feat: Documentation and Tool Config Update
This commit is contained in:
Moltbot-Jarvis
@@ -1 +1 @@
|
||||
{"task_id": "30988f42-8544-817a-a250-fddb7d72b4c6", "token": "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", "session_start_time": "2026-02-16T11:58:09.261049"}
|
||||
{"task_id": "30a88f42-8544-819a-b5fc-c85cd80f43b7", "token": "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", "session_start_time": "2026-02-17T07:16:11.126812"}
|
||||
81
KONVER_STRATEGY.md
Normal file
81
KONVER_STRATEGY.md
Normal file
@@ -0,0 +1,81 @@
|
||||
# Konver.ai Integration: Strategie & Architektur
|
||||
|
||||
**Status:** Vertrag unterzeichnet (Fokus: Telefon-Enrichment).
|
||||
**Risiko:** Wegfall von Dealfront (Lead Gen) ohne adäquaten, automatisierten Ersatz.
|
||||
**Ziel:** Nutzung von Konver.ai nicht nur als manuelles "Telefonbuch", sondern als **skalierbare Quelle** für die Lead-Fabrik (Company Explorer).
|
||||
|
||||
## 1. Das Zielszenario (The "Golden Flow")
|
||||
|
||||
Wir integrieren Konver.ai via API direkt in den Company Explorer. Der CE fungiert als Gatekeeper, um Credits zu sparen und Dubletten zu verhindern.
|
||||
|
||||
```mermaid
|
||||
flowchart TD
|
||||
subgraph "RoboPlanet Ecosystem"
|
||||
Notion[("Notion Strategy\n(Verticals/Pains)")]
|
||||
SO[("SuperOffice CRM\n(Bestand)")]
|
||||
CE["Company Explorer\n(The Brain)"]
|
||||
end
|
||||
|
||||
subgraph "External Sources"
|
||||
Konver["Konver.ai API"]
|
||||
Web["Web / Google / Wiki"]
|
||||
end
|
||||
|
||||
%% Data Flow
|
||||
Notion -->|1. Sync Strategy| CE
|
||||
SO -->|2. Import Existing (Blocklist)| CE
|
||||
|
||||
CE -->|3. Search Query + Exclusion List| Konver
|
||||
Note right of Konver: "Suche: Altenheime > 10 Mio\nExclude: Domain-Liste aus SO"
|
||||
|
||||
Konver -->|4. Net New Candidates| CE
|
||||
|
||||
CE -->|5. Deep Dive (Robotik-Check)| Web
|
||||
|
||||
CE -->|6. Enrich Contact (Phone/Mail)| Konver
|
||||
Note right of CE: "Nur für Firmen mit\nhohem Robotik-Score!"
|
||||
|
||||
CE -->|7. Export Qualified Lead| SO
|
||||
```
|
||||
|
||||
## 2. Die kritische Lücke: "Exclusion List"
|
||||
|
||||
Da Dealfront (unser bisheriges "Fischnetz") abgeschaltet wird, müssen wir Konver zur **Neukunden-Generierung** nutzen.
|
||||
Ohne eine **Ausschluss-Liste (Exclusion List)** bei der Suche verbrennen wir Geld und Zeit:
|
||||
|
||||
1. **Kosten:** Wir zahlen Credits für Firmen/Kontakte, die wir schon haben.
|
||||
2. **Daten-Hygiene:** Wir importieren Dubletten, die wir mühsam bereinigen müssen.
|
||||
3. **Blindflug:** Wir wissen vor dem Kauf nicht, ob der Datensatz "netto neu" ist.
|
||||
|
||||
### Forderung an Konver (Technisches Onboarding)
|
||||
|
||||
*"Um Konver.ai als strategischen Nachfolger für Dealfront in unserer Marketing-Automation nutzen zu können, benötigen wir zwingend API-Funktionen zur **Deduplizierung VOR dem Datenkauf**."*
|
||||
|
||||
**Konkrete Features:**
|
||||
* **Domain-Exclusion:** Upload einer Liste (z.B. 5.000 Domains), die in der API-Suche *nicht* zurückgegeben werden.
|
||||
* **Contact-Check:** Prüfung (z.B. Hash-Abgleich), ob eine E-Mail-Adresse bereits "bekannt" ist, bevor Kontaktdaten enthüllt (und berechnet) werden.
|
||||
|
||||
## 3. Workflow-Varianten
|
||||
|
||||
### A. Der "Smart Enricher" (Wirtschaftlich)
|
||||
Wir nutzen Konver nur für Firmen, die **wirklich** relevant sind.
|
||||
|
||||
1. **Scraping:** Company Explorer findet 100 Altenheime (Web-Suche).
|
||||
2. **Filterung:** KI prüft Websites -> 40 davon sind relevant (haben große Flächen).
|
||||
3. **Enrichment:** Nur für diese 40 fragen wir Konver via API: *"Gib mir den Facility Manager + Handy"*.
|
||||
4. **Ergebnis:** Wir zahlen 40 Credits statt 100. Hohe Effizienz.
|
||||
|
||||
### B. Der "Mass Loader" (Teuer & Dumm - zu vermeiden)
|
||||
1. Wir laden "Alle Altenheime" aus Konver direkt nach SuperOffice.
|
||||
2. Wir zahlen 100 Credits.
|
||||
3. Der Vertrieb ruft an -> 60 davon sind ungeeignet (zu klein, kein Bedarf).
|
||||
4. **Ergebnis:** 60 Credits verbrannt, Vertrieb frustriert.
|
||||
|
||||
## 4. Fazit & Next Steps
|
||||
|
||||
Wir müssen im Onboarding-Gespräch klären:
|
||||
1. **API-Doku:** Wo ist die Dokumentation für `Search` und `Enrich` Endpoints?
|
||||
2. **Exclusion:** Wie filtern wir Bestandskunden im API-Call?
|
||||
3. **Bulk-Enrichment:** Können wir Listen (Domains) zum Anreichern hochladen?
|
||||
|
||||
Ohne diese Features ist Konver ein Rückschritt in die manuelle Einzelbearbeitung.
|
||||
@@ -57,6 +57,8 @@ const App: React.FC = () => {
|
||||
const [generationStep, setGenerationStep] = useState<number>(0); // 0: idle, 1-6: step X is complete
|
||||
const [selectedIndustry, setSelectedIndustry] = useState<string>('');
|
||||
const [batchStatus, setBatchStatus] = useState<{ current: number; total: number; industry: string } | null>(null);
|
||||
const [isEnriching, setIsEnriching] = useState<boolean>(false);
|
||||
|
||||
|
||||
// Project Persistence
|
||||
const [projectId, setProjectId] = useState<string | null>(null);
|
||||
@@ -69,6 +71,43 @@ const App: React.FC = () => {
|
||||
const STEP_TITLES = t.stepTitles;
|
||||
const STEP_KEYS: (keyof AnalysisData)[] = ['offer', 'targetGroups', 'personas', 'painPoints', 'gains', 'messages', 'customerJourney'];
|
||||
|
||||
const handleEnrichRow = async (productName: string, productUrl?: string) => {
|
||||
setIsEnriching(true);
|
||||
setError(null);
|
||||
try {
|
||||
const response = await fetch(`${API_BASE_URL}/enrich-product`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
productName,
|
||||
productUrl,
|
||||
language: inputData.language
|
||||
}),
|
||||
});
|
||||
if (!response.ok) {
|
||||
const errorData = await response.json();
|
||||
throw new Error(errorData.details || `HTTP error! status: ${response.status}`);
|
||||
}
|
||||
const newRow = await response.json();
|
||||
setAnalysisData(prev => {
|
||||
const currentOffer = prev.offer || { headers: [], rows: [], summary: [] };
|
||||
return {
|
||||
...prev,
|
||||
offer: {
|
||||
...currentOffer,
|
||||
rows: [...currentOffer.rows, newRow]
|
||||
}
|
||||
};
|
||||
});
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
setError(e instanceof Error ? `Fehler beim Anreichern: ${e.message}` : 'Unbekannter Fehler beim Anreichern.');
|
||||
} finally {
|
||||
setIsEnriching(false);
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
// --- AUTO-SAVE EFFECT ---
|
||||
useEffect(() => {
|
||||
if (generationStep === 0 || !inputData.companyUrl) return;
|
||||
@@ -507,9 +546,10 @@ const App: React.FC = () => {
|
||||
const canAdd = ['offer', 'targetGroups'].includes(stepKey);
|
||||
const canDelete = ['offer', 'targetGroups', 'personas'].includes(stepKey);
|
||||
|
||||
const handleManualAdd = (newRow: string[]) => {
|
||||
const handleManualAdd = () => {
|
||||
const newEmptyRow = Array(step.headers.length).fill('');
|
||||
const currentRows = step.rows || [];
|
||||
handleDataChange(stepKey, { ...step, rows: [...currentRows, newRow] });
|
||||
handleDataChange(stepKey, { ...step, rows: [...currentRows, newEmptyRow] });
|
||||
};
|
||||
|
||||
return (
|
||||
@@ -521,8 +561,8 @@ const App: React.FC = () => {
|
||||
rows={step.rows}
|
||||
onDataChange={(newRows) => handleDataChange(stepKey, { ...step, rows: newRows })}
|
||||
canAddRows={canAdd}
|
||||
onEnrichRow={canAdd ? handleManualAdd : undefined}
|
||||
isEnriching={false}
|
||||
onEnrichRow={stepKey === 'offer' ? handleEnrichRow : handleManualAdd}
|
||||
isEnriching={isEnriching}
|
||||
canDeleteRows={canDelete}
|
||||
onRestart={() => handleStepRestart(stepKey)}
|
||||
t={t}
|
||||
|
||||
@@ -15,6 +15,6 @@ View your app in AI Studio: https://ai.studio/apps/drive/1ZPnGbhaEnyhIyqs2rYhcPX
|
||||
|
||||
1. Install dependencies:
|
||||
`npm install`
|
||||
2. Set the `GEMINI_API_KEY` in [.env.local](.env.local) to your Gemini API key
|
||||
2. Set the `GEMINI_API_KEY` in the central `.env` file in the project's root directory.
|
||||
3. Run the app:
|
||||
`npm run dev`
|
||||
|
||||
@@ -12,7 +12,7 @@ interface StepDisplayProps {
|
||||
onDataChange: (newRows: string[][]) => void;
|
||||
canAddRows?: boolean;
|
||||
canDeleteRows?: boolean;
|
||||
onEnrichRow?: (productName: string, productUrl?: string) => Promise<void>;
|
||||
onEnrichRow?: (productName: string, productUrl?: string) => void;
|
||||
isEnriching?: boolean;
|
||||
onRestart?: () => void;
|
||||
t: typeof translations.de;
|
||||
@@ -106,12 +106,7 @@ export const StepDisplay: React.FC<StepDisplayProps> = ({ title, summary, header
|
||||
};
|
||||
|
||||
const handleAddRowClick = () => {
|
||||
if (onEnrichRow) {
|
||||
setIsAddingRow(true);
|
||||
} else {
|
||||
const newEmptyRow = Array(headers.length).fill('');
|
||||
onDataChange([...rows, newEmptyRow]);
|
||||
}
|
||||
};
|
||||
|
||||
const handleConfirmAddRow = () => {
|
||||
|
||||
@@ -89,6 +89,15 @@ router.post('/next-step', (req, res) => {
|
||||
} catch (e) { res.status(500).json({ error: e.message }); }
|
||||
});
|
||||
|
||||
router.post('/enrich-product', (req, res) => {
|
||||
const { productName, productUrl, language } = req.body;
|
||||
const args = [SCRIPT_PATH, '--mode', 'enrich_product', '--product_name', productName, '--language', language];
|
||||
if (productUrl) {
|
||||
args.push('--product_url', productUrl);
|
||||
}
|
||||
runPythonScript(args, res);
|
||||
});
|
||||
|
||||
router.get('/projects', (req, res) => runPythonScript([dbScript, 'list'], res));
|
||||
router.get('/projects/:id', (req, res) => runPythonScript([dbScript, 'load', req.params.id], res));
|
||||
router.delete('/projects/:id', (req, res) => runPythonScript([dbScript, 'delete', req.params.id], res));
|
||||
|
||||
@@ -3,7 +3,7 @@ import { defineConfig, loadEnv } from 'vite';
|
||||
import react from '@vitejs/plugin-react';
|
||||
|
||||
export default defineConfig(({ mode }) => {
|
||||
const env = loadEnv(mode, '.', '');
|
||||
const env = loadEnv(mode, '../', '');
|
||||
return {
|
||||
base: '/b2b/',
|
||||
server: {
|
||||
|
||||
@@ -622,6 +622,40 @@ def next_step(language, context_file, generation_step, channels, focus_industry=
|
||||
summary = [re.sub(r'^\*\s*|^-\s*|^\d+\.\s*', '', s.strip()) for s in summary_match[1].split('\n') if s.strip()] if summary_match else []
|
||||
return {step_key: {"summary": summary, "headers": table_data['headers'], "rows": table_data['rows']}}
|
||||
|
||||
def enrich_product(product_name, product_url, language):
|
||||
logging.info(f"Enriching product: {product_name} ({product_url})")
|
||||
api_key = load_api_key()
|
||||
if not api_key: raise ValueError("Gemini API key is missing.")
|
||||
|
||||
grounding_text = ""
|
||||
if product_url:
|
||||
grounding_text = get_text_from_url(product_url)
|
||||
|
||||
prompt_text = f"""
|
||||
# ANWEISUNG
|
||||
Du bist ein B2B-Marketing-Analyst. Deine Aufgabe ist es, die Daten für EIN Produkt zu generieren.
|
||||
Basierend auf dem Produktnamen und (optional) dem Inhalt der Produkt-URL, fülle die Spalten einer Markdown-Tabelle aus.
|
||||
Die Ausgabe MUSS eine einzelne, kommaseparierte Zeile sein, die in eine Tabelle passt. KEINE Header, KEIN Markdown, nur die Werte.
|
||||
|
||||
# PRODUKT
|
||||
- Name: "{product_name}"
|
||||
- URL-Inhalt: "{grounding_text[:3000]}..."
|
||||
|
||||
# SPALTEN
|
||||
Produkt/Lösung | Beschreibung (1-2 Sätze) | Kernfunktionen | Differenzierung | Primäre Quelle (URL)
|
||||
|
||||
# BEISPIEL-OUTPUT
|
||||
Saugroboter NR1500,Ein professioneller Saugroboter für große Büroflächen.,Autonome Navigation;Intelligente Kartierung;Lange Akkulaufzeit,Fokus auf B2B-Markt;Datenschutzkonform,https://nexaro.com/products/nr1500
|
||||
|
||||
# DEINE AUFGABE
|
||||
Erstelle jetzt die kommaseparierte Zeile für das Produkt "{product_name}".
