[2ff88f42] multiplikation vorbereitet
multiplikation vorbereitet
This commit is contained in:
22
company-explorer/backend/scripts/check_mappings.py
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22
company-explorer/backend/scripts/check_mappings.py
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import sys
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import os
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# Setup Environment
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sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
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from backend.database import SessionLocal, JobRoleMapping
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def check_mappings():
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db = SessionLocal()
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count = db.query(JobRoleMapping).count()
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print(f"Total JobRoleMappings: {count}")
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examples = db.query(JobRoleMapping).limit(5).all()
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for ex in examples:
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print(f" - {ex.pattern} -> {ex.role}")
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db.close()
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if __name__ == "__main__":
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check_mappings()
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162
company-explorer/backend/scripts/generate_matrix.py
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162
company-explorer/backend/scripts/generate_matrix.py
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import sys
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import os
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import json
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import argparse
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from typing import List
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# Setup Environment
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sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
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from backend.database import SessionLocal, Industry, Persona, MarketingMatrix
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# --- Configuration ---
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MODEL = "gpt-4o"
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def generate_prompt(industry: Industry, persona: Persona) -> str:
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"""
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Builds the prompt for the AI to generate the marketing texts.
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Combines Industry context with Persona specific pains/gains.
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"""
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# Safely load JSON lists
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try:
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persona_pains = json.loads(persona.pains) if persona.pains else []
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persona_gains = json.loads(persona.gains) if persona.gains else []
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except:
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persona_pains = [persona.pains] if persona.pains else []
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persona_gains = [persona.gains] if persona.gains else []
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industry_pains = industry.pains if industry.pains else "Allgemeine Effizienzprobleme"
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prompt = f"""
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Du bist ein erfahrener B2B-Copywriter für Robotik-Lösungen (Reinigung, Transport, Service).
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Ziel: Erstelle personalisierte E-Mail-Textbausteine für einen Outreach.
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--- KONTEXT ---
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ZIELBRANCHE: {industry.name}
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BRANCHEN-KONTEXT: {industry.description or 'Keine spezifische Beschreibung'}
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BRANCHEN-PAINS: {industry_pains}
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ZIELPERSON (ARCHETYP): {persona.name}
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PERSÖNLICHE PAINS (Herausforderungen):
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{chr(10).join(['- ' + p for p in persona_pains])}
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GEWÜNSCHTE GAINS (Ziele):
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{chr(10).join(['- ' + g for g in persona_gains])}
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--- AUFGABE ---
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Erstelle ein JSON-Objekt mit genau 3 Textbausteinen.
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Tonalität: Professionell, lösungsorientiert, auf den Punkt. Keine Marketing-Floskeln ("Game Changer").
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1. "subject": Betreffzeile (Max 6 Wörter). Muss neugierig machen und einen Pain adressieren.
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2. "intro": Einleitungssatz (1-2 Sätze). Verbinde die Branchen-Herausforderung mit der persönlichen Rolle des Empfängers. Zeige Verständnis für seine Situation.
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3. "social_proof": Ein Satz, der Vertrauen aufbaut. Nenne generische Erfolge (z.B. "Unternehmen in der {industry.name} senken so ihre Kosten um 15%"), da wir noch keine spezifischen Logos nennen dürfen.
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--- FORMAT ---
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{{
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"subject": "...",
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"intro": "...",
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"social_proof": "..."
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}}
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"""
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return prompt
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def mock_openai_call(prompt: str):
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"""Simulates an API call for dry runs."""
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print(f"\n--- [MOCK] GENERATING PROMPT ---\n{prompt[:300]}...\n--------------------------------")
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return {
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"subject": "[MOCK] Effizienzsteigerung in der Produktion",
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"intro": "[MOCK] Als Produktionsleiter wissen Sie, wie teuer Stillstand ist. Unsere Roboter helfen.",
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"social_proof": "[MOCK] Ähnliche Betriebe sparten 20% Kosten."
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}
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def real_openai_call(prompt: str):
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# This would link to the actual OpenAI client
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# For now, we keep it simple or import from a lib
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import openai
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from backend.config import settings
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if not settings.OPENAI_API_KEY:
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raise ValueError("OPENAI_API_KEY not set")
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client = openai.OpenAI(api_key=settings.OPENAI_API_KEY)
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response = client.chat.completions.create(
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model=MODEL,
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response_format={"type": "json_object"},
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7
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)
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return json.loads(response.choices[0].message.content)
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def run_matrix_generation(dry_run: bool = True, force: bool = False):
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db = SessionLocal()
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try:
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industries = db.query(Industry).all()
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personas = db.query(Persona).all()
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print(f"Found {len(industries)} Industries and {len(personas)} Personas.")
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print(f"Mode: {'DRY RUN (No API calls, no DB writes)' if dry_run else 'LIVE'}")
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total_combinations = len(industries) * len(personas)
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processed = 0
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for ind in industries:
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for pers in personas:
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processed += 1
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print(f"[{processed}/{total_combinations}] Check: {ind.name} x {pers.name}")
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# Check existing
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existing = db.query(MarketingMatrix).filter(
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MarketingMatrix.industry_id == ind.id,
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MarketingMatrix.persona_id == pers.id
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).first()
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if existing and not force:
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print(f" -> Skipped (Already exists)")
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continue
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# Generate
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prompt = generate_prompt(ind, pers)
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if dry_run:
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result = mock_openai_call(prompt)
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else:
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try:
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result = real_openai_call(prompt)
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except Exception as e:
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print(f" -> API ERROR: {e}")
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continue
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# Write to DB (only if not dry run)
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if not dry_run:
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if not existing:
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new_entry = MarketingMatrix(
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industry_id=ind.id,
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persona_id=pers.id,
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subject=result.get("subject"),
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intro=result.get("intro"),
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social_proof=result.get("social_proof")
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)
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db.add(new_entry)
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print(f" -> Created new entry.")
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else:
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existing.subject = result.get("subject")
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existing.intro = result.get("intro")
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existing.social_proof = result.get("social_proof")
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print(f" -> Updated entry.")
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db.commit()
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except Exception as e:
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print(f"Error: {e}")
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finally:
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db.close()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--live", action="store_true", help="Actually call OpenAI and write to DB")
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parser.add_argument("--force", action="store_true", help="Overwrite existing matrix entries")
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args = parser.parse_args()
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run_matrix_generation(dry_run=not args.live, force=args.force)
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123
company-explorer/backend/scripts/seed_marketing_data.py
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123
company-explorer/backend/scripts/seed_marketing_data.py
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@@ -0,0 +1,123 @@
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import sys
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import os
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import json
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# Setup Environment to import backend modules
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sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
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from backend.database import SessionLocal, Persona, JobRoleMapping
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def seed_archetypes():
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db = SessionLocal()
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print("Seeding Strategic Archetypes (Pains & Gains)...")
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# --- 1. The 4 Strategic Archetypes ---
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# Based on user input and synthesis of previous specific roles
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archetypes = [
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{
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"name": "Operativer Entscheider",
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"pains": [
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"Personelle Unterbesetzung und hohe Fluktuation führen zu Überstunden und Qualitätsmängeln.",
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"Manuelle, wiederkehrende Prozesse binden wertvolle Ressourcen und senken die Effizienz.",
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"Sicherstellung gleichbleibend hoher Standards (Hygiene/Service) ist bei Personalmangel kaum möglich."
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],
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"gains": [
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"Spürbare Entlastung des Teams von Routineaufgaben (20-40%).",
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"Garantierte, gleichbleibend hohe Ausführungsqualität rund um die Uhr.",
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"Stabilisierung der operativen Abläufe unabhängig von kurzfristigen Personalausfällen."
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]
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},
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{
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"name": "Infrastruktur-Verantwortlicher",
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"pains": [
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"Integration neuer Systeme in bestehende Gebäude/IT ist oft komplex und risikobehaftet.",
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"Sorge vor hohen Ausfallzeiten und aufwändiger Fehlerbehebung ohne internes Spezialwissen.",
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"Unklare Wartungsaufwände und Schnittstellenprobleme (WLAN, Aufzüge, Türen)."
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],
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"gains": [
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"Reibungslose, fachgerechte Integration in die bestehende Infrastruktur.",
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"Maximale Betriebssicherheit durch proaktives Monitoring und schnelle Reaktionszeiten.",
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"Volle Transparenz über Systemstatus und Wartungsbedarf."
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]
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},
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{
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"name": "Wirtschaftlicher Entscheider",
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"pains": [
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"Steigende operative Kosten (Personal, Material) drücken auf die Margen.",
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"Unklare Amortisation (ROI) und Risiko von Fehlinvestitionen bei neuen Technologien.",
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"Intransparente Folgekosten (TCO) über die Lebensdauer der Anlagen."
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],
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"gains": [
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"Nachweisbare Senkung der operativen Kosten (10-25%).",
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"Transparente und planbare Kostenstruktur (TCO) ohne versteckte Überraschungen.",
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"Schneller, messbarer Return on Investment durch Effizienzsteigerung."
