Restore v1.7.9 Parsing Logic
- FIX: `evaluate_branche_chatgpt` in `helpers.py` verwendet nun wieder die robuste Parsing- und Fallback-Logik aus der stabilen Version v1.7.9. - Dies stellt sicher, dass ChatGPT-Antworten zuverlässiger interpretiert werden.
This commit is contained in:
194
helpers.py
194
helpers.py
@@ -894,180 +894,116 @@ def summarize_batch_openai(tasks_data):
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# 9. OPENAI API WRAPPER (BRANCH EVALUATION)
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# 9. OPENAI API WRAPPER (BRANCH EVALUATION)
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# ==============================================================================
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# ==============================================================================
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@retry_on_failure
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@retry_on_failure
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@retry_on_failure
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def evaluate_branche_chatgpt(crm_branche, beschreibung, wiki_branche, wiki_kategorien, website_summary):
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def evaluate_branche_chatgpt(crm_branche, beschreibung, wiki_branche, wiki_kategorien, website_summary):
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"""
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"""
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Bewertet die Branche eines Unternehmens anhand verschiedener textueller Inputs
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Bewertet die Branche eines Unternehmens.
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mittels OpenAI und gibt ein strukturiertes Dictionary zurück.
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NUTZT DIE BEWÄHRTE PARSING-LOGIK AUS v1.7.9.
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"""
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"""
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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from config import TARGET_SCHEMA_STRING, FOCUS_BRANCHES_PROMPT_PART, ALLOWED_TARGET_BRANCHES
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from config import TARGET_SCHEMA_STRING, FOCUS_BRANCHES_PROMPT_PART, ALLOWED_TARGET_BRANCHES
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# Lazy Loading des Branchenschemas
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if not ALLOWED_TARGET_BRANCHES:
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if not ALLOWED_TARGET_BRANCHES:
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logger.warning("Branchenschema nicht geladen. Versuche es jetzt zu laden...")
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logger.warning("Branchenschema nicht geladen. Versuche es jetzt zu laden...")
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if not initialize_target_schema():
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if not initialize_target_schema():
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logger.critical("FEHLER in evaluate_branche_chatgpt: Ziel-Branchenschema konnte auch bei Bedarf nicht geladen werden. Breche Evaluation ab.")
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logger.critical("FEHLER in evaluate_branche_chatgpt: Schema konnte nicht geladen werden.")
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return {
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return {"branch": "FEHLER - SCHEMA FEHLT", "confidence": "N/A", "consistency": "error_schema_missing", "justification": "Fehler: Schema nicht geladen."}
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"branch": "FEHLER - SCHEMA FEHLT",
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"confidence": "N/A",
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"consistency": "error_schema_missing",
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"justification": "Fehler: Ziel-Branchenschema konnte nicht geladen werden."
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}
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allowed_branches_lookup = {b.lower(): b for b in ALLOWED_TARGET_BRANCHES}
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allowed_branches_lookup = {b.lower(): b for b in ALLOWED_TARGET_BRANCHES}
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prompt_parts = [TARGET_SCHEMA_STRING, FOCUS_BRANCHES_PROMPT_PART]
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prompt_parts = [TARGET_SCHEMA_STRING, FOCUS_BRANCHES_PROMPT_PART]
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prompt_parts.append("\nOrdne das Unternehmen anhand folgender Angaben exakt einer Branche des Ziel-Branchenschemas (Kurzformen) zu.")
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prompt_parts.append("\nOrdne das Unternehmen anhand folgender Angaben exakt einer Branche des Ziel-Branchenschemas (Kurzformen) zu.")
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prompt_parts.append("Gib zusätzlich eine Konfidenz für deine Branchenwahl an (Hoch, Mittel oder Niedrig).")
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prompt_parts.append("Gib zusätzlich eine Konfidenz für deine Branchenwahl an (Hoch, Mittel oder Niedrig).")
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if crm_branche and str(crm_branche).strip() and str(crm_branche).strip().lower() != "k.a.":
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# --- Prompt-Zusammenstellung (unverändert) ---
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prompt_parts.append(f"- CRM-Branche (Referenz): {str(crm_branche).strip()}")
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if crm_branche and str(crm_branche).strip() and str(crm_branche).strip().lower() != "k.a.": prompt_parts.append(f"- CRM-Branche (Referenz): {str(crm_branche).strip()}")
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if wiki_branche and str(wiki_branche).strip() and str(wiki_branche).strip().lower() != "k.a.":
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if wiki_branche and str(wiki_branche).strip() and str(wiki_branche).strip().lower() != "k.a.":
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if beschreibung and str(beschreibung).strip() and str(beschreibung).strip().lower() != "k.a.":
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if beschreibung and str(beschreibung).strip() and str(beschreibung).strip().lower() != "k.a.": prompt_parts.append(f"- Beschreibung (CRM): {str(beschreibung).strip()[:500]}...")
