olsch01
5319bcd30b
- Created chatwoot-agent-bot/ with Node.js webhook server - Bot detects intent (greeting, billing, technical, features, account) - Auto-responds from FAQ knowledge base or escalates to human - FAQ-KB.md: Living knowledge base that grows with customer questions - CHATWOOT-SETUP.md: Complete deployment and configuration guide - Supports Telegram notifications on escalation - Bot runs on port 3001, ready for Chatwoot webhook integration
305 lines
9.9 KiB
Python
305 lines
9.9 KiB
Python
#!/usr/bin/env python3
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"""
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Tier 1 Lead Scorer - Progressive Filtering
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- Runs parallel to JAE v5
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- Scores leads as they're processed
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- Maintains dynamic top 50 list
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- Updates in real-time
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"""
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import json, re, time
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from datetime import datetime
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from pathlib import Path
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SCRIPT_DIR = Path(__file__).parent
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STATE_FILE = SCRIPT_DIR / "state" / "tier1-state.json"
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SCORED_FILE = SCRIPT_DIR / "state" / "tier1-scored-leads.json"
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CRM_URL = "https://salesforce.hoaledgeriq.com/rest"
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CRM_TOKEN = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiI5M2FmNGFmNS0zZWQ0LTQ1ZDMtOWE5Zi01MDMzZjc3YTY3MjMiLCJ0eXBlIjoiQVBJX0tFWSIsIndvcmtzcGFjZUlkIjoiOTNhZjRhZjUtM2VkNC00NWQzLTlhOWYtNTAzM2Y3N2E2NzIzIiwiaWF0IjoxNzczMzI4NDQzLCJleHAiOjE4MDQ3ODE2NDIsImp0aSI6IjIwZjEyYzkwLTRkMDctNGJmNi1iMzk3LTZjNmU3MzlmMThjOCJ9.zeM5NvwCSGEcz99m2LYtgb0sVD6WUXcCF7SwonFg930"
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def log(msg):
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ts = datetime.now().strftime('%H:%M:%S')
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print(f"[{ts}] {msg}")
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def load_state():
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if STATE_FILE.exists():
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return json.loads(STATE_FILE.read_text())
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return {"last_processed": 0, "tier1_leads": [], "scoring_rules": {
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"unit_range_ideal": [150, 400],
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"unit_range_acceptable": [100, 500],
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"require_budget_pdf": False,
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"min_score": 6
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}}
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def save_state(s):
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STATE_FILE.write_text(json.dumps(s, indent=2))
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def extract_units_from_note(note):
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"""Extract unit count from note body or title"""
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body = note.get('bodyV2', {}).get('markdown', '') if isinstance(note.get('bodyV2'), dict) else ''
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title = note.get('title', '')
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text = f"{title} {body}".lower()
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# Look for unit patterns
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patterns = [
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r'(\d{1,4})\s*(?:homes|units|lots|properties|residences)',
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r'(\d{1,4})\s*-?\s*(?:home|unit|lot|property|residence)\s*(?:community|association|complex)',
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r'community\s*of\s*(\d{1,4})',
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r'units:\s*(\d{1,4})',
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]
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for pattern in patterns:
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match = re.search(pattern, text, re.IGNORECASE)
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if match:
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try:
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units = int(match.group(1))
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if 10 <= units <= 5000: # Reasonable range
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return units
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except:
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pass
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return None
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def has_budget_pdf(note):
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"""Check if note has budget PDF"""
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body = note.get('bodyV2', {}).get('markdown', '') if isinstance(note.get('bodyV2'), dict) else ''
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title = note.get('title', '')
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text = f"{title} {body}".lower()
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# Check for budget PDF mentions
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if 'budget pdf' in text or 'budget.pdf' in text or 'found budget pdf' in text:
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return True
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if 'budget found' in text and 'pdf' in text:
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return True
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return False
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def has_website(note):
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"""Check if note has website"""
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body = note.get('bodyV2', {}).get('markdown', '') if isinstance(note.get('bodyV2'), dict) else ''
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title = note.get('title', '')
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text = f"{title} {body}"
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return 'https://' in text or 'http://' in text
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def get_temp(note):
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"""Get temperature from note"""
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temp = note.get('temp', 'COLD')
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if temp and temp.upper() in ['HOT', 'WARM', 'COLD']:
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return temp.upper()
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title = note.get('title', '').upper()
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if title.startswith('HOT:'):
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return 'HOT'
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if title.startswith('WARM:'):
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return 'WARM'
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return 'COLD'
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def score_lead(note):
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"""
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Score a lead 1-10 based on Tier 1 criteria
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Returns: (score, breakdown)
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"""
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temp = get_temp(note)
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units = extract_units_from_note(note)
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budget_pdf = has_budget_pdf(note)
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has_site = has_website(note)
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score = 0
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breakdown = []
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# 1. Temperature (max 3 points)
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if temp == 'HOT':
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score += 3
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breakdown.append("Temp: HOT (+3)")
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elif temp == 'WARM':
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score += 2
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breakdown.append("Temp: WARM (+2)")
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else:
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breakdown.append("Temp: COLD (+0)")
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# 2. Unit Count (max 4 points)
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if units:
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if 150 <= units <= 400:
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score += 4
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breakdown.append(f"Units: {units} (ideal range +4)")
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elif 100 <= units < 150 or 400 < units <= 500:
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score += 3
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breakdown.append(f"Units: {units} (good range +3)")
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elif 50 <= units < 100 or 500 < units <= 1000:
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score += 2
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breakdown.append(f"Units: {units} (acceptable +2)")
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else:
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score += 1
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breakdown.append(f"Units: {units} (outside ideal +1)")
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else:
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breakdown.append("Units: Unknown (0)")
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# 3. Budget PDF (max 2 points)
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if budget_pdf:
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score += 2
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breakdown.append("Budget PDF: Found (+2)")
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elif has_site:
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score += 1
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breakdown.append("Budget: Mentioned (+1)")
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else:
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breakdown.append("Budget: Not found (0)")
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# 4. Website Quality (max 1 point)