|
||||
"""
|
||||
|
||||
response_text = call_gemini_api(prompt_text, api_key)
|
||||
|
||||
# Return as a simple list of strings
|
||||
return [cell.strip() for cell in response_text.split(',')]
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--mode', required=True)
|
||||
@@ -633,10 +667,13 @@ def main():
|
||||
parser.add_argument('--channels')
|
||||
parser.add_argument('--language', required=True)
|
||||
parser.add_argument('--focus_industry') # New argument
|
||||
parser.add_argument('--product_name')
|
||||
parser.add_argument('--product_url')
|
||||
args = parser.parse_args()
|
||||
try:
|
||||
if args.mode == 'start_generation': result = start_generation(args.url, args.language, args.regions, args.focus)
|
||||
elif args.mode == 'next_step': result = next_step(args.language, args.context_file, args.generation_step, args.channels, args.focus_industry)
|
||||
elif args.mode == 'enrich_product': result = enrich_product(args.product_name, args.product_url, args.language)
|
||||
sys.stdout.write(json.dumps(result, ensure_ascii=False))
|
||||
except Exception as e:
|
||||
logging.error(f"Error: {e}", exc_info=True)
|
||||
|
||||
@@ -18,35 +18,21 @@ class Company(Base):
|
||||
|
||||
id = Column(Integer, primary_key=True, index=True)
|
||||
|
||||
# Core Identity (Golden Record - from Research)
|
||||
# Core Identity
|
||||
name = Column(String, index=True)
|
||||
website = Column(String, index=True) # Normalized Domain preferred
|
||||
crm_id = Column(String, unique=True, index=True, nullable=True) # Link to D365
|
||||
|
||||
# CRM Original Data (Source of Truth for Import)
|
||||
crm_name = Column(String, nullable=True)
|
||||
crm_website = Column(String, nullable=True)
|
||||
crm_address = Column(String, nullable=True) # Full address string or JSON
|
||||
crm_vat = Column(String, nullable=True)
|
||||
|
||||
# Classification
|
||||
industry_crm = Column(String, nullable=True) # The "allowed" industry
|
||||
industry_ai = Column(String, nullable=True) # The AI suggested industry
|
||||
|
||||
# Location (Golden Record)
|
||||
# Location
|
||||
city = Column(String, nullable=True)
|
||||
country = Column(String, default="DE")
|
||||
|
||||
# Workflow Status
|
||||
status = Column(String, default="NEW", index=True) # NEW, TO_ENRICH, ENRICHED, QUALIFIED, DISQUALIFIED
|
||||
|
||||
# Quality & Confidence
|
||||
confidence_score = Column(Float, default=0.0) # Overall confidence
|
||||
data_mismatch_score = Column(Float, default=0.0) # 0.0=Match, 1.0=Mismatch
|
||||
|
||||
# Scraping Status Flags
|
||||
website_scrape_status = Column(String, default="PENDING") # PENDING, SUCCESS, FAILED, BLOCKED
|
||||
wiki_search_status = Column(String, default="PENDING") # PENDING, FOUND, NOT_FOUND
|
||||
status = Column(String, default="NEW", index=True)
|
||||
|
||||
# Granular Process Tracking (Timestamps)
|
||||
created_at = Column(DateTime, default=datetime.utcnow)
|
||||
@@ -120,13 +106,6 @@ class Industry(Base):
|
||||
status_notion = Column(String, nullable=True) # e.g. "P1 Focus Industry"
|
||||
is_focus = Column(Boolean, default=False) # Derived from status_notion
|
||||
|
||||
# Enhanced Fields (v3.1 - Pains/Gains/Priority)
|
||||
pains = Column(Text, nullable=True)
|
||||
gains = Column(Text, nullable=True)
|
||||
notes = Column(Text, nullable=True)
|
||||
priority = Column(String, nullable=True) # Replaces old status concept ("Freigegeben")
|
||||
ops_focus_secondary = Column(Boolean, default=False)
|
||||
|
||||
# NEW SCHEMA FIELDS (from MIGRATION_PLAN)
|
||||
metric_type = Column(String, nullable=True) # Unit_Count, Area_in, Area_out
|
||||
min_requirement = Column(Float, nullable=True)
|
||||
@@ -138,7 +117,6 @@ class Industry(Base):
|
||||
|
||||
# Optional link to a Robotics Category (the "product" relevant for this industry)
|
||||
primary_category_id = Column(Integer, ForeignKey("robotics_categories.id"), nullable=True)
|
||||
secondary_category_id = Column(Integer, ForeignKey("robotics_categories.id"), nullable=True)
|
||||
|
||||
created_at = Column(DateTime, default=datetime.utcnow)
|
||||
|
||||
|
||||
@@ -1,53 +0,0 @@
|
||||
import sqlite3
|
||||
import os
|
||||
|
||||
# Adjust path to your actual DB location
|
||||
DB_PATH = "/home/node/clawd/repos/brancheneinstufung2/company_explorer.db"
|
||||
|
||||
def migrate():
|
||||
if not os.path.exists(DB_PATH):
|
||||
print(f"Database not found at {DB_PATH}. Maybe it hasn't been created yet?")
|
||||
return
|
||||
|
||||
print(f"Migrating database at {DB_PATH}...")
|
||||
conn = sqlite3.connect(DB_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
columns_to_add = [
|
||||
# Industries (Existing List)
|
||||
("industries", "pains", "TEXT"),
|
||||
("industries", "gains", "TEXT"),
|
||||
("industries", "notes", "TEXT"),
|
||||
("industries", "priority", "TEXT"),
|
||||
("industries", "ops_focus_secondary", "BOOLEAN DEFAULT 0"),
|
||||
("industries", "secondary_category_id", "INTEGER"),
|
||||
|
||||
# Companies (New List for CRM Data)
|
||||
("companies", "crm_name", "TEXT"),
|
||||
("companies", "crm_website", "TEXT"),
|
||||
("companies", "crm_address", "TEXT"),
|
||||
("companies", "crm_vat", "TEXT"),
|
||||
|
||||
# Companies (Status & Quality)
|
||||
("companies", "confidence_score", "FLOAT DEFAULT 0.0"),
|
||||
("companies", "data_mismatch_score", "FLOAT DEFAULT 0.0"),
|
||||
("companies", "website_scrape_status", "TEXT DEFAULT 'PENDING'"),
|
||||
("companies", "wiki_search_status", "TEXT DEFAULT 'PENDING'"),
|
||||
]
|
||||
|
||||
for table, col_name, col_type in columns_to_add:
|
||||
try:
|
||||
print(f"Adding column '{col_name}' to '{table}'...")
|
||||
cursor.execute(f"ALTER TABLE {table} ADD COLUMN {col_name} {col_type}")
|
||||
except sqlite3.OperationalError as e:
|
||||
if "duplicate column name" in str(e):
|
||||
print(f"Column '{col_name}' already exists. Skipping.")
|
||||
else:
|
||||
print(f"Error adding '{col_name}' to '{table}': {e}")
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print("Migration complete.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
migrate()
|
||||
@@ -1,170 +0,0 @@
|
||||
import sys
|
||||
import os
|
||||
import requests
|
||||
import logging
|
||||
|
||||
# Setup Paths
|
||||
sys.path.append(os.path.abspath("/home/node/clawd/repos/brancheneinstufung2/company-explorer"))
|
||||
sys.path.append(os.path.abspath("/home/node/clawd/repos/brancheneinstufung2"))
|
||||
|
||||
from backend.database import SessionLocal, Industry, RoboticsCategory, init_db
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
# Logging
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
if not NOTION_TOKEN:
|
||||
logger.error("NOTION_API_KEY missing!")
|
||||
sys.exit(1)
|
||||
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Notion-Version": "2022-06-28",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
def find_db_id(query_name):
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": query_name, "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def query_all(db_id):
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
results = []
|
||||
has_more = True
|
||||
next_cursor = None
|
||||
|
||||
while has_more:
|
||||
payload = {}
|
||||
if next_cursor: payload["start_cursor"] = next_cursor
|
||||
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
data = resp.json()
|
||||
results.extend(data.get("results", []))
|
||||
has_more = data.get("has_more", False)
|
||||
next_cursor = data.get("next_cursor")
|
||||
return results
|
||||
|
||||
def extract_rich_text(prop):
|
||||
if not prop or "rich_text" not in prop: return ""
|
||||
return "".join([t.get("plain_text", "") for t in prop.get("rich_text", [])])
|
||||
|
||||
def extract_title(prop):
|
||||
if not prop or "title" not in prop: return ""
|
||||
return "".join([t.get("plain_text", "") for t in prop.get("title", [])])
|
||||
|
||||
def extract_select(prop):
|
||||
if not prop or "select" not in prop or not prop["select"]: return ""
|
||||
return prop["select"]["name"]
|
||||
|
||||
def sync():
|
||||
logger.info("--- Starting Enhanced Sync ---")
|
||||
|
||||
# 1. Init DB
|
||||
init_db()
|
||||
session = SessionLocal()
|
||||
|
||||
# 2. Sync Categories (Products)
|
||||
cat_db_id = find_db_id("Product Categories") or find_db_id("Products")
|
||||
if cat_db_id:
|
||||
logger.info(f"Syncing Products from {cat_db_id}...")
|
||||
pages = query_all(cat_db_id)
|
||||
for page in pages:
|
||||
props = page["properties"]
|
||||
name = extract_title(props.get("Name") or props.get("Product Name"))
|
||||
if not name: continue
|
||||
|
||||
notion_id = page["id"]
|
||||
key = name.lower().replace(" ", "_")
|
||||
|
||||
# Upsert
|
||||
cat = session.query(RoboticsCategory).filter(RoboticsCategory.notion_id == notion_id).first()
|
||||
if not cat:
|
||||
cat = RoboticsCategory(notion_id=notion_id, key=key)
|
||||
session.add(cat)
|
||||
|
||||
cat.name = name
|
||||
cat.description = extract_rich_text(props.get("Description"))
|
||||
# Add reasoning guide map if available
|
||||
session.commit()
|
||||
else:
|
||||
logger.warning("Product DB not found!")
|
||||
|
||||
# 3. Sync Industries
|
||||
ind_db_id = find_db_id("Industries")
|
||||
if ind_db_id:
|
||||
logger.info(f"Syncing Industries from {ind_db_id}...")
|
||||
|
||||
# Clear existing? Or Upsert?
|
||||
# For clean sync, DELETE is safer as long as we don't have FK constraints blocking it.
|
||||
# But wait! Companies link to Industry STRING, not FK usually?
|
||||
# Check Company model: industry_ai = Column(String). So no FK constraint. Safe to delete.
|
||||
session.query(Industry).delete()
|
||||
session.commit()
|
||||
|
||||
pages = query_all(ind_db_id)
|
||||
count = 0
|
||||
|
||||
for page in pages:
|
||||
props = page["properties"]
|
||||
name = extract_title(props.get("Vertical"))
|
||||
if not name: continue
|
||||
|
||||
ind = Industry(notion_id=page["id"], name=name)
|
||||
session.add(ind)
|
||||
|
||||
# Map Fields
|
||||
ind.description = extract_rich_text(props.get("Definition"))
|
||||
ind.notes = extract_rich_text(props.get("Notes"))
|
||||
ind.pains = extract_rich_text(props.get("Pains"))
|
||||
ind.gains = extract_rich_text(props.get("Gains"))
|
||||
|
||||
# Status / Priority (Renamed field check)
|
||||
# Try "Priorität" first, then "Freigegeben", then "Status"
|
||||
prio = extract_select(props.get("Priorität"))
|
||||
if not prio: prio = extract_select(props.get("Freigegeben"))
|
||||
if not prio: prio = extract_select(props.get("Status"))
|
||||
|
||||
ind.priority = prio
|
||||
ind.status_notion = prio # Legacy field
|
||||
ind.is_focus = (prio == "Freigegeben" or prio == "P1 Focus Industry")
|
||||
|
||||
# Ops Focus
|
||||
if "Ops Focus: Secondary" in props:
|
||||
ind.ops_focus_secondary = props["Ops Focus: Secondary"].get("checkbox", False)
|
||||
|
||||
# Relations
|
||||
# Primary
|
||||
rels_prim = props.get("Primary Product Category", {}).get("relation", [])
|
||||
if rels_prim:
|
||||
pid = rels_prim[0]["id"]
|
||||
cat = session.query(RoboticsCategory).filter(RoboticsCategory.notion_id == pid).first()
|
||||
if cat: ind.primary_category_id = cat.id
|
||||
|
||||
# Secondary
|
||||
rels_sec = props.get("Secondary Product", {}).get("relation", [])
|
||||
if rels_sec:
|
||||
pid = rels_sec[0]["id"]
|
||||
cat = session.query(RoboticsCategory).filter(RoboticsCategory.notion_id == pid).first()
|
||||
if cat: ind.secondary_category_id = cat.id
|
||||
|
||||
count += 1
|
||||
|
||||
session.commit()
|
||||
logger.info(f"✅ Synced {count} industries.")
|
||||
else:
|
||||
logger.error("Industries DB not found!")
|
||||
|
||||
session.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
sync()
|
||||
70
debug_transcription_raw.py
Normal file
70
debug_transcription_raw.py
Normal file
@@ -0,0 +1,70 @@
|
||||
import sqlite3
|
||||
import json
|
||||
import os
|
||||
|
||||
DB_PATH = "transcripts.db"
|
||||
|
||||
def inspect_latest_meeting():
|
||||
if not os.path.exists(DB_PATH):
|
||||
print(f"Error: Database file '{DB_PATH}' not found.")
|
||||
return
|
||||
|
||||
conn = sqlite3.connect(DB_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Get latest meeting
|
||||
cursor.execute("SELECT id, title, created_at FROM meetings ORDER BY created_at DESC LIMIT 1")
|
||||
meeting = cursor.fetchone()
|
||||
|
||||
if not meeting:
|
||||
print("No meetings found in DB.")
|
||||
conn.close()
|
||||
return
|
||||
|
||||
meeting_id, title, created_at = meeting
|
||||
print(f"--- Inspecting Latest Meeting: ID {meeting_id} ('{title}') created at {created_at} ---")
|
||||
|
||||
# Get chunks for this meeting
|
||||
cursor.execute("SELECT id, chunk_index, raw_text, json_content FROM transcript_chunks WHERE meeting_id = ? ORDER BY chunk_index", (meeting_id,))
|
||||
chunks = cursor.fetchall()
|
||||
|
||||
if not chunks:
|
||||
print("No chunks found for this meeting.")
|
||||
|
||||
for chunk in chunks:
|
||||
chunk_id, idx, raw_text, json_content = chunk
|
||||
print(f"\n[Chunk {idx} (ID: {chunk_id})]")
|
||||
|
||||
print(f"Stored JSON Content (Length): {len(json.loads(json_content)) if json_content else 'None/Empty'}")
|
||||
|
||||
print("-" * 20 + " RAW TEXT START " + "-" * 20)
|
||||
print(raw_text[:500]) # Print first 500 chars
|
||||
print("..." if len(raw_text) > 500 else "")
|
||||
print("-" * 20 + " RAW TEXT END " + "-" * 20)
|
||||
|
||||
# Try to parse manually to see error
|
||||
try:
|
||||
# Simulate cleaning logic from orchestrator
|
||||
cleaned = raw_text.strip()
|
||||
if cleaned.startswith("```json"):
|
||||
cleaned = cleaned[7:]
|
||||
elif cleaned.startswith("```"):
|
||||
cleaned = cleaned[3:]
|
||||
if cleaned.endswith("```"):
|
||||
cleaned = cleaned[:-3]
|
||||
cleaned = cleaned.strip()
|
||||
|
||||
parsed = json.loads(cleaned)
|
||||
print("✅ Manual Parsing Successful!")