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prompt_parts.append(f"- Beschreibung (CRM): {str(beschreibung).strip()[:500]}...")
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if website_summary and str(website_summary).strip() and str(website_summary).strip().lower() != "k.a." and not str(website_summary).strip().startswith("k.A. (Fehler"): prompt_parts.append(f"- Website-Zusammenfassung: {str(website_summary).strip()[:500]}...")
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if website_summary and str(website_summary).strip() and str(website_summary).strip().lower() != "k.a." and not str(website_summary).strip().startswith("k.A. (Fehler"):
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prompt_parts.append(f"- Website-Zusammenfassung: {str(website_summary).strip()[:500]}...")
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prompt_parts.append(f"- Wikipedia-Branche: {str(wiki_branche).strip()[:300]}...")
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prompt_parts.append(f"- Wikipedia-Branche: {str(wiki_branche).strip()[:300]}...")
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if wiki_kategorien and str(wiki_kategorien).strip() and str(wiki_kategorien).strip().lower() != "k.a.":
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if wiki_kategorien and str(wiki_kategorien).strip() and str(wiki_kategorien).strip().lower() != "k.a.": prompt_parts.append(f"- Wikipedia-Kategorien: {str(wiki_kategorien).strip()[:500]}...")
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prompt_parts.append(f"- Wikipedia-Kategorien: {str(wiki_kategorien).strip()[:500]}...")
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else:
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else:
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logger.debug("evaluate_branche_chatgpt: Keine validen Wiki-Daten, nutze Website-Zusammenfassung als primäre Beschreibung (falls vorhanden).")
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logger.debug("evaluate_branche_chatgpt: Keine validen Wiki-Daten, nutze Website-Zusammenfassung als primäre Beschreibung.")
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if website_summary and str(website_summary).strip() and str(website_summary).strip().lower() != "k.a." and not str(website_summary).strip().startswith("k.A. (Fehler"):
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if website_summary and str(website_summary).strip() and str(website_summary).strip().lower() != "k.a." and not str(website_summary).strip().startswith("k.A. (Fehler"): prompt_parts.append(f"- Website-Zusammenfassung (als Hauptbeschreibung): {str(website_summary).strip()[:800]}...")
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prompt_parts.append(f"- Website-Zusammenfassung (als Hauptbeschreibung): {str(website_summary).strip()[:800]}...")
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elif beschreibung and str(beschreibung).strip() and str(beschreibung).strip().lower() != "k.a.": prompt_parts.append(f"- Beschreibung (CRM, als Hauptbeschreibung): {str(beschreibung).strip()[:800]}...")
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elif beschreibung and str(beschreibung).strip() and str(beschreibung).strip().lower() != "k.a.":
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prompt_parts.append(f"- Beschreibung (CRM, als Hauptbeschreibung): {str(beschreibung).strip()[:800]}...")
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if len(prompt_parts) < (3 + (1 if FOCUS_BRANCHES_PROMPT_PART else 0)):
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logger.warning("Warnung in evaluate_branche_chatgpt: Zu wenige Informationen für Branchenevaluierung.")
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crm_short_branch_for_fallback = "k.A."
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if crm_branche and isinstance(crm_branche, str) and crm_branche.strip().lower() != "k.a.":
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crm_short_branch_for_fallback = crm_branche.strip()
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return {
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"branch": crm_short_branch_for_fallback if crm_short_branch_for_fallback.lower() != "k.a." else "FEHLER",
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"confidence": "N/A",
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"consistency": "error_no_info",
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"justification": "Fehler: Zu wenige Informationen fuer eine Einschaetzung"
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}
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prompt = "\n".join(filter(None, prompt_parts))
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prompt = "\n".join(filter(None, prompt_parts))
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chat_response = None
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try:
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try:
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chat_response = call_openai_chat(prompt, temperature=0.0)
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chat_response = call_openai_chat(prompt, temperature=0.0)
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if not chat_response:
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if not chat_response: raise APIError("Keine Antwort von OpenAI erhalten.")
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raise APIError("Keine Antwort von OpenAI erhalten fuer Branchenevaluation.")
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except Exception as e:
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except Exception as e:
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logger.error(f"Endgueltiger FEHLER beim OpenAI-Aufruf fuer Branchenevaluation: {e}")
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logger.error(f"Endgueltiger FEHLER beim OpenAI-Aufruf fuer Branchenevaluation: {e}")
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crm_short_branch_for_fallback = "k.A."
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return {"branch": "FEHLER API", "confidence": "N/A", "consistency": "error_api_failed", "justification": f"Fehler API: {str(e)[:100]}"}
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if crm_branche and isinstance(crm_branche, str) and crm_branche.strip().lower() != "k.a.":
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crm_short_branch_for_fallback = crm_branche.strip()
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return {
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"branch": crm_short_branch_for_fallback if crm_short_branch_for_fallback.lower() != "k.a." else "FEHLER API",
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"confidence": "N/A",
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"consistency": "error_api_failed",
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"justification": f"Fehler API: {str(e)[:100]}"
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}
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# --- v1.7.9 PARSING LOGIK WIEDERHERGESTELLT ---
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lines = chat_response.strip().split("\n")
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lines = chat_response.strip().split("\n")
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result = {
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result = {"confidence": "N/A", "justification": ""}
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"branch": None,
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"confidence": "N/A",
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"consistency": None,
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"justification": ""
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}
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suggested_branch = ""
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suggested_branch = ""
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parsed_branch = False
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parsed_branch = False
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parsed_confidence = False
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for line in lines:
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for line in lines:
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line_lower = line.lower().strip()
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line_lower = line.lower()
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# Sucht nach "branche:", "branchenzuordnung:", "branchenwahl:" etc. in der Zeile
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if line_lower.startswith("branche:"):
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if "branche:" in line_lower or "branchenzuordnung:" in line_lower or "branchenwahl:" in line_lower:
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suggested_branch = line.split(":", 1)[1].strip()
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suggested_branch = line.split(":", 1)[1].strip().strip('"\'')
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parsed_branch = True
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parsed_branch = True
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elif line_lower.startswith("konfidenz:"):
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break # Wichtig: Schleife beenden, sobald der Treffer da ist
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confidence_text = line.split(":", 1)[1].strip().strip('"\'')
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valid_confidences = ["hoch", "mittel", "niedrig"]
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# Fallback, wenn "Branche:" nicht gefunden wurde (Logik aus v1.7.9)
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if confidence_text.lower() in valid_confidences:
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if not parsed_branch and lines:
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result["confidence"] = confidence_text.capitalize()
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suggested_branch = lines[0].strip() # Nimm die erste Zeile als Vorschlag
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else:
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logger.warning(f"Konnte 'Branche:' nicht finden. Interpretiere erste Zeile als Vorschlag: '{suggested_branch}'")
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result["confidence"] = "N/A (Ungueltig)"
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parsed_confidence = True
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# Extrahiere Konfidenz und Begründung separat
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for line in lines:
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line_lower = line.lower()
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if line_lower.startswith("konfidenz:"):
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result["confidence"] = line.split(":", 1)[1].strip()
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elif line_lower.startswith("begruendung:"):
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elif line_lower.startswith("begruendung:"):
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result["justification"] = line.split(":", 1)[1].strip()
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result["justification"] = line.split(":", 1)[1].strip()
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if not parsed_branch:
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if not suggested_branch:
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# Fallback, wenn das Schlüsselwort nicht gefunden wurde, aber die Antwort nur aus einem Wort besteht
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logger.error(f"Fehler: Konnte keine Branche aus der Antwort extrahieren: {chat_response[:200]}")
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if len(lines) == 1 and len(lines[0].split()) < 4:
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return {"branch": "FEHLER PARSING", "confidence": "N/A", "consistency": "error_parsing", "justification": f"Antwort leer oder unklar: {chat_response[:100]}"}
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suggested_branch = lines[0].strip().strip('"\'')
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logger.warning(f"Konnte 'Branche:' nicht finden, nehme die ganze Zeile als Branchenvorschlag: '{suggested_branch}'")
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else:
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logger.error(f"Fehler: Konnte 'Branche:' nicht aus Antwort parsen: {chat_response[:200]}...")
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return {"branch": "FEHLER PARSING", "confidence": "N/A", "consistency": "error_parsing", "justification": f"Antwortformat unerwartet: {chat_response[:100]}"}
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# Validierung und intelligenter Fallback
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# --- Validierung und intelligenter Fallback (leicht angepasst aus v1.9.1) ---
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final_branch = None
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final_branch = None
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suggested_branch_lower = suggested_branch.lower()
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suggested_branch_lower = suggested_branch.lower()
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# 1. Exakter Match
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if suggested_branch_lower in allowed_branches_lookup:
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if suggested_branch_lower in allowed_branches_lookup:
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final_branch = allowed_branches_lookup[suggested_branch_lower]
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final_branch = allowed_branches_lookup[suggested_branch_lower]
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result["consistency"] = "pending_comparison"
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logger.debug(f"KI-Vorschlag '{suggested_branch}' ist ein exakter Match.")