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]
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},
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{
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"name": "Innovations-Treiber",
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"pains": [
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"Verlust der Wettbewerbsfähigkeit durch veraltete Prozesse und Kundenangebote.",
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"Schwierigkeit, das Unternehmen als modernes, zukunftsorientiertes Brand zu positionieren.",
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"Verpasste Chancen durch fehlende Datengrundlage für Optimierungen."
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],
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"gains": [
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"Positionierung als Innovationsführer und Steigerung der Arbeitgeberattraktivität.",
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"Nutzung modernster Technologie als sichtbares Differenzierungsmerkmal.",
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"Gewinnung wertvoller Daten zur kontinuierlichen Prozessoptimierung."
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]
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}
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]
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# Clear existing Personas to avoid mix-up with old granular ones
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# (In production, we might want to be more careful, but here we want a clean slate for the new archetypes)
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try:
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db.query(Persona).delete()
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db.commit()
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print("Cleared old Personas.")
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except Exception as e:
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print(f"Warning clearing personas: {e}")
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for p_data in archetypes:
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print(f"Creating Archetype: {p_data['name']}")
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new_persona = Persona(
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name=p_data["name"],
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pains=json.dumps(p_data["pains"]),
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gains=json.dumps(p_data["gains"])
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)
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db.add(new_persona)
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db.commit()
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# --- 2. Update JobRoleMappings to map to Archetypes ---
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# We map the patterns to the new 4 Archetypes
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mapping_updates = [
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# Wirtschaftlicher Entscheider
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{"role": "Wirtschaftlicher Entscheider", "patterns": ["%geschäftsführer%", "%ceo%", "%director%", "%einkauf%", "%procurement%", "%finance%", "%cfo%"]},
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# Operativer Entscheider
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{"role": "Operativer Entscheider", "patterns": ["%housekeeping%", "%hausdame%", "%hauswirtschaft%", "%reinigung%", "%restaurant%", "%f&b%", "%werksleiter%", "%produktionsleiter%", "%lager%", "%logistik%", "%operations%", "%coo%"]},
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# Infrastruktur-Verantwortlicher
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{"role": "Infrastruktur-Verantwortlicher", "patterns": ["%facility%", "%technik%", "%instandhaltung%", "%it-leiter%", "%cto%", "%admin%", "%building%"]},
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# Innovations-Treiber
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{"role": "Innovations-Treiber", "patterns": ["%innovation%", "%digital%", "%transformation%", "%business dev%", "%marketing%"]}
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]
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# Clear old mappings to prevent confusion
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db.query(JobRoleMapping).delete()
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db.commit()
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print("Cleared old JobRoleMappings.")
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for group in mapping_updates:
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role_name = group["role"]
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for pattern in group["patterns"]:
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print(f"Mapping '{pattern}' -> '{role_name}'")
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db.add(JobRoleMapping(pattern=pattern, role=role_name))
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db.commit()
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print("Archetypes and Mappings Seeded Successfully.")
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db.close()
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if __name__ == "__main__":
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seed_archetypes()
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134
company-explorer/backend/scripts/sync_notion_personas.py
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134
company-explorer/backend/scripts/sync_notion_personas.py
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@@ -0,0 +1,134 @@
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import sys
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import os
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import requests
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import json
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import logging
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# Add company-explorer to path (parent of backend)
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
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from backend.database import SessionLocal, Persona, init_db
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from backend.config import settings
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# Setup Logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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NOTION_TOKEN_FILE = "/app/notion_token.txt"
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# Sector & Persona Master DB
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PERSONAS_DB_ID = "2e288f42-8544-8113-b878-ec99c8a02a6b"
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VALID_ARCHETYPES = {
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"Wirtschaftlicher Entscheider",
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"Operativer Entscheider",
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"Infrastruktur-Verantwortlicher",
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"Innovations-Treiber"
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}
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def load_notion_token():
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try:
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with open(NOTION_TOKEN_FILE, "r") as f:
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return f.read().strip()
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except FileNotFoundError:
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logger.error(f"Notion token file not found at {NOTION_TOKEN_FILE}")
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sys.exit(1)
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def query_notion_db(token, db_id):
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url = f"https://api.notion.com/v1/databases/{db_id}/query"
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headers = {
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"Authorization": f"Bearer {token}",
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"Notion-Version": "2022-06-28",
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"Content-Type": "application/json"
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}
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results = []
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has_more = True
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next_cursor = None
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while has_more:
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payload = {}
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if next_cursor:
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payload["start_cursor"] = next_cursor
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response = requests.post(url, headers=headers, json=payload)
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if response.status_code != 200:
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logger.error(f"Error querying Notion DB {db_id}: {response.text}")
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break
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data = response.json()
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results.extend(data.get("results", []))
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has_more = data.get("has_more", False)
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next_cursor = data.get("next_cursor")
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return results
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def extract_title(prop):
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if not prop: return ""
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return "".join([t.get("plain_text", "") for t in prop.get("title", [])])
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def extract_rich_text_to_list(prop):
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"""
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Extracts rich text and converts bullet points/newlines into a list of strings.