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if has_site:
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score += 1
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breakdown.append("Website: Yes (+1)")
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return score, breakdown
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def fetch_recent_notes(limit=200):
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"""Fetch recent notes from CRM"""
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import urllib.request, ssl, json
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ssl_context = ssl.create_default_context()
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ssl_context.check_hostname = False
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ssl_context.verify_mode = ssl.CERT_NONE
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try:
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req = urllib.request.Request(
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f"{CRM_URL}/notes?limit={limit}&order[createdAt]=desc",
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headers={"Authorization": f"Bearer {CRM_TOKEN}", "Accept": "application/json"}
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)
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opener = urllib.request.build_opener(urllib.request.HTTPSHandler(context=ssl_context))
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with opener.open(req, timeout=30) as r:
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data = json.loads(r.read().decode())
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return data.get('data', {}).get('notes', [])
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except Exception as e:
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log(f"Fetch error: {e}")
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return []
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def update_crm_note(note_id, score, tier1_label):
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"""Update CRM note with tier1_score field"""
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import urllib.request, ssl, json
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ssl_context = ssl.create_default_context()
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ssl_context.check_hostname = False
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ssl_context.verify_mode = ssl.CERT_NONE
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try:
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# Patch the note to add tier1_score
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patch_data = json.dumps({
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"tier1Score": score,
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"tier1Label": tier1_label
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}).encode()
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req = urllib.request.Request(
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f"{CRM_URL}/notes/{note_id}",
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data=patch_data,
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headers={
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"Authorization": f"Bearer {CRM_TOKEN}",
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"Content-Type": "application/json"
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},
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method='PATCH'
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)
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opener = urllib.request.build_opener(urllib.request.HTTPSHandler(context=ssl_context))
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with opener.open(req, timeout=20) as r:
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return True
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except Exception as e:
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log(f" ⚠️ CRM update failed: {e}")
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return False
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def main():
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log("=" * 60)
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log("Tier 1 Scorer - Starting")
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log("=" * 60)
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state = load_state()
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scored_leads = state.get('tier1_leads', [])
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last_processed = state.get('last_processed', 0)
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log(f"Loading {len(scored_leads)} previously scored leads")
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# Fetch recent notes
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notes = fetch_recent_notes(500)
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log(f"Fetched {len(notes)} recent notes")
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new_additions = 0
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updated_additions = 0
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crm_updates = 0
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for i, note in enumerate(notes):
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note_id = note.get('id')
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title = note.get('title', '')[:50]
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# Score the lead
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score, breakdown = score_lead(note)
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# Determine Tier 1 label
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if score >= 8:
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tier1_label = "Tier 1 - Priority"
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elif score >= 6:
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tier1_label = "Tier 1"
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else:
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tier1_label = ""
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# Check if already in scored list
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existing = next((x for x in scored_leads if x['id'] == note_id), None)
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if score >= 6: # Minimum threshold for Tier 1 consideration
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lead_data = {
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'id': note_id,
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'title': title,
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'score': score,
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'breakdown': breakdown,
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'temp': get_temp(note),
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'units': extract_units_from_note(note),
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'budget_pdf': has_budget_pdf(note),
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'updated': datetime.now().isoformat()
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}
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if existing:
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# Update existing
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if existing['score'] != score:
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existing.update(lead_data)
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updated_additions += 1
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# Update CRM
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if update_crm_note(note_id, score, tier1_label):
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crm_updates += 1
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log(f" ✓ Updated CRM: {title[:40]} (Score: {score}/10)")
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else:
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# Add new
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scored_leads.append(lead_data)
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new_additions += 1
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# Update CRM
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if update_crm_note(note_id, score, tier1_label):
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crm_updates += 1
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log(f" ✓ Updated CRM: {title[:40]} (Score: {score}/10)")
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# Sort by score (descending)
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scored_leads.sort(key=lambda x: x['score'], reverse=True)
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# Keep only top 100 for now
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scored_leads = scored_leads[:100]
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# Save state
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state['tier1_leads'] = scored_leads
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state['last_processed'] = len(notes)
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save_state(state)
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log(f"\n=== Tier 1 Results ===")
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log(f"Total scored: {len(scored_leads)}")
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log(f"New additions: {new_additions}")
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log(f"Updates: {updated_additions}")
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log(f"CRM updates: {crm_updates}")
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if scored_leads:
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log(f"\nTop 10 Tier 1 Leads:")
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for i, lead in enumerate(scored_leads[:10], 1):
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units_str = f"{lead['units']} units" if lead['units'] else "units: ?"
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log(f" {i}. [{lead['score']}/10] {lead['title'][:40]} ({lead['temp']}, {units_str})")
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log("\n" + "=" * 60)
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log(f"Tier 1 scoring complete. Top lead score: {scored_leads[0]['score'] if scored_leads else 0}/10")
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log("=" * 60)
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log(f"\n📊 CRM Integration:")
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log(f" • Field: tier1_score (numeric)")
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log(f" • Label: tier1_label (text)")
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log(f" • Filter view: tier1_score >= 6")
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log("=" * 60)
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if __name__ == "__main__":
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main()
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