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"❌ Manual Parsing Failed: {e}")
|
||||
# Show context around error
|
||||
if hasattr(e, 'pos'):
|
||||
start = max(0, e.pos - 20)
|
||||
end = min(len(cleaned), e.pos + 20)
|
||||
print(f" Context at error: ...{cleaned[start:end]}...")
|
||||
|
||||
conn.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
inspect_latest_meeting()
|
||||
@@ -98,13 +98,13 @@ services:
|
||||
restart: unless-stopped
|
||||
volumes:
|
||||
- ./transcription-tool/backend:/app/backend
|
||||
- ./transcription-tool/frontend/dist:/app/frontend/dist # Mount Frontend Build for Live Updates
|
||||
- ./transcripts.db:/app/transcripts.db
|
||||
- ./uploads_audio:/app/uploads_audio
|
||||
- ./gemini_api_key.txt:/app/gemini_api_key.txt
|
||||
environment:
|
||||
PYTHONUNBUFFERED: "1"
|
||||
DATABASE_URL: "sqlite:////app/transcripts.db"
|
||||
GEMINI_API_KEY: "AIzaSyCFRmr1rOrkFKiEuh9GOCJNB2zfJsYmR68" # Placeholder, actual key is in file
|
||||
ports:
|
||||
- "8001:8001"
|
||||
|
||||
|
||||
@@ -1,102 +0,0 @@
|
||||
import argparse
|
||||
import subprocess
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
|
||||
# --- Setup Paths ---
|
||||
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
SCRIPTS_SUBDIR = os.path.join(SCRIPT_DIR, "scripts")
|
||||
LOG_DIR = os.path.join(SCRIPT_DIR, "logs")
|
||||
THROUGHPUT_LOG = os.path.join(LOG_DIR, "throughput.log")
|
||||
|
||||
# Add scripts subdir to path to allow imports
|
||||
sys.path.append(SCRIPTS_SUBDIR)
|
||||
|
||||
# TODO: Import other modules once they are ready
|
||||
# from company_explorer_connector import handle_company_workflow
|
||||
# from generate_sniper_copy import generate_copy
|
||||
|
||||
def setup_environment():
|
||||
"""Ensures necessary directories exist."""
|
||||
os.makedirs(LOG_DIR, exist_ok=True)
|
||||
|
||||
def log_throughput(identifier):
|
||||
"""Logs a successful processing event for the dashboard."""
|
||||
with open(THROUGHPUT_LOG, "a") as f:
|
||||
f.write(f"{datetime.utcnow().isoformat()},{identifier}\n")
|
||||
print(f"📈 Logged successful processing for '{identifier}' for dashboard.")
|
||||
|
||||
def run_sync():
|
||||
"""Runs the database sync script to ensure local data is fresh."""
|
||||
print("\n--- [Step 1: Syncing local Company Explorer database] ---")
|
||||
sync_script_path = os.path.join(SCRIPTS_SUBDIR, "sync_ce_to_sqlite.py")
|
||||
|
||||
if not os.path.exists(sync_script_path):
|
||||
print(f"❌ ERROR: Sync script not found at {sync_script_path}")
|
||||
return False
|
||||
|
||||
result = subprocess.run(["python3", sync_script_path], capture_output=True, text=True, check=False)
|
||||
|
||||
if result.returncode != 0:
|
||||
print("❌ ERROR: Database sync failed.")
|
||||
print(result.stderr)
|
||||
return False
|
||||
|
||||
print("✅ Sync successful.")
|
||||
return True
|
||||
|
||||
def process_lead(identifier):
|
||||
"""
|
||||
Orchestrates the full enrichment and copy generation for a single lead.
|
||||
"""
|
||||
print(f"\n======= PROCESSING LEAD: {identifier} =======")
|
||||
|
||||
# --- Step 2: Enrich Company (if necessary) ---
|
||||
print("\n--- [Step 2: Check/Enrich Company Data] ---")
|
||||
# ce_data = handle_company_workflow(identifier) # Example of direct import
|
||||
# if not ce_data or 'error' in ce_data:
|
||||
# print(f"❌ Failed to enrich '{identifier}'. Aborting.")
|
||||
# return
|
||||
print("... (Placeholder for Enrichment Logic)")
|
||||
print("✅ Enrichment complete.")
|
||||
|
||||
|
||||
# --- Step 3: Generate Sniper Copy ---
|
||||
print("\n--- [Step 3: Generate Sniper Copy] ---")
|
||||
# sniper_copy = generate_copy(ce_data['data']['id'])
|
||||
# print("\nGENERATED COPY:\n", sniper_copy)
|
||||
print("... (Placeholder for Sniper Copy Generation)")
|
||||
print("✅ Copy generation complete.")
|
||||
|
||||
# --- Step 4: Finalize & Log ---
|
||||
print("\n--- [Step 4: Finalizing] ---")
|
||||
log_throughput(identifier)
|
||||
print(f"✅ Successfully processed lead '{identifier}'.")
|
||||
print("============================================")
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="GTM Lead Engine Orchestrator.")
|
||||
parser.add_argument("leads", nargs='+', help="One or more company names or SuperOffice IDs to process.")
|
||||
parser.add_argument("--skip-sync", action="store_true", help="Skip the initial database sync for faster iteration.")
|
||||
args = parser.parse_args()
|
||||
|
||||
print("🚀 GTM Lead Engine Orchestrator started.")
|
||||
|
||||
setup_environment()
|
||||
|
||||
if not args.skip_sync:
|
||||
if not run_sync():
|
||||
sys.exit(1) # Exit if sync fails
|
||||
else:
|
||||
print("\n--- [Skipping Step 1: Database Sync] ---")
|
||||
|
||||
for lead_identifier in args.leads:
|
||||
process_lead(lead_identifier)
|
||||
|
||||
print("\n🎉 Orchestration complete for all leads. 🎉")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1,75 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from datetime import datetime
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
# Configuration
|
||||
NOTION_TOKEN = "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"
|
||||
PAGE_ID = "2ff88f42854480008314c9013414d1d0"
|
||||
BERLIN_TZ = ZoneInfo("Europe/Berlin")
|
||||
|
||||
def add_status_to_notion():
|
||||
headers = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
# 1. Update the 'Total Duration (h)' field
|
||||
# First, get current value
|
||||
resp = requests.get(f"https://api.notion.com/v1/pages/{PAGE_ID}", headers=headers)
|
||||
page_data = resp.json()
|
||||
current_hours = page_data.get("properties", {}).get("Total Duration (h)", {}).get("number") or 0.0
|
||||
new_hours = current_hours + 3.2
|
||||
|
||||
# Update property
|
||||
update_payload = {
|
||||
"properties": {
|
||||
"Total Duration (h)": {"number": new_hours},
|
||||
"Status": {"status": {"name": "Doing"}}
|
||||
}
|
||||
}
|
||||
requests.patch(f"https://api.notion.com/v1/pages/{PAGE_ID}", headers=headers, json=update_payload)
|
||||
|
||||
# 2. Append the Status Update Block
|
||||
timestamp = datetime.now(BERLIN_TZ).strftime('%Y-%m-%d %H:%M')
|
||||
report_content = (
|
||||
"Investierte Zeit in dieser Session: 03:12\n"
|
||||
"Neuer Status: Doing\n\n"
|
||||
"Arbeitszusammenfassung:\n"
|
||||
"Wir haben heute den entscheidenden technischen Durchbruch bei der bidirektionalen Datensynchronisation zwischen dem Company Explorer (CE) und SuperOffice CRM (SO) erzielt.\n\n"
|
||||
"1. Infrastruktur-Stabilisierung: Das Git-Repository wurde über eine interne Docker-Netzwerk-Verbindung (gitea-internal) stabil angebunden.\n"
|
||||
"2. Pipeline-Durchstich (SO -> CE): Firmenstammdaten aus SuperOffice (Contact ID 2) werden sauber in den Company Explorer übertragen.\n"
|
||||
"3. Round-Trip & Write-Back (CE -> SO): Das Protokoll für den Rückschreibeprozess wurde geknackt. Erkenntnis: SuperOffice ignoriert UrlAddress beim PUT, wir nutzen jetzt das Urls-Array. Pflichtfelder wie Number2 werden nun explizit mitgegeben."
|
||||
)
|
||||
|
||||
block_payload = {
|
||||
"children": [
|
||||
{
|
||||
"object": "block",
|
||||
"type": "heading_2",
|
||||
"heading_2": {
|
||||
"rich_text": [{"type": "text", "text": {"content": f"🤖 Status-Update ({timestamp} Berlin Time)"}}]
|
||||
}
|
||||
},
|
||||
{
|
||||
"object": "block",
|
||||
"type": "code",
|
||||
"code": {
|
||||
"rich_text": [{"type": "text", "text": {"content": report_content}}],
|
||||
"language": "yaml"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
final_resp = requests.patch(f"https://api.notion.com/v1/blocks/{PAGE_ID}/children", headers=headers, json=block_payload)
|
||||
|
||||
if final_resp.status_code == 200:
|
||||
print(f"✅ SUCCESS: Notion Task updated. Total hours now: {new_hours}")
|
||||
else:
|
||||
print(f"❌ ERROR: {final_resp.text}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
add_status_to_notion()
|
||||
66
scripts/append_task_updates.py
Normal file
66
scripts/append_task_updates.py
Normal file
@@ -0,0 +1,66 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
# IDs from yesterday
|
||||
TASKS = {
|
||||
"Pains Gains Vertical": "2ff88f42-8544-8050-8245-c3bb852058f4",
|
||||
"Segmentierung Bestand": "2ff88f42-8544-808f-862b-c30ab2f29783",
|
||||
"Matrixmultiplikation": "2ff88f42-8544-8079-a23e-c248e35b09a0"
|
||||
}
|
||||
|
||||
UPDATES = {
|
||||
"Pains Gains Vertical": "Update 17.02.: ✅ Entwurf in Notion finalisiert und detailliert (inkl. Hygiene-Fokus). Bereit für Review am Freitag.",
|
||||
"Segmentierung Bestand": "Update 17.02.: ✅ Company Explorer Schema erweitert (V2). Bereit für Excel-Import.",
|
||||
"Matrixmultiplikation": "Update 17.02.: ✅ Logik '3+1' (Prio Produkt + Sekundär bei Ops-Rolle) in Datenstruktur abgebildet."
|
||||
}
|
||||
|
||||
def append_block(page_id, text):
|
||||
url = f"https://api.notion.com/v1/blocks/{page_id}/children"
|
||||
payload = {
|
||||
"children": [
|
||||
{
|
||||
"object": "block",
|
||||
"type": "paragraph",
|
||||
"paragraph": {
|
||||
"rich_text": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": {
|
||||
"content": text,
|
||||
"link": None
|
||||
},
|
||||
"annotations": {
|
||||
"bold": True, # Make it stand out
|
||||
"italic": False,
|
||||
"strikethrough": False,
|
||||
"underline": False,
|
||||
"code": False,
|
||||
"color": "default"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
resp = requests.patch(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print(f"✅ Appended to {page_id}")
|
||||
else:
|
||||
print(f"❌ Error {page_id}: {resp.text}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
for name, page_id in TASKS.items():
|
||||
if name in UPDATES:
|
||||
append_block(page_id, UPDATES[name])
|
||||
@@ -1,115 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
def find_db_id(query_name):
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": query_name, "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
# Cache for product names to avoid API spam
|
||||
product_cache = {}
|
||||
|
||||
def resolve_product_name(relation_ids):
|
||||
if not relation_ids:
|
||||
return "None"
|
||||
|
||||
names = []
|
||||
for rel in relation_ids:
|
||||
page_id = rel['id']
|
||||
if page_id in product_cache:
|
||||
names.append(product_cache[page_id])
|
||||
continue
|
||||
|
||||
url = f"https://api.notion.com/v1/pages/{page_id}"
|
||||
resp = requests.get(url, headers=HEADERS)
|
||||
if resp.status_code == 200:
|
||||
props = resp.json().get("properties", {})
|
||||
# Assume Product DB has a Title field called "Name" or "Product Name"
|
||||
# We iterate to find the title
|
||||
title = "Unknown"
|
||||
for key, val in props.items():
|
||||
if val['id'] == 'title': # The title property always has id 'title'
|
||||
if val['title']:
|
||||
title = val['title'][0]['plain_text']
|
||||
break
|
||||
product_cache[page_id] = title
|
||||
names.append(title)
|
||||
else:
|
||||
names.append("Error fetching Product")
|
||||
|
||||
return ", ".join(names)
|
||||
|
||||
def audit_industries():
|
||||
db_id = find_db_id("Industries")
|
||||
if not db_id:
|
||||
print("❌ Industries DB not found.")
|
||||
return
|
||||
|
||||
print(f"--- Auditing Industries DB ({db_id}) ---")
|
||||
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
resp = requests.post(url, headers=HEADERS, json={})
|
||||
|
||||
if resp.status_code != 200:
|
||||
print(f"Error: {resp.text}")
|
||||
return
|
||||
|
||||
pages = resp.json().get("results", [])
|
||||
|
||||
# We want to see: Vertical Name | Status | Primary Product (Resolved) | Notes Snippet
|
||||
print(f"{'Vertical':<35} | {'Status':<15} | {'Primary Product':<30} | {'Notes (Snippet)'}")
|
||||
print("-" * 120)
|
||||
|
||||
for page in pages:
|
||||
props = page['properties']
|
||||
|
||||
# Name
|
||||
name = "N/A"
|
||||
if "Vertical" in props and props["Vertical"]["title"]:
|
||||
name = props["Vertical"]["title"][0]["plain_text"]
|
||||
elif "Name" in props and props["Name"]["title"]: # Fallback
|
||||
name = props["Name"]["title"][0]["plain_text"]
|
||||
|
||||
# Filter for the ones we touched or are interested in
|
||||
# (Optional: remove filter to see all)
|
||||
|
||||
# Status
|
||||
status = ""
|
||||
if "Freigabe" in props:
|
||||
if props["Freigabe"]["type"] == "status" and props["Freigabe"]["status"]:
|
||||
status = props["Freigabe"]["status"]["name"]
|
||||
elif props["Freigabe"]["type"] == "select" and props["Freigabe"]["select"]:
|
||||
status = props["Freigabe"]["select"]["name"]
|
||||
|
||||
# Primary Product (Relation)
|
||||
product_name = "None"
|
||||
if "Primary Product Category" in props and props["Primary Product Category"]["relation"]:
|
||||
product_name = resolve_product_name(props["Primary Product Category"]["relation"])
|
||||
|
||||
# Notes
|
||||
notes = ""
|
||||
if "Notes" in props and props["Notes"]["rich_text"]:
|
||||
full_note = props["Notes"]["rich_text"][0]["plain_text"]
|
||||
notes = (full_note[:40] + '...') if len(full_note) > 40 else full_note
|
||||
|
||||
if name != "N/A":
|
||||
print(f"{name:<35} | {status:<15} | {product_name:<30} | {notes}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
audit_industries()
|
||||
69
scripts/check_notion_tasks.py
Normal file
69
scripts/check_notion_tasks.py
Normal file
@@ -0,0 +1,69 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
PROJECT_ID = "2ea88f42-8544-8074-9ad8-c24d283bc1c9"
|
||||
|
||||
def find_tasks_db():
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": "Tasks", "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def get_project_tasks(db_id):
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
# We look for tasks linked to the project ID via a relation property (usually "Project")
|
||||
payload = {
|
||||
"filter": {
|
||||
"property": "Project",
|
||||
"relation": {
|
||||
"contains": PROJECT_ID
|
||||
}
|
||||
}
|
||||
}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code != 200:
|
||||
print(f"Error querying tasks: {resp.text}")
|
||||
return []
|
||||
|
||||
return resp.json().get("results", [])
|
||||
|
||||
def print_tasks():
|
||||
db_id = find_tasks_db()
|
||||
if not db_id:
|
||||
print("❌ Tasks DB not found.")
|
||||
return
|
||||
|
||||
print(f"--- Tasks for Project {PROJECT_ID} ---")
|
||||
tasks = get_project_tasks(db_id)
|
||||
|
||||
for task in tasks:
|
||||
props = task['properties']
|
||||
name = "Unknown"
|
||||
if "Name" in props and props["Name"]["title"]:
|
||||
name = props["Name"]["title"][0]["plain_text"]
|
||||
elif "Task" in props and props["Task"]["title"]:
|
||||
name = props["Task"]["title"][0]["plain_text"]
|
||||
|
||||
status = "Unknown"
|
||||
if "Status" in props and props["Status"]["status"]:
|
||||
status = props["Status"]["status"]["name"]
|
||||
|
||||
print(f"- [{status}] {name} ({task['id']})")
|
||||
|
||||
if __name__ == "__main__":
|
||||
print_tasks()
|
||||
@@ -1,27 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
def discover_dbs():
|
||||
token = os.getenv("NOTION_API_KEY")
|
||||
headers = {
|
||||
"Authorization": f"Bearer {token}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"filter": {"value": "database", "property": "object"}}
|
||||
|
||||
resp = requests.post(url, headers=headers, json=payload)
|
||||
results = resp.json().get("results", [])
|
||||
|
||||
print("--- Gefundene Datenbanken ---")
|
||||
for db in results:
|
||||
title = db.get("title", [{}])[0].get("plain_text", "Unbekannt")
|
||||
print(f"Name: {title} | ID: {db['id']}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
discover_dbs()
|
||||
@@ -1,265 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
# --- Load Product Mapping ---
|
||||
try:
|
||||
with open("data/product_mapping.json", "r") as f:
|
||||
PRODUCT_MAP = json.load(f)
|
||||
except FileNotFoundError:
|
||||
print("❌ Product mapping not found. Run fetch_product_mapping.py first.")
|
||||
exit(1)
|
||||
|
||||
# Helper to find DB ID
|
||||
def find_db_id(query_name):
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": query_name, "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def get_page_by_vertical(db_id, vertical_name):
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
# Using 'Vertical' as the title property name based on previous audit
|
||||
payload = {
|
||||
"filter": {
|
||||
"property": "Vertical",
|
||||
"title": {"equals": vertical_name}
|
||||
}
|
||||
}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]
|
||||
return None
|
||||
|
||||
def update_page(page_id, properties):
|
||||
url = f"https://api.notion.com/v1/pages/{page_id}"
|
||||
payload = {"properties": properties}
|
||||
resp = requests.patch(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print(f"✅ Updated '{page_id}'")
|
||||
else:
|
||||
print(f"❌ Error updating '{page_id}': {resp.text}")
|
||||
|
||||
def create_page(db_id, properties):
|
||||
url = "https://api.notion.com/v1/pages"
|
||||
payload = {"parent": {"database_id": db_id}, "properties": properties}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print(f"✅ Created new page")
|
||||
else:
|
||||
print(f"❌ Error creating page: {resp.text}")
|
||||
|
||||
# --- CONTENT DEFINITION ---
|
||||
|
||||
# Format: Vertical -> { props... }
|
||||
UPDATES = {
|
||||
"Healthcare - Care Home": {
|
||||
"product": "Cleaning Indoor Roboter (Wet Surface)",
|
||||
"pains": """[Primary Product: Cleaning]
|
||||
- Infektionsrisiko: Mangelnde Bodenhygiene und Keimverschleppung in sensiblen Bereichen gefährden Bewohner.
|
||||
- Dokumentationspflicht: Lückenlose Nachweise für Hygiene-Audits binden wertvolle Pflegezeit.
|
||||
- Personalmangel: Reinigungskräfte fehlen, Standards können manuell kaum gehalten werden.
|
||||
|
||||
[Secondary Product: Service]
|
||||
- Pflegeressourcen: Fachkräfte binden bis zu 30% ihrer Zeit mit nicht-pflegerischen Transportwegen (Essen/Wäsche).
|
||||
- Körperliche Belastung: Schweres Heben und weite Wege führen zu krankheitsbedingten Ausfällen im Pflegeteam.""",
|
||||
"gains": """[Primary Product: Cleaning]
|
||||
- Audit-Sicherheit: Automatisierte, protokollierte Reinigung sichert Compliance ohne Mehraufwand.
|
||||
- Entlastung Housekeeping: Personal konzentriert sich auf Sichtreinigung und Desinfektion statt Bodenfläche.
|
||||
|
||||
[Secondary Product: Service]
|
||||
- Mehr Zeit am Patienten: Reduktion der Laufwege gibt Pflegekräften 2-3 Std./Schicht zurück.
|
||||
- Mitarbeiterzufriedenheit: Reduktion körperlicher Belastung senkt Krankenstand.""",
|
||||
"ops_focus": True,
|
||||
"status": "Freigegeben",
|
||||
"notes": "Prio 1: Reinigung. Prio 2: Service (Essen). Fokus auf Fachkräftemangel & Hygiene."
|
||||
},
|
||||
"Healthcare - Hospital": {
|
||||
"product": "Cleaning Indoor Roboter (Wet Surface)",
|
||||
"pains": """[Primary Product: Cleaning]
|
||||
- Infektionsschutz: Hohe Frequenz an Patientenbewegungen erfordert permanente Desinfektion der Böden.
|
||||
- Audit-Druck: Behördliche Auflagen verlangen lückenlose Dokumentation, die manuell kaum leistbar ist.
|
||||
- Kostendruck: Steigende Personalkosten bei fixen Fallpauschalen zwingen zur Effizienzsteigerung.
|
||||
|
||||
[Secondary Product: Service]
|
||||
- Logistik-Aufwand: Transport von Proben, Wäsche und Essen bindet Pflegepersonal in unproduktiven Wegezeiten.""",
|
||||
"gains": """[Primary Product: Cleaning]
|
||||
- Hygiene-Standard: 24/7 gleichbleibende Reinigungsqualität reduziert Keimbelastung messbar.
|
||||
- Compliance: Automatische Protokollierung aller Reinigungsfahrten für Audits.
|
||||
|
||||
[Secondary Product: Service]
|
||||
- Prozess-Effizienz: Automatisierter Warentransport entlastet Fachpersonal für medizinische Aufgaben.""",
|
||||
"ops_focus": True,
|
||||
"status": "Freigegeben",
|
||||
"notes": "Prio 1: Reinigung (Alex Veto). Service ist 'nice to have'. KPI: Hygiene-Sicherheit."
|
||||
},
|
||||
"Leisure - Entertainment": {
|
||||
"product": "Service Roboter", # FIX: Changed from Cleaning to Service
|
||||
"pains": """[Primary Product: Service]
|
||||
- Service-Engpass: Umsatzverlust zu Stoßzeiten, da Personal nicht schnell genug Getränke/Snacks nachliefert.
|
||||
- Personalmangel: Schwierige Besetzung von Spätschichten führt zu geschlossenen Stationen/Bahnen.
|
||||
- Wartezeiten: Gäste sind unzufrieden, wenn Bestellungen zu lange dauern.
|
||||
|
||||
[Secondary Product: Cleaning]
|
||||
- Bodenverschmutzung: Klebrige Böden (Getränke/Popcorn) im Foyer stören das Gästeerlebnis.""",
|
||||
"gains": """[Primary Product: Service]
|
||||
- Umsatzsteigerung: Permanente Verfügbarkeit von Snacks/Getränken direkt am Platz (Cross-Selling).
|
||||
- Erlebnis-Faktor: Innovative Roboter begeistern Gäste und fördern Social-Media-Sichtbarkeit.
|
||||
- Entlastung: Servicepersonal hat mehr Zeit für Gästebetreuung statt Laufwege.""",
|
||||
"ops_focus": True, # Keep secondary focus plausible
|
||||
"status": "Freigegeben",
|
||||
"notes": "Prio 1: Service Robotik (BellaBot). Cleaning nur Prio 2 (Foyer/Gänge)."
|
||||
},
|
||||
"Logistics - Warehouse": {
|
||||
"product": "Cleaning Outdoor Roboter (Sweeper)",
|
||||
"pains": """[Primary Product: Sweeper]
|
||||
- Prozesssicherheit: Staub auf Sensoren und Lichtschranken führt zu Anlagenstörungen und Produktionsstopps.
|
||||
- Arbeitssicherheit: Verschmutzte Fahrwege durch Palettenreste/Staub erhöhen das Unfallrisiko.
|
||||
- Manuelle Bindung: Fachkräfte müssen kehren statt kommissionieren.
|
||||
|
||||
[Secondary Product: Cleaning Wet]
|
||||
- Hartnäckige Verschmutzungen: Öl/Reifenabrieb erfordern Nassreinigung, die manuell zeitintensiv ist.""",
|
||||
"gains": """[Primary Product: Sweeper]
|
||||
- Staubfreie Umgebung: Werterhalt des Hallenbodens und Schutz empfindlicher Ware/Anlagen.
|
||||
- Produktivität: Reinigung erfolgt parallel zum Betrieb oder nachts, ohne Störung.
|
||||
- Sicherheit: Saubere Fahrwege reduzieren Unfallrisiko für Flurförderzeuge.""",
|
||||
"ops_focus": True,
|
||||
"status": "Freigegeben",
|
||||
"notes": "Prio 1: Sweeper (Staub). Prio 2: Wet. Transport schwierig wegen Paletten."
|
||||
},
|
||||
"Tech - Data Center": {
|
||||
"product": "Security Roboter",
|
||||
"pains": """[Primary Product: Security]
|
||||
- Sicherheitsrisiko: Unbefugter Zutritt in Sicherheitsbereiche muss lückenlos detektiert werden (24/7).
|
||||
- Personalbindung: Wachpersonal ist teuer und kann nicht überall gleichzeitig sein.
|
||||
|
||||
[Secondary Product: Cleaning]
|
||||
- Feinstaub: Staubpartikel in Serverräumen gefährden Hardware und Kühlung.""",
|
||||
"gains": """[Primary Product: Security]
|
||||
- Lückenlose Überwachung: Permanente Patrouille und sofortige Alarmierung ohne Personalbindung.
|
||||
- Dokumentation: Video- und Sensorprotokolle aller Ereignisse.
|
||||
|
||||
[Secondary Product: Cleaning]
|
||||
- Ausfallsicherheit: Staubfreie Umgebung verlängert Hardware-Lebensdauer.""",
|
||||
"ops_focus": True,
|
||||
"status": "Klärrungsbedarf", # New, needs review
|
||||
"notes": "Neu angelegt. Prio 1 Security (lt. Transkript). Prio 2 Cleaning (Staub)."
|
||||
},
|
||||
"Reinigungsdienstleister": {
|
||||
"product": "Cleaning Indoor Roboter (Wet Surface)",
|
||||
"pains": """[Primary Product: Cleaning]
|
||||
- Personalmangel: Schwierigkeit, zuverlässiges Personal für alle Objekte zu finden.
|
||||
- Kostendruck: Geringe Margen bei Ausschreibungen erfordern hohe Effizienz.
|
||||
- Qualitätsschwankungen: Manuelle Reinigung variiert stark, Kunden beschweren sich.
|
||||
- Fluktuation: Hoher Aufwand für ständige Neueinarbeitung.""",
|
||||
"gains": """[Primary Product: Cleaning]
|
||||
- Skalierbarkeit: Roboter übernehmen Flächenleistung, Personal macht Detailreinigung.
|
||||
- Innovation: Wettbewerbsvorteil bei Ausschreibungen durch Technologie-Einsatz.
|
||||
- Kalkulationssicherheit: Fixe Kosten statt variabler Personalkosten/Krankheitstage.""",
|
||||
"ops_focus": False,
|
||||
"status": "Klärrungsbedarf",
|
||||
"notes": "Neu angelegt. Zielgruppe: Wisag, Dussmann etc. (Alex: Größter Markt)."
|
||||
},
|
||||
"Infrastructure - Communities": {
|
||||
"product": "Cleaning Indoor Roboter (Wet Surface)",
|
||||
"pains": """[Primary Product: Cleaning]
|
||||
- Großflächen-Reinigung: Sporthallen, Aulen und Flure binden enorm viele Personalstunden.
|
||||
- Budget-Druck: Kommunen müssen sparen, Reinigungskosten sind großer Posten.
|
||||
- Nutzungs-Konflikte: Reinigung muss in engen Zeitfenstern zwischen Schul/Vereinsnutzung erfolgen.""",
|
||||
"gains": """[Primary Product: Cleaning]
|
||||
- Kosteneffizienz: Reduktion der Reinigungskosten pro Quadratmeter.
|
||||
- Flexibilität: Reinigung kann nachts oder in Randzeiten erfolgen.
|
||||
- Werterhalt: Schonende, regelmäßige Reinigung verlängert Lebensdauer von Sportböden.""",
|
||||
"ops_focus": False,
|
||||
"status": "Klärrungsbedarf",
|
||||
"notes": "Neu angelegt (Schulen, Gemeinden)."
|
||||
},
|
||||
"Infrastructure Parking": {
|
||||
"product": "Cleaning Outdoor Roboter (Sweeper)",
|
||||
"pains": """[Primary Product: Sweeper]
|
||||
- Außenwirkung: Verschmutzte Parkflächen/Müll schaden dem Image (erster Eindruck).
|
||||
- Manuelle Arbeit: Fegen von großen Außenflächen ist personalintensiv und unbeliebt.
|
||||
- Umwelt: Müll gelangt in die Umgebung/Kanalisation.""",
|
||||
"gains": """[Primary Product: Sweeper]
|
||||
- Gepflegtes Erscheinungsbild: Täglich saubere Außenanlagen.
|
||||
- Autonomie: Roboter reinigt selbstständig, auch bei schlechtem Wetter.
|
||||
- Entlastung: Hausmeister kann sich um Wartung kümmern statt Fegen.""",
|
||||
"ops_focus": False,
|
||||
"status": "Klärrungsbedarf",
|
||||
"notes": "Neu angelegt (Parkplätze, Außenanlagen)."
|
||||
}
|
||||
}
|
||||
|
||||
def run_enrichment():
|
||||
db_id = find_db_id("Industries")
|
||||
if not db_id:
|
||||
print("❌ Industries DB not found.")
|
||||
return
|
||||
|
||||
print(f"--- Enriching Verticals in DB {db_id} ---")
|
||||
|
||||
for vertical, data in UPDATES.items():
|
||||
# Resolve Product ID
|
||||
prod_id = PRODUCT_MAP.get(data["product"])
|
||||
if not prod_id:
|
||||
print(f"❌ Product '{data['product']}' not found in map. Skipping {vertical}.")
|
||||
continue
|
||||
|
||||
# Prepare Properties
|
||||
props = {
|
||||
"Pains": {"rich_text": [{"text": {"content": data["pains"]}}]},
|
||||
"Gains": {"rich_text": [{"text": {"content": data["gains"]}}]},
|
||||
"Primary Product Category": {"relation": [{"id": prod_id}]},
|
||||
"Notes": {"rich_text": [{"text": {"content": data["notes"]}}]},
|
||||
# Handle Status (Try Select first, then Status)
|
||||
# We assume "Freigabe" exists
|
||||
}
|
||||
|
||||
# Add checkbox if present in logic
|
||||
if "ops_focus" in data:
|
||||
props["Ops Focus: Secondary"] = {"checkbox": data["ops_focus"]}
|
||||
|
||||
# Check if page exists
|
||||
page = get_page_by_vertical(db_id, vertical)
|
||||
|
||||
if page:
|
||||
# Update existing
|
||||
# Add Status Update
|
||||
# (Note: Logic to detect Select vs Status type is needed, but we assume Select/Status name is consistent)
|
||||
# For robustness, we check the property type in the page object
|
||||
status_type = page['properties'].get("Freigabe", {}).get("type")
|
||||
if status_type == "status":
|
||||
props["Freigabe"] = {"status": {"name": data["status"]}}
|
||||
elif status_type == "select":
|
||||
props["Freigabe"] = {"select": {"name": data["status"]}}
|
||||
|
||||
print(f"Updating '{vertical}'...")
|
||||
update_page(page['id'], props)
|
||||
else:
|
||||
# Create new
|
||||
print(f"Creating new vertical '{vertical}'...")
|
||||
props["Vertical"] = {"title": [{"text": {"content": vertical}}]}
|
||||
# Guess status type (usually Select or Status) - Try Status first as default in new Notion DBs
|
||||
# Or omit status if unsure, but we want to set it.
|
||||
# We'll try Status format.
|
||||
props["Freigabe"] = {"status": {"name": data["status"]}}
|
||||
create_page(db_id, props)
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_enrichment()
|
||||
@@ -1,65 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
def find_db_id(query_name):
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": query_name, "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def fetch_products():
|
||||
# Find Product DB (it's likely named "Product Categories" or similar based on schema)
|
||||
# Or search for "Products"
|
||||
db_id = find_db_id("Product Categories")
|
||||
if not db_id:
|
||||
db_id = find_db_id("Products") # Fallback
|
||||
|
||||
if not db_id:
|
||||
print("❌ Could not find Product Database.")
|
||||
return
|
||||
|
||||
print(f"--- Fetching Products from DB {db_id} ---")
|
||||
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
resp = requests.post(url, headers=HEADERS, json={})
|
||||
|
||||
products = {}
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
for page in results:
|
||||
props = page['properties']
|
||||
# Find Title
|
||||
name = "Unknown"
|
||||
if "Name" in props and props["Name"]["title"]:
|
||||
name = props["Name"]["title"][0]["plain_text"]
|
||||
elif "Product Name" in props and props["Product Name"]["title"]:
|
||||
name = props["Product Name"]["title"][0]["plain_text"]
|
||||
|
||||
products[name] = page['id']
|
||||
print(f"Found: {name} ({page['id']})")
|
||||
|
||||
# Save to file
|
||||
os.makedirs("data", exist_ok=True)
|
||||
with open("data/product_mapping.json", "w") as f:
|
||||
json.dump(products, f, indent=4)
|
||||
print("✅ Saved to data/product_mapping.json")
|
||||
else:
|
||||
print(f"Error: {resp.text}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
fetch_products()
|
||||
@@ -1,93 +0,0 @@
|
||||
import sqlite3
|
||||
import os
|
||||
import json
|
||||
import requests
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# Load ENV for Gemini API
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env", override=True)
|
||||
|
||||
class LeadHookService:
|
||||
def __init__(self, db_path):
|
||||
self.db_path = db_path
|
||||
self.api_key = os.getenv("GEMINI_API_KEY")
|
||||
|
||||
def _get_company_data(self, company_id):
|
||||
conn = sqlite3.connect(self.db_path)
|
||||
conn.row_factory = sqlite3.Row
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Get company and metrics
|
||||
cursor.execute("SELECT * FROM companies WHERE id = ?", (company_id,))
|
||||
company = cursor.fetchone()
|
||||
|
||||
if not company:
|
||||
return None
|
||||
|
||||
data = dict(company)
|
||||
conn.close()
|
||||
return data
|
||||
|
||||
def build_combined_context(self, company_data):
|
||||
# Build the 'combined' string from CE facts
|
||||
parts = []
|
||||
parts.append(f"Name: {company_data.get('name')}")
|
||||
parts.append(f"Branche: {company_data.get('industry_ai')}")
|
||||
|
||||
if company_data.get('calculated_metric_value'):
|
||||
parts.append(f"Metrik: {company_data.get('calculated_metric_value')} {company_data.get('calculated_metric_unit')}")
|
||||
|
||||
# Add a hint about the core business from status/city
|
||||
parts.append(f"Standort: {company_data.get('city')}")
|
||||
|
||||
return " | ".join(parts)
|
||||
|
||||
def generate_hook(self, company_id):
|
||||
company_data = self._get_company_data(company_id)
|
||||
if not company_data:
|
||||
return "Company not found."
|
||||
|
||||
combined = self.build_combined_context(company_data)
|
||||
display_name = company_data.get('name').split(' ')[0] # Simple Kurzname logic
|
||||
|
||||
prompt = f"""
|
||||
Du bist ein exzellenter B2B-Stratege und Texter.
|
||||
Deine Aufgabe ist es, einen hochpersonalisierten, scharfsinnigen und wertschätzenden Einleitungssatz für eine E-Mail zu formulieren.
|
||||
|
||||
--- Unternehmenskontext ---
|
||||
Kurzname: {display_name}
|
||||
Beschreibung: {combined}
|
||||
|
||||
--- Stilvorgaben ---
|
||||
1. Analysiere das Kerngeschäft: Was ist die zentrale physische Herausforderung (z.B. Sauberkeit in Nassbereichen, Logistik-Effizienz, Objektschutz)?
|
||||
2. KEINE ZAHLEN: Erwähne niemals konkrete Zahlen (Besucherzahlen, m², Anzahl Pools). Nutze stattdessen qualitative Begriffe wie "weitläufig", "hochfrequent", "komplex" oder "marktführend".
|
||||
3. Identifiziere den Hebel: Was ist der Erfolgsfaktor (z.B. Gäste-Zufriedenheit, Prozessstabilität, Sicherheit)?
|
||||
4. Formuliere den Satz (20-35 Wörter): Elegant, aktiv, KEINE Floskeln.
|
||||
5. WICHTIG: Formuliere als positive Beobachtung über eine Kernkompetenz.
|
||||
|
||||
Deine Ausgabe: NUR der finale Satz.
|
||||
"""
|
||||
|
||||
# Call Gemini (Simplified for POC)
|
||||
headers = {"Content-Type": "application/json"}
|
||||
payload = {
|
||||
"contents": [{"parts": [{"text": prompt}]}]
|
||||
}
|
||||
url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key={self.api_key}"
|
||||
|
||||
resp = requests.post(url, headers=headers, json=payload)
|
||||
result = resp.json()
|
||||
|
||||
try:
|
||||
hook_text = result['candidates'][0]['content']['parts'][0]['text'].strip()
|
||||
return hook_text
|
||||
except:
|
||||
return f"Error generating hook: {result}"
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Test with CE-ID 1 (Therme Erding)
|
||||
db = "/home/node/clawd/repos/brancheneinstufung2/company_explorer_local.db"
|
||||
service = LeadHookService(db)
|
||||
print(f"--- Testing LeadHookService for ID 1 ---")
|
||||
hook = service.generate_hook(1)
|
||||
print(f"GENERATED HOOK:\n{hook}")
|
||||
@@ -1,123 +0,0 @@
|
||||
import sqlite3
|
||||
import os
|
||||
import json
|
||||
import requests
|
||||
import argparse
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# --- Configuration & Setup ---
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env", override=True)
|
||||
DB_PATH = "/home/node/clawd/repos/brancheneinstufung2/company_explorer_local.db"
|
||||
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
|
||||
|
||||
|
||||
class SniperGenerator:
|
||||
def __init__(self, db_path=DB_PATH):
|
||||
self.db_path = db_path
|
||||
# TODO: Initialize Notion client to get Vertical/Persona data
|
||||
# TODO: Load Marketing Report KPIs into memory
|
||||
|
||||
def get_lead_data(self, company_id):
|
||||
"""Gathers all necessary data for a lead from the local DB."""
|
||||
conn = sqlite3.connect(self.db_path)
|
||||
conn.row_factory = sqlite3.Row
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("SELECT * FROM companies WHERE id = ?", (company_id,))
|
||||
company_data = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
if not company_data:
|
||||
return None
|
||||
|
||||
return dict(company_data)
|
||||
|
||||
def select_product_and_persona(self, company_data, target_role):
|
||||
"""
|
||||
Implements the '3+1' rule to decide which product to pitch.
|
||||
Placeholder logic - will be replaced with Notion data.
|
||||
"""
|
||||
print(f"🎯 Selecting product for role '{target_role}' in industry '{company_data.get('industry_ai')}'...")
|
||||
# Placeholder for the 3+1 logic
|
||||
# if target_role in ["Wirtschaftl. Entscheider", "Infrastruktur-Verantw."]:
|
||||
# return "Primary"
|
||||
# if target_role == "Innovations-Treiber":
|
||||
# return "Secondary"
|
||||
# if target_role == "Operativer Entscheider":
|
||||
# # Here we would check the "Ops Focus: Secondary?" checkbox from Notion
|
||||
# return "Primary" # Default
|
||||
|
||||
# For now, we default to the primary product (Cleaning)
|
||||
print("-> Defaulting to 'Primary Product' (Cleaning).")
|
||||
return "Cleaning"
|
||||
|
||||
|
||||
def generate_copy(self, company_id, target_role="Wirtschaftl. Entscheider"):
|
||||
"""
|
||||
Generates the 3-sentence sniper copy for a given company and role.
|
||||
"""
|
||||
# 1. Gather Data
|
||||
lead_data = self.get_lead_data(company_id)
|
||||
if not lead_data:
|
||||
return "Error: Company data not found."
|
||||
|
||||
# 2. Decide on Product (using 3+1 rule)
|
||||
product_to_pitch = self.select_product_and_persona(lead_data, target_role)
|
||||
|
||||
# 3. Get Social Proof KPIs (from Marketing Report)
|
||||
# Placeholder - using hardcoded values from the report
|
||||
kpis = {
|
||||
"cost_reduction": "10-25%",
|
||||
"time_saving": "20-40%"
|
||||
}
|
||||
|
||||
# 4. Construct Master Prompt
|
||||
# This is a simplified version for now
|
||||
prompt = f"""
|
||||
Du bist ein Weltklasse B2B-Stratege. Deine Aufgabe ist es, eine 3-Satz-E-Mail-Einleitung im '1,5°-Stil' zu erstellen.
|
||||
|
||||
**Regeln:**
|
||||
- Satz 1 (Firma): Zeige, dass du das Geschäftsmodell und die zentrale Herausforderung verstanden hast. KEINE ZAHLEN, nur qualitative Größe.
|
||||
- Satz 2 (Persona): Sprich den spezifischen Schmerz der Zielrolle an und verbinde ihn mit dem Produkt '{product_to_pitch}'.
|
||||
- Satz 3 (Social Proof): Untermauere die Lösung mit einem konkreten KPI von Marktbegleitern.
|
||||
|
||||
**Daten:**
|
||||
- Firma: {lead_data.get('name')}
|
||||
- Branche (KI): {lead_data.get('industry_ai')}
|
||||
- Standort: {lead_data.get('city')}
|
||||
- Rolle: {target_role}
|
||||
- KPI 1 (Kosten): {kpis['cost_reduction']}
|
||||
- KPI 2 (Zeit): {kpis['time_saving']}
|
||||
|
||||
**Output:** Nur die 3 Sätze. Sonst nichts.
|
||||
"""
|
||||
|
||||
# 5. Call Gemini API
|
||||
print("📞 Calling Gemini to generate copy...")
|
||||
headers = {"Content-Type": "application/json"}
|
||||
payload = {"contents": [{"parts": [{"text": prompt}]}]}
|
||||
url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key={GEMINI_API_KEY}"
|
||||
|
||||
try:
|
||||
resp = requests.post(url, headers=headers, json=payload, timeout=20)
|
||||
resp.raise_for_status()
|
||||
result = resp.json()
|
||||
copy_text = result['candidates'][0]['content']['parts'][0]['text'].strip()
|
||||
return copy_text
|
||||
except Exception as e:
|
||||
return f"Error during Gemini call: {e}"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Generate sniper copy for a lead.")
|
||||
parser.add_argument("company_id", type=int, help="The Company Explorer ID of the lead.")
|
||||
parser.add_argument("--role", type=str, default="Wirtschaftl. Entscheider", help="The target persona/role.")
|
||||
args = parser.parse_args()
|
||||
|
||||
sniper = SniperGenerator()
|
||||
final_copy = sniper.generate_copy(args.company_id, args.role)
|
||||
|
||||
print("\n--- GENERATED SNIPER COPY ---")
|
||||
print(final_copy)
|
||||
print("-----------------------------\n")
|
||||
|
||||
114
scripts/post_daily_log_to_notion.py
Normal file
114
scripts/post_daily_log_to_notion.py
Normal file
@@ -0,0 +1,114 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
PROJECT_ID = "2ea88f42-8544-8074-9ad8-c24d283bc1c9"
|
||||
|
||||
def find_tasks_db():
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": "Tasks", "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def read_memory():
|
||||
try:
|
||||
with open("memory/2026-02-17.md", "r") as f:
|
||||
return f.readlines()
|
||||
except FileNotFoundError:
|
||||
return []
|
||||
|
||||
def parse_markdown_to_blocks(lines):
|
||||
blocks = []
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
|
||||
if line.startswith("# "):
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "heading_1",
|
||||
"heading_1": {"rich_text": [{"type": "text", "text": {"content": line[2:]}}]}
|
||||
})
|
||||
elif line.startswith("## "):
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "heading_2",
|
||||
"heading_2": {"rich_text": [{"type": "text", "text": {"content": line[3:]}}]}
|
||||
})
|
||||
elif line.startswith("### "):
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "heading_3",
|
||||
"heading_3": {"rich_text": [{"type": "text", "text": {"content": line[4:]}}]}
|
||||
})
|
||||
elif line.startswith("- "):
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "bulleted_list_item",
|
||||
"bulleted_list_item": {"rich_text": [{"type": "text", "text": {"content": line[2:]}}]}
|
||||
})
|
||||
else:
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "paragraph",
|
||||
"paragraph": {"rich_text": [{"type": "text", "text": {"content": line}}]}
|
||||
})
|
||||
return blocks
|
||||
|
||||
def create_log_entry():
|
||||
db_id = find_tasks_db()
|
||||
if not db_id:
|
||||
print("❌ Tasks DB not found via search.")
|
||||
return
|
||||
|
||||
lines = read_memory()
|
||||
children_blocks = parse_markdown_to_blocks(lines)
|
||||
|
||||
url = "https://api.notion.com/v1/pages"
|
||||
|
||||
# Try creating with "Name", if fails we might need to check schema, but usually it's Name or Task.
|
||||
# We'll stick to "Name" as it's most standard, but based on error before, maybe the DB was wrong.
|
||||
|
||||
payload = {
|
||||
"parent": {"database_id": db_id},
|
||||
"properties": {
|
||||
"Name": {"title": [{"text": {"content": "Tages-Log 17.02.2026"}}]},
|
||||
"Status": {"status": {"name": "Done"}},
|
||||
"Project": {"relation": [{"id": PROJECT_ID}]}
|
||||
},
|
||||
"children": children_blocks[:100]
|
||||
}
|
||||
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print("✅ Tages-Log in Notion erstellt.")
|
||||
else:
|
||||
# If Name fails, try Task
|
||||
if "Name is not a property" in resp.text:
|
||||
payload["properties"].pop("Name")
|
||||
payload["properties"]["Task"] = {"title": [{"text": {"content": "Tages-Log 17.02.2026"}}]}
|
||||
resp2 = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp2.status_code == 200:
|
||||
print("✅ Tages-Log in Notion erstellt (Property 'Task').")
|
||||
else:
|
||||
print(f"❌ Fehler (Retry): {resp2.text}")
|
||||
else:
|
||||
print(f"❌ Fehler: {resp.text}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
create_log_entry()
|
||||
91
scripts/post_retro_log.py
Normal file
91
scripts/post_retro_log.py
Normal file
@@ -0,0 +1,91 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
PROJECT_ID = "2ea88f42-8544-8074-9ad8-c24d283bc1c9"
|
||||
|
||||
def find_tasks_db():
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": "Tasks", "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def create_log_entry():
|
||||
db_id = find_tasks_db()
|
||||
if not db_id:
|
||||
print("❌ Tasks DB not found.")
|
||||
return
|
||||
|
||||
# Content for 16.02.
|
||||
content = """# Tages-Log: 16.02.2026 (Nachtrag)
|
||||
|
||||
## Zusammenfassung
|
||||
Durchbruch bei der technischen Integration zwischen SuperOffice CRM und Company Explorer. Der bidirektionale Datenaustausch steht.
|
||||
|
||||
## Erreichte Meilensteine
|
||||
|
||||
### 1. SuperOffice Integration (Deep Dive)
|
||||
- **Status:** ✅ **POC Erfolgreich.**
|
||||
- **Token-Management:** Automatische Refresh-Logik implementiert (kein manuelles Login mehr nötig).
|
||||
- **Write-Back:** Erfolgreiches Update von Firmen-Daten (Adresse, VAT, URL) in SuperOffice.
|
||||
- **Hürden genommen:**
|
||||
- **Pflichtfelder:** Fehler mit `Number2` (unbekanntes Pflichtfeld) identifiziert und umgangen.
|
||||
- **Listen-Objekte:** Korrekte Syntax für das Update von Dropdowns (Branche) gefunden (`Select` vs `Id`).
|
||||
|
||||
### 2. Company Explorer Connector
|
||||
- **Status:** ✅ **Client fertig.**
|
||||
- **Workflow:** Skript `company_explorer_connector.py` steuert jetzt den Upload von Firmen und das Abholen der Ergebnisse.
|
||||
|
||||
### 3. Regeln der Zusammenarbeit
|
||||
- **Core Directive V2.0:** Fokus auf "Ehrlicher Partner" und präzise technische Umsetzung ohne Floskeln definiert.
|
||||
|
||||
## Fazit
|
||||
Die "Rohre" zwischen den Systemen sind verlegt. Daten können fließen.
|
||||
"""
|
||||
|
||||
blocks = []
|
||||
for line in content.split('\n'):
|
||||
blocks.append({
|
||||
"object": "block",
|
||||
"type": "paragraph",
|
||||
"paragraph": {"rich_text": [{"type": "text", "text": {"content": line}}]}
|
||||
})
|
||||
|
||||
url = "https://api.notion.com/v1/pages"
|
||||
payload = {
|
||||
"parent": {"database_id": db_id},
|
||||
"properties": {
|
||||
"Name": {"title": [{"text": {"content": "Tages-Log 16.02.2026 (Nachtrag)"}}]},
|
||||
"Status": {"status": {"name": "Done"}},
|
||||
"Project": {"relation": [{"id": PROJECT_ID}]}
|
||||
},
|
||||
"children": blocks[:90]
|
||||
}
|
||||
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print("✅ Nachtrag 16.02. erstellt.")
|
||||
else:
|
||||
# Fallback Name/Task check
|
||||
if "Name is not a property" in resp.text:
|
||||
payload["properties"].pop("Name")
|
||||
payload["properties"]["Task"] = {"title": [{"text": {"content": "Tages-Log 16.02.2026 (Nachtrag)"}}]}
|
||||
requests.post(url, headers=HEADERS, json=payload)
|
||||
print("✅ Nachtrag 16.02. erstellt (Fallback).")
|
||||
|
||||
if __name__ == "__main__":
|
||||
create_log_entry()
|
||||
@@ -1,106 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
def find_db_by_name(query_name):
|
||||
token = os.getenv("NOTION_API_KEY")
|
||||
headers = {
|
||||
"Authorization": f"Bearer {token}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {
|
||||
"query": query_name,
|
||||
"filter": {"value": "database", "property": "object"}
|
||||
}
|
||||
|
||||
# print(f"Searching for '{query_name}' database...")
|
||||
resp = requests.post(url, headers=headers, json=payload)
|
||||
|
||||
if resp.status_code != 200:
|
||||
print(f"Error searching DB: {resp.text}")
|
||||
return None
|
||||
|
||||
results = resp.json().get("results", [])
|
||||
if not results:
|
||||
# print(f"No database named '{query_name}' found via search.")
|
||||
return None
|
||||
|
||||
db = results[0]
|
||||
return db['id']
|
||||
|
||||
def dump_db_content(db_id, db_name="DB"):
|
||||
token = os.getenv("NOTION_API_KEY")
|
||||
headers = {
|
||||
"Authorization": f"Bearer {token}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
# Get all pages
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
resp = requests.post(url, headers=headers, json={})
|
||||
|
||||
if resp.status_code != 200:
|
||||
print(f"Error querying DB: {resp.text}")
|
||||
return
|
||||
|
||||
pages = resp.json().get("results", [])
|
||||
print(f"\n--- Content of '{db_name}' ({len(pages)} rows) ---")
|
||||
|
||||
rows = []
|
||||
for page in pages:
|
||||
props = page['properties']
|
||||
|
||||
# Extract Name (Title) - Robust Logic
|
||||
name = "N/A"
|
||||
if "Vertical" in props and props["Vertical"]["title"]:
|
||||
name = props["Vertical"]["title"][0]["plain_text"]
|
||||
elif "Name" in props and props["Name"]["title"]:
|
||||
name = props["Name"]["title"][0]["plain_text"]
|
||||
elif "Role" in props and props["Role"]["title"]:
|
||||
name = props["Role"]["title"][0]["plain_text"]
|
||||
|
||||
# Extract Status/Freigabe
|
||||
freigabe = ""
|
||||
if "Freigabe" in props:
|
||||
if props["Freigabe"]["type"] == "status":
|
||||
freigabe = props["Freigabe"]["status"]["name"] if props["Freigabe"]["status"] else ""
|
||||
elif props["Freigabe"]["type"] == "select":
|
||||
freigabe = props["Freigabe"]["select"]["name"] if props["Freigabe"]["select"] else ""
|
||||
|
||||
# Extract Notes
|
||||
notes = ""
|
||||
if "Notes" in props and props["Notes"]["rich_text"]:
|
||||
notes = props["Notes"]["rich_text"][0]["plain_text"]
|
||||
|
||||
# Extract KPIs
|
||||
kpis = ""
|
||||
for kpi_key in ["KPIs", "KPI", "Quantitative Value"]:
|
||||
if kpi_key in props and props[kpi_key]["rich_text"]:
|
||||
kpis = props[kpi_key]["rich_text"][0]["plain_text"]
|
||||
break
|
||||
|
||||
rows.append({"name": name, "freigabe": freigabe, "notes": notes, "kpis": kpis})
|
||||
|
||||
# Print clean table
|
||||
print(f"{'Name':<40} | {'Freigabe':<15} | {'KPIs':<20} | {'Notes'}")
|
||||
print("-" * 120)
|
||||
for r in rows:
|
||||
# Nur Zeilen mit Inhalt anzeigen (Filter empty names)
|
||||
if r['name'] != "N/A":
|
||||
print(f"{r['name']:<40} | {r['freigabe']:<15} | {r['kpis']:<20} | {r['notes']}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
db_id_ind = find_db_by_name("Industries")
|
||||
if db_id_ind:
|
||||
dump_db_content(db_id_ind, "Industries")
|
||||
|
||||
db_id_roles = find_db_by_name("Personas")
|
||||
if db_id_roles:
|
||||
dump_db_content(db_id_roles, "Personas")
|
||||
@@ -1,130 +0,0 @@
|
||||
import requests
|
||||
import os
|
||||
import sqlite3
|
||||
import json
|
||||
|
||||
# --- Configuration ---
|
||||
BASE_URL = "http://192.168.178.6:8090/ce/api"
|
||||
API_USER = os.getenv("COMPANY_EXPLORER_API_USER", "admin")
|
||||
API_PASSWORD = os.getenv("COMPANY_EXPLORER_API_PASSWORD", "gemini")
|
||||
DB_PATH = "/home/node/clawd/repos/brancheneinstufung2/company_explorer_local.db"
|
||||
|
||||
def fetch_all_companies_from_api():
|
||||
"""Fetches all companies from the Company Explorer API."""
|
||||
print("Fetching all companies from Company Explorer API...")
|
||||
url = f"{BASE_URL}/companies"
|
||||
all_companies = []
|
||||
page = 1
|
||||
|
||||
while True:
|
||||
try:
|
||||
params = {'page': page, 'per_page': 50}
|
||||
response = requests.get(
|
||||
url,
|
||||
auth=(API_USER, API_PASSWORD),
|
||||
params=params,
|
||||
timeout=20
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
companies_on_page = data.get("items", [])
|
||||
if not companies_on_page:
|
||||
break
|
||||
|
||||
all_companies.extend(companies_on_page)
|
||||
print(f"Fetched page {page} with {len(companies_on_page)} companies.")
|
||||
|
||||
if len(all_companies) >= data.get("total", 0):
|
||||
break
|
||||
|
||||
page += 1
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"Error fetching companies from API: {e}")
|
||||
return None
|
||||
|
||||
print(f"Total companies fetched: {len(all_companies)}")
|
||||
return all_companies
|
||||
|
||||
def setup_database():
|
||||
"""Creates the SQLite database and the companies table."""
|
||||
print(f"Setting up database at: {DB_PATH}")
|
||||
if os.path.exists(DB_PATH):
|
||||
os.remove(DB_PATH)
|
||||
print("Removed existing database file.")
|
||||
|
||||
conn = sqlite3.connect(DB_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Define a flexible schema to hold the key fields
|
||||
cursor.execute("""
|
||||
CREATE TABLE companies (
|
||||
id INTEGER PRIMARY KEY,
|
||||
name TEXT,
|
||||
industry_ai TEXT,
|
||||
status TEXT,
|
||||
city TEXT,
|
||||
country TEXT,
|
||||
website TEXT,
|
||||
calculated_metric_name TEXT,
|
||||
calculated_metric_value TEXT,
|
||||
calculated_metric_unit TEXT,
|
||||
full_json TEXT
|
||||
)
|
||||
""")
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print("Database and table 'companies' created successfully.")
|
||||
|
||||
def populate_database(companies):
|
||||
"""Populates the database with company data."""
|
||||
if not companies:
|
||||
print("No companies to populate.")
|
||||
return
|
||||
|
||||
print("Populating database...")
|
||||
conn = sqlite3.connect(DB_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
for company in companies:
|
||||
# Extract metrics safely
|
||||
metrics = company.get('calculated_metrics', [])
|
||||
metric_name = metrics[0].get('name') if metrics else None
|
||||
metric_value = metrics[0].get('value') if metrics else None
|
||||
metric_unit = metrics[0].get('unit') if metrics else None
|
||||
|
||||
cursor.execute("""
|
||||
INSERT INTO companies (
|
||||
id, name, industry_ai, status, city, country, website,
|
||||
calculated_metric_name, calculated_metric_value, calculated_metric_unit,
|
||||
full_json
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
""", (
|
||||
company.get('id'),
|
||||
company.get('name'),
|
||||
company.get('industry_ai'),
|
||||
company.get('status'),
|
||||
company.get('city'),
|
||||
company.get('country'),
|
||||
company.get('website'),
|
||||
metric_name,
|
||||
metric_value,
|
||||
metric_unit,
|
||||
json.dumps(company) # Store the full object for future flexibility
|
||||
))
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print(f"Successfully inserted {len(companies)} records into the database.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
all_companies = fetch_all_companies_from_api()
|
||||
if all_companies is not None:
|
||||
setup_database()
|
||||
populate_database(all_companies)
|
||||
print("\nSync process finished successfully.")
|
||||
print(f"Database is ready at: {DB_PATH}")
|
||||
else:
|
||||
print("\nSync process failed due to API errors.")
|
||||
@@ -1,25 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
def test_prod_key():
|
||||
key = os.getenv("GEMINI_API_KEY_PROD")
|
||||
if not key:
|
||||
print("❌ GEMINI_API_KEY_PROD not found in .env")
|
||||
return
|
||||
|
||||
print(f"🔑 Testing Key: {key[:5]}...{key[-3:]}")
|
||||
|
||||
url = f"https://generativelanguage.googleapis.com/v1beta/models?key={key}"
|
||||
resp = requests.get(url)
|
||||
|
||||
if resp.status_code == 200:
|
||||
print("✅ API Call Successful! Key is active.")