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"""
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if not prop: return []
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full_text = "".join([t.get("plain_text", "") for t in prop.get("rich_text", [])])
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# Split by newline and clean up bullets
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lines = full_text.split('\n')
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cleaned_lines = []
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for line in lines:
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line = line.strip()
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if not line: continue
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if line.startswith("- "):
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line = line[2:]
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elif line.startswith("• "):
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line = line[2:]
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cleaned_lines.append(line)
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return cleaned_lines
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def sync_personas(token, session):
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logger.info("Syncing Personas from Notion...")
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pages = query_notion_db(token, PERSONAS_DB_ID)
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count = 0
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for page in pages:
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props = page.get("properties", {})
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name = extract_title(props.get("Name"))
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if name not in VALID_ARCHETYPES:
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logger.debug(f"Skipping '{name}' (Not a target Archetype)")
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continue
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logger.info(f"Processing Persona: {name}")
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pains_list = extract_rich_text_to_list(props.get("Pains"))
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gains_list = extract_rich_text_to_list(props.get("Gains"))
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# Upsert Logic
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persona = session.query(Persona).filter(Persona.name == name).first()
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if not persona:
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persona = Persona(name=name)
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session.add(persona)
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logger.info(f" -> Creating new entry")
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else:
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logger.info(f" -> Updating existing entry")
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persona.pains = json.dumps(pains_list, ensure_ascii=False)
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persona.gains = json.dumps(gains_list, ensure_ascii=False)
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count += 1
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session.commit()
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logger.info(f"Sync complete. Updated {count} personas.")
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if __name__ == "__main__":
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token = load_notion_token()
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db = SessionLocal()
|
||||
|
||||
try:
|
||||
sync_personas(token, db)
|
||||
except Exception as e:
|
||||
logger.error(f"Sync failed: {e}", exc_info=True)
|
||||
finally:
|
||||
db.close()
|
||||
@@ -7,7 +7,7 @@ import logging
|
||||
# /app/backend/scripts/sync.py -> /app
|
||||
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
|
||||
|
||||
from backend.database import SessionLocal, Industry, RoboticsCategory, init_db
|
||||
from backend.database import SessionLocal, Industry, RoboticsCategory, Persona, init_db
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# Try loading from .env in root if exists
|
||||
@@ -76,6 +76,21 @@ def extract_number(prop):
|
||||
if not prop or "number" not in prop: return None
|
||||
return prop["number"]
|
||||
|
||||
def extract_rich_text_to_list(prop):
|
||||
if not prop or "rich_text" not in prop: return []
|
||||
full_text = "".join([t.get("plain_text", "") for t in prop.get("rich_text", [])])
|
||||
lines = full_text.split('\n')
|
||||
cleaned_lines = []
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line: continue
|
||||
if line.startswith("- "):
|
||||
line = line[2:]
|
||||
elif line.startswith("• "):
|
||||
line = line[2:]
|
||||
cleaned_lines.append(line)
|
||||
return cleaned_lines
|
||||
|
||||
def sync():
|
||||
logger.info("--- Starting Enhanced Sync ---")
|
||||
|
||||
@@ -83,6 +98,48 @@ def sync():
|
||||
init_db()
|
||||
session = SessionLocal()
|
||||
|
||||
# --- 4. Sync Personas (NEW) ---
|
||||
# Sector & Persona Master ID
|
||||
PERSONAS_DB_ID = "2e288f42-8544-8113-b878-ec99c8a02a6b"
|
||||
VALID_ARCHETYPES = {
|
||||
"Wirtschaftlicher Entscheider",
|
||||
"Operativer Entscheider",
|
||||
"Infrastruktur-Verantwortlicher",
|
||||
"Innovations-Treiber"
|
||||
}
|
||||
|
||||
if PERSONAS_DB_ID:
|
||||
logger.info(f"Syncing Personas from {PERSONAS_DB_ID}...")
