheet}: {e_branch_eval}", exc_info=True)
error_updates = [
{"key": "Chat Vorschlag Branche", "value": "FEHLER_CALL"},
{"key": "Chat Branche Konfidenz", "value": "N/A"},
{"key": "Chat Konsistenz Branche", "value": "error"},
{"key": "Chat Begruendung Abweichung Branche", "value": str(e_branch_eval)[:100]}
]
for item in error_updates: