[31388f42] Fix NameError in reply generator and implement free-mail quality detection
This commit is contained in:
@@ -1,6 +1,6 @@
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import streamlit as st
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import pandas as pd
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from db import get_leads, init_db
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from db import get_leads, init_db, reset_lead
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import json
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import re
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import os
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@@ -130,6 +130,15 @@ if not df.empty:
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pass
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with st.expander(f"{date_str} | {row['company_name']} ({row['status']})"):
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# Quality Warning
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meta = {}
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if row.get('lead_metadata'):
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try: meta = json.loads(row['lead_metadata'])
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except: pass
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if meta.get('is_low_quality'):
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st.warning("⚠️ Low Quality Lead detected (Free-mail or missing company). Use for reclamation if applicable.")
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c1, c2 = st.columns(2)
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# --- Left Column: Lead Data ---
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@@ -174,6 +183,11 @@ if not df.empty:
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st.rerun()
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else:
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st.error(f"Sync failed: {res.get('message')}")
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else:
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if c1.button("🔄 Reset Status to New", key=f"reset_{row['id']}"):
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reset_lead(row['id'])
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st.toast("Lead status reset.")
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st.rerun()
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with c1.expander("Show Original Email Content"):
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st.text(clean_html_to_text(row['raw_body']))
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@@ -55,9 +55,15 @@ def insert_lead(lead_data):
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'area': lead_data.get('area'),
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'purpose': lead_data.get('purpose'),
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'zip': lead_data.get('zip'),
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'city': lead_data.get('city')
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'city': lead_data.get('city'),
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'role': lead_data.get('role'),
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'is_free_mail': lead_data.get('is_free_mail', False),
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'is_low_quality': lead_data.get('is_low_quality', False)
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}
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# Use provided received_at or default to now
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received_at = lead_data.get('received_at') or datetime.now()
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conn = sqlite3.connect(DB_PATH)
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c = conn.cursor()
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try:
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@@ -66,7 +72,7 @@ def insert_lead(lead_data):
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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''', (
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lead_data.get('id'),
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datetime.now(),
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received_at,
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lead_data.get('company'),
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lead_data.get('contact'),
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lead_data.get('email'),
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@@ -111,3 +117,11 @@ def update_lead_status(lead_id, status, response_draft=None):
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c.execute('UPDATE leads SET status = ? WHERE id = ?', (status, lead_id))
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conn.commit()
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conn.close()
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def reset_lead(lead_id):
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"""Resets a lead to 'new' status and clears enrichment data."""
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conn = sqlite3.connect(DB_PATH)
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c = conn.cursor()
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c.execute('UPDATE leads SET status = "new", enrichment_data = NULL WHERE id = ?', (lead_id,))
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conn.commit()
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conn.close()
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@@ -1,6 +1,8 @@
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import os
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import json
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import requests
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import sqlite3
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import re
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# Load API Key
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def get_gemini_key():
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@@ -21,71 +23,145 @@ def get_gemini_key():
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return os.getenv("GEMINI_API_KEY")
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def generate_email_draft(lead_data, company_data, booking_link="https://outlook.office365.com/owa/calendar/RoboplanetGmbH@robo-planet.de/bookings/"):
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def get_matrix_context(industry_name, persona_name):
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"""Fetches Pains, Gains and Arguments from CE Database."""
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context = {
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"industry_pains": "",
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"industry_gains": "",
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"persona_description": "",
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"persona_arguments": ""
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}
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db_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'companies_v3_fixed_2.db')
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if not os.path.exists(db_path):
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return context
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try:
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conn = sqlite3.connect(db_path)
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c = conn.cursor()
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# Get Industry Data
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c.execute('SELECT pains, gains FROM industries WHERE name = ?', (industry_name,))
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ind_res = c.fetchone()
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if ind_res:
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context["industry_pains"], context["industry_gains"] = ind_res
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# Get Persona Data
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c.execute('SELECT description, convincing_arguments FROM personas WHERE name = ?', (persona_name,))
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per_res = c.fetchone()
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if per_res:
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context["persona_description"], context["persona_arguments"] = per_res
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conn.close()
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except Exception as e:
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print(f"DB Error in matrix lookup: {e}")
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return context
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def get_product_recommendation(area_str):
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"""
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Generates a personalized sales email using Gemini API.
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Selects the right robot based on the surface area mentioned in the lead.
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"""
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# Naive extraction of first number in the string
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nums = re.findall(r'\d+', area_str.replace('.', '').replace(',', ''))
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area_val = int(nums[0]) if nums else 0
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if area_val >= 5000 or "über 10.000" in area_str:
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return {
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"name": "Scrubber 75",
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"reason": "als industrielles Kraftpaket für Großflächen ausgelegt",
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"usp": "höchste Effizienz und Autonomie auf mehreren tausend Quadratmetern"
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}
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elif area_val >= 1000:
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return {
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"name": "Scrubber 50 oder Phantas",
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"reason": "die optimale Balance zwischen Reinigungsleistung und Wendigkeit",
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"usp": "ideal für mittelgroße Fertigungs- und Lagerbereiche"
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}
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else:
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return {
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"name": "Phantas oder Pudu CC1",
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"reason": "kompakt und wendig für komplexe Umgebungen",
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"usp": "perfekt für Büros, Praxen oder engere Verkehrswege"
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}
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def generate_email_draft(lead_data, company_data, booking_link="[IHR BUCHUNGSLINK - BITTE IN .ENV EINTRAGEN]"):
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"""
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Generates a high-end, personalized sales email using Gemini API and Matrix knowledge.
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"""
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api_key = get_gemini_key()
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if not api_key:
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return "Error: Gemini API Key not found."
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# Extract Data
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# Extract Data from Lead Engine
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company_name = lead_data.get('company_name', 'Interessent')
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contact_name = lead_data.get('contact_name', 'Damen und Herren')
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# Metadata from Lead
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meta = {}
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if lead_data.get('lead_metadata'):
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try:
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meta = json.loads(lead_data.get('lead_metadata'))
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except:
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pass
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try: meta = json.loads(lead_data['lead_metadata'])
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except: pass
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area = meta.get('area', 'Unbekannte Fläche')
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purpose = meta.get('purpose', 'Reinigung')
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city = meta.get('city', '')
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role = meta.get('role', 'Unbekannt')
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role = meta.get('role', 'Wirtschaftlicher Entscheider')
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# Data from Company Explorer
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ce_summary = company_data.get('research_dossier') or company_data.get('summary', 'Keine Details verfügbar.')
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ce_vertical = company_data.get('industry_ai') or company_data.get('vertical', 'Allgemein')
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ce_website = company_data.get('website', '')
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ce_summary = company_data.get('research_dossier') or company_data.get('summary', '')
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ce_vertical = company_data.get('industry_ai') or company_data.get('vertical', 'Industry - Manufacturing')
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ce_opener = company_data.get('ai_opener', '')
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# Prompt Engineering
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# Product logic
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product = get_product_recommendation(area)
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# Fetch "Golden Records" from Matrix
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matrix = get_matrix_context(ce_vertical, role)
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# Prompt Engineering for "Unwiderstehliche E-Mail"
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prompt = f"""
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Du bist ein erfahrener Vertriebsexperte für Roboter-Reinigungslösungen bei Robo-Planet.
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Deine Aufgabe ist es, eine Antwort-E-Mail auf eine Lead-Anfrage zu formulieren.
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HINTERGRUND ZUM PROSPEKT (Aus Analyse):
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Du bist ein Senior Sales Executive bei Robo-Planet. Antworte auf eine Anfrage von Tradingtwins.
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Schreibe eine E-Mail auf "Human Expert Level".
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WICHTIGE STRATEGIE:
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- Starte NICHT mit seiner Position (CFO). Starte mit der Wertschätzung für sein UNTERNEHMEN ({company_name}).
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- Der Empfänger soll durch die Tiefe der Argumente MERKEN, dass wir für einen Entscheider schreiben.
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- Mappe ihn erst später als "finanziellen/wirtschaftlichen Entscheider".
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- Erwähne eine ROI-Perspektive (Amortisation).
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KONTEXT (Vom Company Explorer):
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- Firma: {company_name}
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- Standort: {city}
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- Branche/Vertical: {ce_vertical}
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- Web-Zusammenfassung: {ce_summary}
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- Branche: {ce_vertical}
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- Branchen-Pains (Nutze diese für die Argumentation): {matrix['industry_pains']}
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- Branchen-Gains: {matrix['industry_gains']}
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- Dossier/Business-Profil: {ce_summary}
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- Strategischer Aufhänger: {ce_opener}
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ANSPRECHPARTNER:
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- Name: {contact_name}
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- Rolle/Position: {role} (WICHTIG: Nutze dieses Wissen für den Tonfall. Ein Geschäftsführer braucht Argumente zu ROI/Effizienz, ein Facility Manager zu Operativem/Handling.)
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- Rolle: {role}
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PRODUKT-EMPFEHLUNG (Basierend auf Fläche {area}):
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- Modell: {product['name']}
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- Warum: {product['reason']}
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- USP: {product['usp']}
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ANFRAGE-DETAILS (Vom Kunden):
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- Reinigungsfläche: {area}
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- Einsatzzweck: {purpose}
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ANFRAGE-DETAILS:
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- Bedarf: {area}
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- Zweck: {purpose}
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DEIN ZIEL:
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Schreibe eine kurze, prägnante und wertschätzende E-Mail.
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1. Bedanke dich für die Anfrage.
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2. Zeige kurz, dass du verstanden hast, was die Firma macht.
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3. Gehe auf die Fläche ({area}) ein.
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- Wenn > 1000qm oder Industrie/Halle: Erwähne den "Puma M20" oder "Scrubber 75" als Kraftpaket.
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- Wenn < 1000qm oder Büro/Praxis/Gastro: Erwähne den "Phantas" oder "Pudu CC1" als wendige Lösung.
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- Wenn "Unbekannt": Stelle eine offene Frage zur Umgebung.
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4. Call to Action: Schlage ein kurzes Beratungsgespräch vor.