|
||||
pages = query_all(PERSONAS_DB_ID)
|
||||
p_count = 0
|
||||
|
||||
# We assume Personas are cumulative, so we don't delete all first (safer for IDs)
|
||||
# But we could if we wanted a clean slate. Upsert is better.
|
||||
|
||||
for page in pages:
|
||||
props = page["properties"]
|
||||
name = extract_title(props.get("Name"))
|
||||
|
||||
if name not in VALID_ARCHETYPES:
|
||||
continue
|
||||
|
||||
import json
|
||||
pains_list = extract_rich_text_to_list(props.get("Pains"))
|
||||
gains_list = extract_rich_text_to_list(props.get("Gains"))
|
||||
|
||||
persona = session.query(Persona).filter(Persona.name == name).first()
|
||||
if not persona:
|
||||
persona = Persona(name=name)
|
||||
session.add(persona)
|
||||
|
||||
persona.pains = json.dumps(pains_list, ensure_ascii=False)
|
||||
persona.gains = json.dumps(gains_list, ensure_ascii=False)
|
||||
|
||||
p_count += 1
|
||||
|
||||
session.commit()
|
||||
logger.info(f"✅ Synced {p_count} Personas.")
|
||||
|
||||
# 2. Sync Categories (Products)
|
||||
cat_db_id = find_db_id("Product Categories") or find_db_id("Products")
|
||||
if cat_db_id:
|
||||
|
||||
47
company-explorer/backend/scripts/test_mapping_logic.py
Normal file
47
company-explorer/backend/scripts/test_mapping_logic.py
Normal file
@@ -0,0 +1,47 @@
|
||||
|
||||
import sys
|
||||
import os
|
||||
|
||||
# Setup Environment
|
||||
sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
|
||||
|
||||
from backend.database import SessionLocal, JobRoleMapping, Persona
|
||||
|
||||
def test_mapping(job_title):
|
||||
db = SessionLocal()
|
||||
print(f"\n--- Testing Mapping for '{job_title}' ---")
|
||||
|
||||
# 1. Find Role Name via JobRoleMapping
|
||||
role_name = None
|
||||
mappings = db.query(JobRoleMapping).all()
|
||||
for m in mappings:
|
||||
pattern_clean = m.pattern.replace("%", "").lower()
|
||||
if pattern_clean in job_title.lower():
|
||||
role_name = m.role
|
||||
print(f" -> Matched Pattern: '{m.pattern}' => Role: '{role_name}'")
|
||||
break
|
||||
|
||||
if not role_name:
|
||||
print(" -> No Pattern Matched.")
|
||||
return
|
||||
|
||||
# 2. Find Persona via Role Name
|
||||
persona = db.query(Persona).filter(Persona.name == role_name).first()
|
||||
if persona:
|
||||
print(f" -> Found Persona ID: {persona.id} (Name: {persona.name})")
|
||||
else:
|
||||
print(f" -> ERROR: Persona '{role_name}' not found in DB!")
|
||||
|
||||
db.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_titles = [
|
||||
"Leiter Hauswirtschaft",
|
||||
"CTO",
|
||||
"Geschäftsführer",
|
||||
"Head of Marketing",
|
||||
"Einkaufsleiter"
|
||||
]
|
||||
|
||||
for t in test_titles:
|
||||
test_mapping(t)
|
||||
33
company-explorer/backend/scripts/upgrade_schema_v2.py
Normal file
33
company-explorer/backend/scripts/upgrade_schema_v2.py
Normal file
@@ -0,0 +1,33 @@
|
||||
|
||||
import sys
|
||||
import os
|
||||
|
||||
# Add parent directory to path to allow import of backend.database
|
||||
sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
|
||||
|
||||
# Import everything to ensure metadata is populated
|
||||
from backend.database import engine, Base, Company, Contact, Industry, JobRoleMapping, Persona, Signal, EnrichmentData, RoboticsCategory, ImportLog, ReportedMistake, MarketingMatrix
|
||||
|
||||
def migrate():
|
||||
print("Migrating Database Schema...")
|
||||
|
||||
try:
|
||||
# Hacky migration for MarketingMatrix: Drop if exists to enforce new schema
|
||||
with engine.connect() as con:
|
||||
print("Dropping old MarketingMatrix table to enforce schema change...")
|
||||
try:
|
||||
from sqlalchemy import text
|
||||
con.execute(text("DROP TABLE IF EXISTS marketing_matrix"))
|
||||
print("Dropped marketing_matrix.")
|
||||
except Exception as e:
|
||||
print(f"Could not drop marketing_matrix: {e}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Pre-migration cleanup error: {e}")
|
||||
|
||||
# This creates 'personas' table AND re-creates 'marketing_matrix'
|
||||
Base.metadata.create_all(bind=engine)
|
||||
print("Migration complete. 'personas' table created and 'marketing_matrix' refreshed.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
migrate()
|
||||
Reference in New Issue
Block a user