feat: Build complete POC for Butler model (client, matrix, daemon)

2026-02-12 14:18:52 +00:00
parent 5b1939c881
commit 5a19a9c85f
13 changed files with 1288 additions and 352 deletions
--- a/connector-superoffice/generate_marketing_copy.py
+++ b/connector-superoffice/generate_marketing_copy.py
@@ -0,0 +1,126 @@
+import os
+import json
+import requests
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv(override=True)
+
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+NOTION_API_KEY = os.getenv("NOTION_API_KEY")
+
+# Configuration
+NOTION_DB_INDUSTRIES = "2ec88f4285448014ab38ea664b4c2b81"  # ID aus deinen Links
+
+def get_vertical_data(vertical_name):
+    """Fetches Pains/Gains for a specific Vertical from Notion."""
+    url = f"https://api.notion.com/v1/databases/{NOTION_DB_INDUSTRIES}/query"
+    headers = {
+        "Authorization": f"Bearer {NOTION_API_KEY}",
+        "Notion-Version": "2022-06-28",
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "filter": {
+            "property": "Vertical",
+            "title": {
+                "contains": vertical_name
+            }
+        }
+    }
+    
+    response = requests.post(url, headers=headers, json=payload)
+    if response.status_code == 200:
+        results = response.json().get("results", [])
+        if results:
+            page = results[0]
+            props = page['properties']
+            
+            # Extract Text from Rich Text fields
+            pains = props.get('Pains', {}).get('rich_text', [])
+            gains = props.get('Gains', {}).get('rich_text', [])
+            
+            pain_text = pains[0]['plain_text'] if pains else "N/A"
+            gain_text = gains[0]['plain_text'] if gains else "N/A"
+            
+            return {
+                "vertical": vertical_name,
+                "pains": pain_text,
+                "gains": gain_text
+            }
+    return None
+
+def generate_copy_with_gemini(vertical_data, persona_role, persona_pains):
+    """
+    Generates the 3 text blocks using Gemini.
+    """
+    url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={GEMINI_API_KEY}"
+    
+    # Der Prompt (Dein Template)
+    prompt_text = f"""
+    Du bist ein kompetenter Lösungsberater und brillanter Texter.
+    AUFGABE: Erstelle 3 Textblöcke (Subject, Introduction_Textonly, Industry_References_Textonly) für eine E-Mail.
+    
+    --- KONTEXT ---
+    ZIELBRANCHE: {vertical_data['vertical']}
+    BRANCHEN-HERAUSFORDERUNGEN (PAIN POINTS): {vertical_data['pains']}
+    LÖSUNGS-VORTEILE (GAINS): {vertical_data['gains']}
+    
+    ANSPRECHPARTNER: {persona_role}
+    PERSÖNLICHE HERAUSFORDERUNGEN DES ANSPRECHPARTNERS: {persona_pains}
+    
+    REFERENZKUNDEN: "Wir arbeiten bereits mit Marktführern in Ihrer Branche." (Platzhalter)
+    
+    --- DEINE AUFGABE ---
+    1. Subject: Formuliere eine kurze Betreffzeile (max. 5 Wörter). Richte sie direkt an einem Pain Point aus.
+    2. Introduction_Textonly: Formuliere einen Einleitungstext (2 Sätze).
+       - Fokus: Brücke zwischen Problem und Lösung.
+    3. Industry_References_Textonly: Formuliere einen Social Proof Satz.
+    
+    --- FORMAT ---
+    Antworte NUR mit reinem JSON:
+    {{
+      "Subject": "...",
+      "Introduction_Textonly": "...",
+      "Industry_References_Textonly": "..."
+    }}
+    """
+    
+    payload = {
+        "contents": [{"parts": [{"text": prompt_text}]}],
+        "generationConfig": {"responseMimeType": "application/json"}
+    }
+    
+    try:
+        response = requests.post(url, json=payload)
+        if response.status_code == 200:
+            return json.loads(response.json()['candidates'][0]['content']['parts'][0]['text'])
+        else:
+            print(f"Gemini Error: {response.text}")
+            return None
+    except Exception as e:
+        print(f"Error: {e}")
+        return None
+
+if __name__ == "__main__":
+    # TEST RUN
+    
+    # 1. Daten holen (Beispiel: Logistics)
+    print("Fetching Vertical Data...")
+    vertical = get_vertical_data("Logistics - Warehouse")
+    
+    if vertical:
+        print(f"Loaded: {vertical['vertical']}")
+        
+        # 2. Persona definieren (Beispiel: Operativer Entscheider)
+        role = "Logistikleiter / Operations Manager"
+        role_pains = "Stillstand, Personalmangel, Stress, Unfallgefahr"
+        
+        # 3. Generieren
+        print("Generating Copy...")
+        copy = generate_copy_with_gemini(vertical, role, role_pains)
+        
+        print("\n--- RESULT ---")
+        print(json.dumps(copy, indent=2, ensure_ascii=False))
+    else:
+        print("Vertical not found.")