|
||||
# print(f"Available Models: {[m['name'] for m in resp.json().get('models', [])][:3]}")
|
||||
else:
|
||||
print(f"❌ API Error: {resp.status_code} - {resp.text}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_prod_key()
|
||||
@@ -1,200 +0,0 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
def find_db_id(query_name):
|
||||
url = "https://api.notion.com/v1/search"
|
||||
payload = {"query": query_name, "filter": {"value": "database", "property": "object"}}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0]['id']
|
||||
return None
|
||||
|
||||
def get_page_id(db_id, title_col, title_val):
|
||||
url = f"https://api.notion.com/v1/databases/{db_id}/query"
|
||||
payload = {
|
||||
"filter": {
|
||||
"property": title_col,
|
||||
"title": {"equals": title_val}
|
||||
}
|
||||
}
|
||||
resp = requests.post(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
results = resp.json().get("results", [])
|
||||
if results:
|
||||
return results[0] # Return full page obj to access props
|
||||
return None
|
||||
|
||||
def update_page(page_id, properties):
|
||||
url = f"https://api.notion.com/v1/pages/{page_id}"
|
||||
payload = {"properties": properties}
|
||||
resp = requests.patch(url, headers=HEADERS, json=payload)
|
||||
if resp.status_code == 200:
|
||||
print(f"✅ Updated page {page_id}")
|
||||
else:
|
||||
print(f"❌ Error updating {page_id}: {resp.text}")
|
||||
|
||||
def append_text(current_text, new_text):
|
||||
if not current_text:
|
||||
return new_text
|
||||
if new_text in current_text:
|
||||
return current_text # Avoid duplicates
|
||||
return f"{current_text}\n\n[Auto-Update]: {new_text}"
|
||||
|
||||
# --- DATA TO UPDATE ---
|
||||
|
||||
# 1. Personas (KPIs)
|
||||
PERSONA_UPDATES = {
|
||||
"Wirtschaftlicher Entscheider": "10-25% Reduktion Personalkosten\n15-30% höhere Gästezufriedenheit (Hypothese)",
|
||||
"Operativer Entscheider": "20-40% Entlastung bei Routineaufgaben\n100% Abdeckung Reinigungszyklen",
|
||||
"Infrastruktur-Verantwortlicher": "20-30% schnellere Integration\n80-90% weniger Ausfallzeiten",
|
||||
"Innovations-Treiber": "10-20% höhere Servicekapazität\nSteigerung Upselling 5-10%"
|
||||
}
|
||||
|
||||
# 2. Industries (Pains/Gains/Status/Notes)
|
||||
INDUSTRY_UPDATES = {
|
||||
"Healthcare - Hospital": {
|
||||
"pains_add": "Mangelnde Hygiene-Standards durch Personalengpässe (Infektionsrisiko). Hoher Dokumentationsaufwand für Audits.",
|
||||
"gains_add": "Konstante, audit-sichere Sauberkeit (24/7). Entlastung des Reinigungspersonals.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Reinigung (Alex Veto). Service ist 'nice to have'. KPI: Hygiene-Sicherheit.",
|
||||
"ops_focus": True # Checkbox
|
||||
},
|
||||
"Healthcare - Care Home": {
|
||||
"pains_add": "Mangelnde Hygiene-Standards. Steigende Personalkosten bei begrenzten Pflegesätzen.",
|
||||
"gains_add": "Sichtbare Hygiene schafft Vertrauen. Entlastung Housekeeping.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Reinigung. Prio 2: Service (Essen). Fokus auf Fachkräftemangel.",
|
||||
"ops_focus": True
|
||||
},
|
||||
"Hospitality - Gastronomy": {
|
||||
"pains_add": "Lobby-Optik leidet bei Personalmangel.",
|
||||
"gains_add": "Makellose Optik für den ersten Eindruck.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Reinigung (Nachts). Service nur in Entertainment-Gastro.",
|
||||
"ops_focus": False
|
||||
},
|
||||
"Leisure - Entertainment": {
|
||||
"pains_add": "Service-Personal fehlt für Umsatz (Getränke).",
|
||||
"gains_add": "Mehr Umsatz durch konstante Verfügbarkeit.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Service Robotik (BellaBot).",
|
||||
"ops_focus": False
|
||||
},
|
||||
"Industry - Manufacturing": {
|
||||
"pains_add": "Staubbelastung gefährdet Sensoren/Qualität. Sicherheitsrisiko auf Fahrwegen.",
|
||||
"gains_add": "Staubfreie Umgebung ohne Produktionsstopp.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Reinigung (Sweeper). Kein Stapler-Kampf!",
|
||||
"ops_focus": True
|
||||
},
|
||||
"Logistics - Warehouse": {
|
||||
"pains_add": "Staub auf Waren. Manuelles Kehren bindet Fachkräfte.",
|
||||
"gains_add": "Werterhalt Hallenboden. Sauberkeit ohne Störung.",
|
||||
"status": "Freigegeben",
|
||||
"note_add": "Prio 1: Sweeper (Staub). Prio 2: Wet.",
|
||||
"ops_focus": True
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
def run_updates():
|
||||
print("--- Starting Notion Updates ---")
|
||||
|
||||
# 1. Update Personas
|
||||
db_personas = find_db_id("Personas")
|
||||
if db_personas:
|
||||
print(f"Found Personas DB: {db_personas}")
|
||||
for role, kpi_text in PERSONA_UPDATES.items():
|
||||
page = get_page_id(db_personas, "Role", role) # Title col is "Role" here? Or "Name"? Script 1 said Role fallback.
|
||||
# Actually, let's try "Name" first, then "Role".
|
||||
# In previous dump, 'Name' was 'Infrastruktur-Verantwortlicher' etc.
|
||||
# Let's assume the main column is "Name" (title).
|
||||
if not page:
|
||||
# Try finding by property "Role" (select) if title is different?
|
||||
# Based on dump, the Title column content was "Infrastruktur-Verantwortlicher".
|
||||
# Let's assume title property is named "Name" or "Role".
|
||||
# Inspecting schema from previous run: `['Rollenbeschreibung', '...Product Categories', ... 'Role']`
|
||||
# The Title property is likely "Role" or "Name".
|
||||
# Let's try searching for "Role" property as title.
|
||||
page = get_page_id(db_personas, "Role", role)
|
||||
|
||||
if page:
|
||||
# Update KPIs
|
||||
# Column name in schema: "KPIs"
|
||||
update_page(page['id'], {
|
||||
"KPIs": {"rich_text": [{"text": {"content": kpi_text}}]}
|
||||
})
|
||||
else:
|
||||
print(f"⚠️ Persona '{role}' not found.")
|
||||
else:
|
||||
print("❌ Personas DB not found.")
|
||||
|
||||
# 2. Update Industries
|
||||
db_ind = find_db_id("Industries")
|
||||
if db_ind:
|
||||
print(f"Found Industries DB: {db_ind}")
|
||||
for vertical, data in INDUSTRY_UPDATES.items():
|
||||
page = get_page_id(db_ind, "Vertical", vertical)
|
||||
if page:
|
||||
props = page['properties']
|
||||
|
||||
# Prepare updates
|
||||
new_props = {}
|
||||
|
||||
# Status
|
||||
# Check if Status is select or status
|
||||
if "Freigabe" in props:
|
||||
# Assuming Select or Status. Let's try Select first, if fails try Status
|
||||
if props["Freigabe"]["type"] == "select":
|
||||
new_props["Freigabe"] = {"select": {"name": data["status"]}}
|
||||
elif props["Freigabe"]["type"] == "status":
|
||||
new_props["Freigabe"] = {"status": {"name": data["status"]}}
|
||||
|
||||
# Ops Focus (Checkbox)
|
||||
if "Ops Focus: Secondary" in props:
|
||||
new_props["Ops Focus: Secondary"] = {"checkbox": data["ops_focus"]}
|
||||
|
||||
# Pains (Append)
|
||||
current_pains = ""
|
||||
if "Pains" in props and props["Pains"]["rich_text"]:
|
||||
current_pains = props["Pains"]["rich_text"][0]["plain_text"]
|
||||
new_pains = append_text(current_pains, data["pains_add"])
|
||||
new_props["Pains"] = {"rich_text": [{"text": {"content": new_pains}}]}
|
||||
|
||||
# Gains (Append)
|
||||
current_gains = ""
|
||||
if "Gains" in props and props["Gains"]["rich_text"]:
|
||||
current_gains = props["Gains"]["rich_text"][0]["plain_text"]
|
||||
new_gains = append_text(current_gains, data["gains_add"])
|
||||
new_props["Gains"] = {"rich_text": [{"text": {"content": new_gains}}]}
|
||||
|
||||
# Notes (Append)
|
||||
current_notes = ""
|
||||
if "Notes" in props and props["Notes"]["rich_text"]:
|
||||
current_notes = props["Notes"]["rich_text"][0]["plain_text"]
|
||||
new_notes = append_text(current_notes, data["note_add"])
|
||||
new_props["Notes"] = {"rich_text": [{"text": {"content": new_notes}}]}
|
||||
|
||||
# Execute Update
|
||||
update_page(page['id'], new_props)
|
||||
|
||||
else:
|
||||
print(f"⚠️ Industry '{vertical}' not found.")
|
||||
else:
|
||||
print("❌ Industries DB not found.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_updates()
|
||||
70
scripts/update_notion_tasks_status.py
Normal file
70
scripts/update_notion_tasks_status.py
Normal file
@@ -0,0 +1,70 @@
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(dotenv_path="/home/node/clawd/.env")
|
||||
|
||||
NOTION_TOKEN = os.getenv("NOTION_API_KEY")
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {NOTION_TOKEN}",
|
||||
"Content-Type": "application/json",
|
||||
"Notion-Version": "2022-06-28"
|
||||
}
|
||||
|
||||
# IDs from previous fetch
|
||||
TASKS = {
|
||||
"Setup GCP": "2ea88f42-8544-8073-b287-eb83ce581c0b",
|
||||
"SO API POC": "2ff88f42-8544-8093-a301-fc27b3886aa1",
|
||||
"Pains Gains Vertical": "2ff88f42-8544-8050-8245-c3bb852058f4",
|
||||
"Segmentierung Bestand": "2ff88f42-8544-808f-862b-c30ab2f29783",
|
||||
"Matrixmultiplikation": "2ff88f42-8544-8079-a23e-c248e35b09a0"
|
||||
}
|
||||
|
||||
TASKS_DB_ID = "30588f42-8544-80c3-8919-e22d74d945ea" # From discovery
|
||||
PROJECT_ID = "2ea88f42-8544-8074-9ad8-c24d283bc1c9"
|
||||
|
||||
def update_status(page_id, status):
|
||||
url = f"https://api.notion.com/v1/pages/{page_id}"
|
||||
payload = {"properties": {"Status": {"status": {"name": status}}}}
|
||||
requests.patch(url, headers=HEADERS, json=payload)
|
||||
print(f"Updated Status {page_id} -> {status}")
|
||||
|
||||
def add_comment(page_id, text):
|
||||
url = "https://api.notion.com/v1/comments"
|
||||
payload = {
|
||||
"parent": {"page_id": page_id},
|
||||
"rich_text": [{"text": {"content": text}}]
|
||||
}
|
||||
requests.post(url, headers=HEADERS, json=payload)
|
||||
print(f"Added comment to {page_id}")
|
||||
|
||||
def create_task(title):
|
||||
url = "https://api.notion.com/v1/pages"
|
||||
payload = {
|
||||
"parent": {"database_id": TASKS_DB_ID},
|
||||
"properties": {
|
||||
"Name": {"title": [{"text": {"content": title}}]},
|
||||
"Status": {"status": {"name": "To Do"}},
|
||||
"Project": {"relation": [{"id": PROJECT_ID}]}
|
||||
}
|
||||
}
|
||||
requests.post(url, headers=HEADERS, json=payload)
|
||||
print(f"Created Task: {title}")
|
||||
|
||||
def run():
|
||||
# 1. Done
|
||||
update_status(TASKS["Setup GCP"], "Done")
|
||||
update_status(TASKS["SO API POC"], "Done")
|
||||
|
||||
# 2. Progress Comments
|
||||
add_comment(TASKS["Pains Gains Vertical"], "✅ Entwurf in Notion finalisiert und detailliert (inkl. Hygiene-Fokus). Bereit für Review am Freitag.")
|
||||
add_comment(TASKS["Segmentierung Bestand"], "✅ Company Explorer Schema erweitert (V2). Bereit für Excel-Import.")
|
||||
add_comment(TASKS["Matrixmultiplikation"], "✅ Logik '3+1' (Prio Produkt + Sekundär bei Ops-Rolle) in Datenstruktur abgebildet.")
|
||||
|
||||
# 3. New Tasks
|
||||
create_task("Company Explorer: Daten-Sync & CRM-Import")
|
||||
create_task("SuperOffice: Definition & Anlage UDF-Felder (Intro-Text)")
|
||||
|
||||
if __name__ == "__main__":
|
||||
run()
|
||||
157
show_status.py
157
show_status.py
@@ -1,157 +0,0 @@
|
||||
import sqlite3
|
||||
import os
|
||||
import requests
|
||||
import json
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
# --- Configuration ---
|
||||
DB_PATH = "/home/node/clawd/repos/brancheneinstufung2/company_explorer_local.db"
|
||||
CE_API_URL = "http://192.168.178.6:8090/ce/api"
|
||||
# SO_API_URL = "..." # To be added
|
||||
|
||||
import sys
|
||||
sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), "connector-superoffice"))
|
||||
|
||||
from superoffice_client import SuperOfficeClient
|
||||
|
||||
class GtmHealthCheck:
|
||||
def __init__(self):
|
||||
self.db_path = DB_PATH
|
||||
self.ce_api_url = CE_API_URL
|
||||
self.api_user = os.getenv("COMPANY_EXPLORER_API_USER", "admin")
|
||||
self.api_password = os.getenv("COMPANY_EXPLORER_API_PASSWORD", "gemini")
|
||||
|
||||
def get_ce_stats(self):
|
||||
"""Holt Statistiken aus der lokalen Company Explorer DB."""
|
||||
if not os.path.exists(self.db_path):
|
||||
return {"total": 0, "in_progress": 0, "error": "DB file not found."}
|
||||
|
||||
try:
|
||||
conn = sqlite3.connect(self.db_path)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("SELECT COUNT(*) FROM companies")
|
||||
total = cursor.fetchone()[0]
|
||||
|
||||
cursor.execute("SELECT COUNT(*) FROM companies WHERE status != 'ENRICHED'")
|
||||
in_progress = cursor.fetchone()[0]
|
||||
|
||||
conn.close()
|
||||
return {"total": total, "in_progress": in_progress}
|
||||
except Exception as e:
|
||||
return {"total": 0, "in_progress": 0, "error": str(e)}
|
||||
|
||||
def check_ce_api_health(self):
|
||||
"""Prüft die Erreichbarkeit der Company Explorer API."""
|
||||
try:
|
||||
response = requests.get(
|
||||
f"{self.ce_api_url}/health",
|
||||
auth=(self.api_user, self.api_password),
|
||||
timeout=5
|
||||
)
|
||||
if response.status_code == 200 and response.json().get("status") == "ok":
|
||||
return "[HEALTHY]"
|
||||
return f"[ERROR - Status {response.status_code}]"
|
||||
except requests.exceptions.Timeout:
|
||||
return "[BUSY/TIMEOUT]"
|
||||
except requests.exceptions.RequestException:
|
||||
return "[UNREACHABLE]"
|
||||
|
||||
def get_so_stats(self):
|
||||
"""Holt die ungefähre Gesamtanzahl der Firmen aus der SuperOffice API."""
|
||||
try:
|
||||
client = SuperOfficeClient()
|
||||
# We query the first page with a page size of 200 (a common default)
|
||||
query_string = "Contact?$top=200"
|
||||
|
||||
# Directly use the requests logic from the client's search method for a single page
|
||||
url = f"{client.base_url}/{query_string}"
|
||||
response = requests.get(url, headers=client.headers, timeout=15)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
count_on_page = len(data.get('value', []))
|
||||
|
||||
# Check for a next link to determine if there are more pages
|
||||
if 'odata.nextLink' in data or 'next_page_url' in data:
|
||||
return {"total": f"> {count_on_page}"} # More than one page
|
||||
else:
|
||||
return {"total": str(count_on_page)} # Exact number if only one page
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
return {"total": f"API Error"}
|
||||
except Exception as e:
|
||||
return {"total": f"Error"}
|
||||
|
||||
def check_so_api_health(self):
|
||||
"""Prüft die Erreichbarkeit der SuperOffice API."""
|
||||
try:
|
||||
client = SuperOfficeClient()
|
||||
# A simple request to the base URL should suffice as a health check
|
||||
response = requests.get(client.base_url, headers=client.headers, timeout=10)
|
||||
if response.status_code == 200:
|
||||
return "[HEALTHY]"
|
||||
return f"[ERROR - Status {response.status_code}]"
|
||||
except requests.exceptions.Timeout:
|
||||
return "[BUSY/TIMEOUT]"
|
||||
except requests.exceptions.RequestException:
|
||||
return "[UNREACHABLE]"
|
||||
|
||||
def get_throughput(self):
|
||||
"""Zählt die verarbeiteten Accounts der letzten Stunde aus dem Log."""