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else:
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else:
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# 2. Substring-Match für den Vorschlag
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# Substring-Match für KI-Vorschlag
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best_suggestion_match = None
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best_suggestion_match = next((val for key, val in allowed_branches_lookup.items() if suggested_branch_lower in key), None)
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for allowed_key, allowed_value in allowed_branches_lookup.items():
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if suggested_branch_lower in allowed_key:
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best_suggestion_match = allowed_value
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break
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if best_suggestion_match:
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if best_suggestion_match:
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final_branch = best_suggestion_match
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final_branch = best_suggestion_match
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result["consistency"] = "pending_comparison"
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logger.info(f"KI-Vorschlag '{suggested_branch}' per Substring zu '{final_branch}' gemappt.")
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result["justification"] = f"Info: KI-Vorschlag '{suggested_branch}' zu '{final_branch}' gemappt. " + result.get("justification", "")
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if final_branch:
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result["branch"] = final_branch
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# Konsistenzprüfung (ok/X)
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if final_branch.lower() == crm_branche.strip().lower():
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result["consistency"] = "ok"
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else:
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else:
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# 3. Fallback auf CRM-Branche mit Substring-Match
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result["consistency"] = "X"
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logger.debug(f"Vorschlag '{suggested_branch}' nicht im Schema. Prüfe Fallback auf CRM-Branche...")
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else:
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crm_short_branch = crm_branche.strip()
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# Fallback auf CRM-Branche
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crm_short_branch_lower = crm_short_branch.lower()
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logger.debug(f"Vorschlag '{suggested_branch}' nicht im Schema. Prüfe Fallback auf CRM-Branche...")
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best_crm_fallback = None
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crm_short_branch_lower = crm_branche.strip().lower()
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if crm_short_branch_lower and crm_short_branch_lower != 'k.a.':
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best_crm_fallback = next((val for key, val in allowed_branches_lookup.items() if crm_short_branch_lower in key and crm_short_branch_lower), None)
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for allowed_key, allowed_value in allowed_branches_lookup.items():
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if crm_short_branch_lower in allowed_key:
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if best_crm_fallback:
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best_crm_fallback = allowed_value
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result["branch"] = best_crm_fallback
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break
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result["consistency"] = "fallback_crm_substring"
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result["justification"] = f"Fallback: KI-Vorschlag ungültig. CRM-Branche '{crm_branche}' passt zu Schema '{best_crm_fallback}'."
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if best_crm_fallback:
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result["confidence"] = "N/A (Fallback)"
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final_branch = best_crm_fallback
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else:
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result["consistency"] = "fallback_crm_substring"
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result["branch"] = "FEHLER - UNGUELTIGE ZUWEISUNG"
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result["justification"] = f"Fallback: KI-Vorschlag '{suggested_branch}' ungültig. CRM-Branche '{crm_short_branch}' passt zu '{final_branch}'."
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result["consistency"] = "fallback_invalid"
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result["confidence"] = "N/A (Fallback)"
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result["justification"] = f"Fehler: Weder KI-Vorschlag ('{suggested_branch}') noch CRM-Branche ('{crm_branche}') passen zum Schema."
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else:
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result["confidence"] = "N/A (Fehler)"
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final_branch = "FEHLER - UNGUELTIGE ZUWEISUNG"
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result["consistency"] = "fallback_invalid"
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result["justification"] = f"Fehler: Weder KI-Vorschlag ('{suggested_branch}') noch CRM-Branche ('{crm_short_branch}') passen zum Schema."
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result["confidence"] = "N/A (Fehler)"
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result["branch"] = final_branch if final_branch else "FEHLER"
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logger.debug(f"Finale Branch-Evaluation: {result}")
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crm_branch_to_compare = crm_branche.strip() if crm_branche and isinstance(crm_branche, str) else "k.A."
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if result["consistency"] == "pending_comparison" and result["branch"] != "FEHLER" and not result["branch"].startswith("FEHLER"):
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if result["branch"].lower() == crm_branch_to_compare.lower():
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result["consistency"] = "ok"
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else:
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result["consistency"] = "X"
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if result["consistency"] == "pending_comparison":
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result["consistency"] = "error_comparison_failed"
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elif result["consistency"] is None:
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result["consistency"] = "error_unknown_state"
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logger.debug(f"Finale Branch-Evaluation Ergebnis: Branch='{result.get('branch')}', Confidence='{result.get('confidence')}', Consistency='{result.get('consistency')}', Justification='{result.get('justification', '')[:100]}...'")
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return result
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return result
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# ==============================================================================
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# ==============================================================================
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