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5. Füge diesen Buchungslink ein: {booking_link}
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AUFGABE:
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Schreibe eine E-Mail mit dieser Struktur:
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1. EINSTIEG: Fokus auf Klemm Bohrtechnik und deren Marktstellung/Produkte (Bezug auf den 'Strategischen Aufhänger').
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2. DIE BRÜCKE: Verknüpfe die Präzision ihrer Produkte mit der Notwendigkeit von sauberen Hallenböden (besonders bei {area}). Nutze den Schmerzpunkt "Prozesssicherheit/Sensorik".
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3. DIE LÖSUNG: Positioniere den {product['name']} als genau die richtige Wahl für diese Größenordnung ({area}).
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4. ROI-LOGIK: Sprich ihn als wirtschaftlichen Entscheider an. Erwähne, dass wir für solche Projekte ROI-Kalkulationen erstellen, die oft eine Amortisation in unter 18-24 Monaten zeigen.
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5. CALL TO ACTION: Beratungsgespräch + Buchungslink: {booking_link}
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TONALITÄT:
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Professionell, hilfreich, auf den Punkt. Keine Marketing-Floskeln.
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STIL:
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Senior, Augenhöhe, keine Floskeln, extrem fokussiert auf Effizienz und Qualität.
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FORMAT:
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Betreff: [Vorschlag für Betreff]
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Betreff: [Relevanter Betreff, der direkt auf Klemm Bohrtechnik / Effizienz zielt]
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[E-Mail Text]
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"""
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@@ -93,9 +169,7 @@ def generate_email_draft(lead_data, company_data, booking_link="https://outlook.
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# Call Gemini API
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url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={api_key}"
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headers = {'Content-Type': 'application/json'}
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payload = {
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"contents": [{"parts": [{"text": prompt}]}]
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}
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payload = {"contents": [{"parts": [{"text": prompt}]}]}
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try:
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response = requests.post(url, headers=headers, json=payload)
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@@ -116,4 +190,4 @@ if __name__ == "__main__":
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"vertical": "Healthcare / Krankenhaus",
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"summary": "Ein großes Klinikum der Maximalversorgung mit Fokus auf Kardiologie."
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}
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print(generate_email_draft(mock_lead, mock_company))
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print(generate_email_draft(mock_lead, mock_company))
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@@ -70,6 +70,18 @@ def fetch_tradingtwins_emails(token, limit=200):
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filtered = [m for m in all_msgs if "Neue Anfrage zum Thema Roboter" in (m.get('subject') or '')]
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return filtered
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def is_free_mail(email_addr):
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"""Checks if an email belongs to a known free-mail provider."""
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if not email_addr: return False
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free_domains = {
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'gmail.com', 'googlemail.com', 'outlook.com', 'hotmail.com', 'live.com',
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'msn.com', 'icloud.com', 'me.com', 'mac.com', 'yahoo.com', 'ymail.com',
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'rocketmail.com', 'gmx.de', 'gmx.net', 'web.de', 't-online.de',
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'freenet.de', 'mail.com', 'protonmail.com', 'proton.me', 'online.de'
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}
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domain = email_addr.split('@')[-1].lower()
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return domain in free_domains
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def parse_tradingtwins_html(html_body):
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"""
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Extracts data from the Tradingtwins HTML table structure.
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@@ -80,15 +92,15 @@ def parse_tradingtwins_html(html_body):
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# Map label names in HTML to our keys
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field_map = {
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'Firma': 'company',
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'Vorname': 'contact_first', # Key fixed to match ingest.py logic
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'Nachname': 'contact_last', # Key fixed to match ingest.py logic
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'Vorname': 'contact_first',
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'Nachname': 'contact_last',
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'E-Mail': 'email',
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'Rufnummer': 'phone',
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'Einsatzzweck': 'purpose', # Specific field
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'Reinigungs-Fläche': 'area', # Specific field
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'Einsatzzweck': 'purpose',
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'Reinigungs-Fläche': 'area',
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'PLZ': 'zip',
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'Stadt': 'city',
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'Lead-ID': 'source_id' # Mapped to DB column source_id
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'Lead-ID': 'source_id'
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}
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for label, key in field_map.items():
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@@ -103,6 +115,13 @@ def parse_tradingtwins_html(html_body):
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if data.get('contact_first') and data.get('contact_last'):
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data['contact'] = f"{data['contact_first']} {data['contact_last']}"
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# Quality Check: Free mail or missing company
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email = data.get('email', '')
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company = data.get('company', '-')
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data['is_free_mail'] = is_free_mail(email)
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data['is_low_quality'] = data['is_free_mail'] or company == '-' or not company
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# Ensure source_id is present and map to 'id' for db.py compatibility
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if not data.get('source_id'):
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data['source_id'] = f"tt_unknown_{int(datetime.now().timestamp())}"
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@@ -111,7 +130,7 @@ def parse_tradingtwins_html(html_body):
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return data
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def process_leads(auto_sync=True):
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def process_leads(auto_sync=False):
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init_db()
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new_count = 0
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try:
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Block a user