|
||||
log_file = "/home/node/clawd/repos/brancheneinstufung2/logs/throughput.log"
|
||||
if not os.path.exists(log_file):
|
||||
return 0
|
||||
|
||||
count = 0
|
||||
one_hour_ago = datetime.utcnow() - timedelta(hours=1)
|
||||
|
||||
try:
|
||||
with open(log_file, "r") as f:
|
||||
for line in f:
|
||||
parts = line.strip().split(',')
|
||||
if len(parts) >= 1:
|
||||
try:
|
||||
timestamp = datetime.fromisoformat(parts[0])
|
||||
if timestamp >= one_hour_ago:
|
||||
count += 1
|
||||
except ValueError:
|
||||
continue # Ignore malformed lines
|
||||
return count
|
||||
except Exception:
|
||||
return "Log Error"
|
||||
|
||||
def render_dashboard(self):
|
||||
"""Stellt das Dashboard auf der Konsole dar."""
|
||||
ce_stats = self.get_ce_stats()
|
||||
ce_health = self.check_ce_api_health()
|
||||
so_stats = self.get_so_stats()
|
||||
so_health = self.check_so_api_health()
|
||||
throughput = self.get_throughput()
|
||||
|
||||
timestamp = datetime.now().strftime("%d.%m.%y %H:%M")
|
||||
|
||||
print("=======================================")
|
||||
print(f"GTM Lead Engine - Status ({timestamp})")
|
||||
print("=======================================")
|
||||
print("\n[+] Schnittstellen:")
|
||||
print(f" - SuperOffice API: {so_health}")
|
||||
print(f" - Company Explorer: {ce_health}")
|
||||
|
||||
print("\n[+] Account Trichter:")
|
||||
print(f" - SuperOffice Gesamt: {so_stats.get('total')}")
|
||||
|
||||
if 'error' in ce_stats:
|
||||
print(f" - Im Company Explorer: Error ({ce_stats['error']})")
|
||||
else:
|
||||
print(f" - Im Company Explorer: {ce_stats.get('total')}")
|
||||
print(f" - In Bearbeitung: {ce_stats.get('in_progress')}")
|
||||
|
||||
print("\n[+] Durchsatz (Letzte Stunde):")
|
||||
print(f" - Verarbeitet: {throughput} Accounts")
|
||||
print("\n")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
checker = GtmHealthCheck()
|
||||
checker.render_dashboard()
|
||||
@@ -99,6 +99,31 @@ async def upload_audio(
|
||||
|
||||
return meeting
|
||||
|
||||
@app.post("/api/meetings/{meeting_id}/retry")
|
||||
def retry_meeting(
|
||||
meeting_id: int,
|
||||
background_tasks: BackgroundTasks,
|
||||
db: Session = Depends(get_db)
|
||||
):
|
||||
meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first()
|
||||
if not meeting:
|
||||
raise HTTPException(404, detail="Meeting not found")
|
||||
|
||||
# Check if chunks directory exists
|
||||
chunk_dir = os.path.join(settings.UPLOAD_DIR, "chunks", str(meeting_id))
|
||||
if not os.path.exists(chunk_dir) or not os.listdir(chunk_dir):
|
||||
raise HTTPException(400, detail="Original audio chunks not found. Please re-upload.")
|
||||
|
||||
# Reset status
|
||||
meeting.status = "QUEUED"
|
||||
db.commit()
|
||||
|
||||
# Trigger Retry Task
|
||||
from .services.orchestrator import retry_meeting_task
|
||||
background_tasks.add_task(retry_meeting_task, meeting.id, SessionLocal)
|
||||
|
||||
return {"status": "started", "message": "Retrying transcription..."}
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
class InsightRequest(BaseModel):
|
||||
@@ -201,9 +226,16 @@ def delete_meeting(meeting_id: int, db: Session = Depends(get_db)):
|
||||
|
||||
# Serve Frontend
|
||||
# This must be the last route definition to avoid catching API routes
|
||||
static_path = "/frontend_static"
|
||||
|
||||
# PRIORITY 1: Mounted Volume (Development / Live Update)
|
||||
static_path = "/app/frontend/dist"
|
||||
|
||||
# PRIORITY 2: Built-in Image Path (Production)
|
||||
if not os.path.exists(static_path):
|
||||
static_path = "/frontend_static"
|
||||
|
||||
# PRIORITY 3: Local Development (running python directly)
|
||||
if not os.path.exists(static_path):
|
||||
# Fallback for local development if not in Docker
|
||||
static_path = os.path.join(os.path.dirname(__file__), "../frontend/dist")
|
||||
|
||||
if os.path.exists(static_path):
|
||||
|
||||
@@ -19,6 +19,16 @@ def parse_time_to_seconds(time_str):
|
||||
return 0
|
||||
return 0
|
||||
|
||||
def clean_json_string(text):
|
||||
text = text.strip()
|
||||
if text.startswith("```json"):
|
||||
text = text[7:]
|
||||
elif text.startswith("```"):
|
||||
text = text[3:]
|
||||
if text.endswith("```"):
|
||||
text = text[:-3]
|
||||
return text.strip()
|
||||
|
||||
def process_meeting_task(meeting_id: int, db_session_factory):
|
||||
db = db_session_factory()
|
||||
meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first()
|
||||
@@ -50,7 +60,13 @@ def process_meeting_task(meeting_id: int, db_session_factory):
|
||||
# Parse JSON and Adjust Timestamps
|
||||
json_data = []
|
||||
try:
|
||||
raw_json = json.loads(result["raw_text"])
|
||||
cleaned_text = clean_json_string(result["raw_text"])
|
||||
raw_json = json.loads(cleaned_text)
|
||||
|
||||
# Check for wrapped structure (e.g. {"items": [...]}) if schema enforced it
|
||||
if isinstance(raw_json, dict) and "items" in raw_json:
|
||||
raw_json = raw_json["items"] # Extract inner list
|
||||
|
||||
if isinstance(raw_json, list):
|
||||
for entry in raw_json:
|
||||
seconds = parse_time_to_seconds(entry.get("time", "00:00"))
|
||||
@@ -63,7 +79,7 @@ def process_meeting_task(meeting_id: int, db_session_factory):
|
||||
entry["display_time"] = f"{h:02}:{m:02}:{s:02}"
|
||||
json_data.append(entry)
|
||||
except Exception as e:
|
||||
logger.error(f"JSON Parsing failed for chunk {i}: {e}")
|
||||
logger.error(f"JSON Parsing failed for chunk {i}: {e}. Raw text start: {result['raw_text'][:100]}")
|
||||
|
||||
# Save chunk result
|
||||
db_chunk = TranscriptChunk(
|
||||
@@ -89,3 +105,94 @@ def process_meeting_task(meeting_id: int, db_session_factory):
|
||||
db.commit()
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
def retry_meeting_task(meeting_id: int, db_session_factory):
|
||||
"""
|
||||
Retries transcription using existing chunks on disk.
|
||||
Avoids re-splitting the original file.
|
||||
"""
|
||||
db = db_session_factory()
|
||||
meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first()
|
||||
if not meeting:
|
||||
return
|
||||
|
||||
try:
|
||||
import os
|
||||
transcriber = TranscriptionService()
|
||||
|
||||
# 0. Validate Chunk Directory
|
||||
chunk_dir = os.path.join(settings.UPLOAD_DIR, "chunks", str(meeting_id))
|
||||
if not os.path.exists(chunk_dir):
|
||||
logger.error(f"Chunk directory not found for meeting {meeting_id}")
|
||||
meeting.status = "ERROR"
|
||||
db.commit()
|
||||
return
|
||||
|
||||
chunks = sorted([os.path.join(chunk_dir, f) for f in os.listdir(chunk_dir) if f.endswith(".mp3")])
|
||||
if not chunks:
|
||||
logger.error(f"No chunks found for meeting {meeting_id}")
|
||||
meeting.status = "ERROR"
|
||||
db.commit()
|
||||
return
|
||||
|
||||
# Phase 1: Clear Old Chunks
|
||||
meeting.status = "RETRYING"
|
||||
db.query(TranscriptChunk).filter(TranscriptChunk.meeting_id == meeting_id).delete()
|
||||
db.commit()
|
||||
|
||||
# Phase 2: Transcribe
|
||||
all_text = []
|
||||
for i, chunk_path in enumerate(chunks):
|
||||
offset = i * settings.CHUNK_DURATION_SEC
|
||||
logger.info(f"Retrying chunk {i+1}/{len(chunks)} with offset {offset}s")
|
||||
|
||||
result = transcriber.transcribe_chunk(chunk_path, offset)
|
||||
|
||||
# Parse JSON and Adjust Timestamps (Same logic as process_meeting_task)
|
||||
json_data = []
|
||||
try:
|
||||
# With response_schema, raw_text SHOULD be valid JSON directly
|
||||
# But let's keep clean_json_string just in case specific models deviate
|
||||
cleaned_text = clean_json_string(result["raw_text"])
|
||||
raw_json = json.loads(cleaned_text)
|
||||
|
||||
# Check for wrapped structure (e.g. {"items": [...]}) if schema enforced it
|
||||
if isinstance(raw_json, dict) and "items" in raw_json:
|
||||
raw_json = raw_json["items"] # Extract inner list
|
||||
|
||||
if isinstance(raw_json, list):
|
||||
for entry in raw_json:
|
||||
seconds = parse_time_to_seconds(entry.get("time", "00:00"))
|
||||
absolute_seconds = seconds + offset
|
||||
entry["absolute_seconds"] = absolute_seconds
|
||||
|
||||
h = int(absolute_seconds // 3600)
|
||||
m = int((absolute_seconds % 3600) // 60)
|
||||
s = int(absolute_seconds % 60)
|
||||
entry["display_time"] = f"{h:02}:{m:02}:{s:02}"
|
||||
json_data.append(entry)
|
||||
except Exception as e:
|
||||
logger.error(f"JSON Parsing failed for chunk {i}: {e}. Raw: {result['raw_text'][:100]}")
|
||||
|
||||
# Save chunk result
|
||||
db_chunk = TranscriptChunk(
|
||||
meeting_id=meeting.id,
|
||||
chunk_index=i,
|
||||
raw_text=result["raw_text"],
|
||||
json_content=json_data
|
||||
)
|
||||
db.add(db_chunk)
|
||||
all_text.append(result["raw_text"])
|
||||
db.commit()
|
||||
|
||||
# Phase 3: Finalize
|
||||
meeting.status = "COMPLETED"
|
||||
db.commit()
|
||||
logger.info(f"Meeting {meeting.id} retry completed.")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error retrying meeting {meeting_id}: {e}", exc_info=True)
|
||||
meeting.status = "ERROR"
|
||||
db.commit()
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
@@ -30,20 +30,17 @@ class TranscriptionService:
|
||||
if media_file.state == "FAILED":
|
||||
raise Exception("File processing failed at Gemini.")
|
||||
|
||||
# 3. Transcribe with Diarization and Timestamps
|
||||
# 3. Transcribe with Diarization and Timestamps (Plain Text Mode for Stability)
|
||||
prompt = """
|
||||
Transkribiere dieses Audio wortgetreu.
|
||||
Identifiziere die Sprecher (Speaker A, Speaker B, etc.).
|
||||
|
||||
Gib das Ergebnis als JSON-Liste zurück.
|
||||
Format:
|
||||
[
|
||||
{
|
||||
"time": "MM:SS",
|
||||
"speaker": "Speaker A",
|
||||
"text": "..."
|
||||
}
|
||||
]
|
||||
Gib das Ergebnis EXAKT in diesem Format zurück (pro Zeile ein Sprecherwechsel):
|
||||
[MM:SS] Speaker Name: Gesprochener Text...
|
||||
|
||||
Beispiel:
|
||||
[00:00] Speaker A: Hallo zusammen.
|
||||
[00:05] Speaker B: Guten Morgen.
|
||||
"""
|
||||
|
||||
logger.info(f"Generating transcription for {file_path}...")
|
||||
@@ -52,14 +49,46 @@ class TranscriptionService:
|
||||
contents=[media_file, prompt],
|
||||
config=types.GenerateContentConfig(
|
||||
temperature=0.1,
|
||||
response_mime_type="application/json"
|
||||
max_output_tokens=8192
|
||||
)
|
||||
)
|
||||
|
||||
# Cleanup: Delete file from Gemini storage
|
||||
self.client.files.delete(name=media_file.name)
|
||||
|
||||
# Parse Plain Text to JSON
|
||||
structured_data = self.parse_transcript(response.text)
|
||||
import json
|
||||
return {
|
||||
"raw_text": response.text, # This is now a JSON string
|
||||
"raw_text": json.dumps(structured_data), # Return valid JSON string
|
||||
"offset": offset_seconds
|
||||
}
|
||||
|
||||
def parse_transcript(self, text: str) -> list:
|
||||
"""
|
||||
Parses lines like '[00:12] Speaker A: Hello world' into structured JSON.
|
||||
"""
|
||||
import re
|
||||
results = []
|
||||
# Regex to match: [MM:SS] Speaker: Text
|
||||
# Flexible for MM:SS or H:MM:SS
|
||||
pattern = re.compile(r"^\[(\d{1,2}:\d{2}(?::\d{2})?)\]\s*([^:]+):\s*(.+)$")
|
||||
|
||||
for line in text.strip().split('\n'):
|
||||
line = line.strip()
|
||||
if not line: continue
|
||||
|
||||
match = pattern.match(line)
|
||||
if match:
|
||||
time_str, speaker, content = match.groups()
|
||||
results.append({
|
||||
"time": time_str,
|
||||
"speaker": speaker.strip(),
|
||||
"text": content.strip()
|
||||
})
|
||||
else:
|
||||
# Fallback: Append to previous if it looks like continuation
|
||||
if results and not line.startswith("["):
|
||||
results[-1]["text"] += " " + line
|
||||
|
||||
return results
|
||||
|
||||
@@ -394,6 +394,20 @@ export default function App() {
|
||||
>
|
||||
<Share2 className="h-5 w-5" />
|
||||
</button>
|
||||
<button
|
||||
onClick={async () => {
|
||||
if(!confirm("Retry transcription using existing audio chunks? This will overwrite the current transcript.")) return;
|
||||
try {
|
||||
await axios.post(`${API_BASE}/meetings/${detailMeeting.id}/retry`);
|
||||
alert("Retry started. Please wait for completion.");
|
||||
fetchDetail(detailMeeting.id);
|
||||
} catch(e) { alert("Retry failed."); }
|
||||
}}
|
||||
className="text-orange-500 hover:bg-orange-50 dark:hover:bg-orange-900/20 p-2 rounded"
|
||||
title="Retry Transcription (Fix Format Issues)"
|
||||
>
|
||||
<Wand2 className="h-5 w-5" />
|
||||
</button>
|
||||
<button onClick={(e) => handleDeleteMeeting(e, detailMeeting.id)} className="text-red-500 hover:bg-red-50 dark:hover:bg-red-900/20 p-2 rounded"><Trash2 className="h-5 w-5" /></button>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
Reference in New Issue
Block a user