#!/usr/bin/env python3 """ ReceptionistAI - VAPI Client Agent Template ============================================ Creates customized voice agents for new clients based on their business info. Usage: python vapi_client_template.py --create "Business Name" --type trades python vapi_client_template.py --list-agents python vapi_client_template.py --test-agent "agent_id" """ import os import sys import json import requests import argparse from datetime import datetime from pathlib import Path sys.path.insert(0, str(Path(__file__).parent.parent.parent)) class VAPIClientTemplate: """Creates and manages VAPI agents for ReceptionistAI clients.""" def __init__(self): self.api_key = os.getenv("VAPI_API_KEY", "5d7f9c70-7873-4182-93f3-f68db8e3a193") self.base_url = "https://api.vapi.ai" self.headers = { "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json" } # Voice options (ElevenLabs) self.voices = { "female_au": {"provider": "11labs", "voiceId": "pFZP5JQG7iQjIQuC4Bku", "model": "eleven_turbo_v2_5"}, "male_au": {"provider": "11labs", "voiceId": "IKne3meq5aSn9XLyUdCD", "model": "eleven_turbo_v2_5"}, "female_professional": {"provider": "11labs", "voiceId": "Xb7hH8MSUJpSbSDYk0k2", "model": "eleven_turbo_v2_5"} } # Industry-specific templates self.templates = self._load_templates() def _load_templates(self) -> dict: """Load industry-specific prompt templates.""" return { "trades": { "greeting": "G'day! Thanks for calling {business_name}. This is {ai_name}, your AI receptionist. How can I help you today?", "services_prompt": "We handle all kinds of {service_type} work - from small repairs to big jobs. Would you like to book a quote or get some info?", "booking_prompt": "I can book you in for a quote. What suburb are you in, and what's the best time for our {role} to come have a look?", "system_prompt": """You are {ai_name}, an AI receptionist for {business_name}, an Australian {service_type} business. ## Your Role - Answer calls professionally with a friendly Australian manner - Gather job details: what work is needed, location, urgency - Book quotes/appointments into the calendar - Take messages when the {role} is unavailable - Handle after-hours calls professionally ## Key Information - Business: {business_name} - Service Type: {service_type} - Service Areas: {service_areas} - Operating Hours: {operating_hours} - Emergency Contact: {emergency_contact} ## Conversation Flow 1. Greet warmly with Australian friendliness 2. Ask what they need help with 3. For quotes: Get address, job details, preferred time 4. For emergencies: Collect details, promise callback within 30 mins 5. For general inquiries: Provide helpful info or take message ## Phrases to Use - "No worries, I can help with that" - "Let me book you in for a quote" - "The {role} will give you a call back" - "Is this urgent or can it wait a day or two?" ## Never Do - Give specific prices (say "the {role} will quote after seeing the job") - Promise exact appointment times without checking - Share personal details about staff""" }, "medical": { "greeting": "Good morning, {business_name}, this is {ai_name}. How may I assist you today?", "services_prompt": "We offer a range of {service_type} services. Would you like to book an appointment?", "booking_prompt": "I can help you schedule an appointment. Are you an existing patient or new to our practice?", "system_prompt": """You are {ai_name}, an AI receptionist for {business_name}, a medical/health practice. ## Your Role - Handle appointment bookings professionally - Verify patient details (name, DOB, Medicare if applicable) - Triage urgency appropriately - Maintain strict confidentiality ## Key Information - Practice: {business_name} - Services: {service_type} - Hours: {operating_hours} ## Urgent Indicators (Transfer/Escalate) - Chest pain, difficulty breathing - Severe bleeding or injury - Mental health crisis - Allergic reactions ## Booking Flow 1. Confirm patient identity 2. Reason for visit (brief) 3. Preferred practitioner (if any) 4. Available times 5. Confirm details ## Compliance - Never provide medical advice - Always recommend emergency services for urgent issues - Maintain AHPRA compliance""" }, "legal": { "greeting": "Thank you for calling {business_name}. This is {ai_name}. How may I direct your call?", "services_prompt": "We practice in {service_type}. Would you like to schedule a consultation?", "booking_prompt": "I can arrange an initial consultation. May I take your name and brief details about your matter?", "system_prompt": """You are {ai_name}, an AI receptionist for {business_name}, a law firm. ## Your Role - Screen incoming calls professionally - Schedule consultations - Take detailed messages - Maintain strict confidentiality ## Key Information - Firm: {business_name} - Practice Areas: {service_type} - Partners: {staff_names} ## Important Guidelines - Never provide legal advice - All matters are confidential - Existing clients: verify identity before discussing matters - New inquiries: gather basic details only ## Booking Flow 1. Name and contact details 2. Type of legal matter (brief) 3. How they heard about us 4. Urgency level 5. Preferred solicitor (if any)""" }, "generic": { "greeting": "Hello, thank you for calling {business_name}. This is {ai_name}, how can I help you today?", "services_prompt": "We'd be happy to help you with {service_type}. What can I assist you with?", "booking_prompt": "I can schedule that for you. What day and time works best?", "system_prompt": """You are {ai_name}, an AI receptionist for {business_name}. ## Your Role - Answer calls professionally and warmly - Book appointments and take messages - Provide basic information about services - Transfer to appropriate staff when needed ## Key Information - Business: {business_name} - Services: {service_type} - Hours: {operating_hours} - Location: {location} ## Conversation Guidelines - Be friendly and helpful - Listen carefully to caller needs - Confirm all details before ending call - Offer to take a message if staff unavailable""" } } def _make_request(self, method: str, endpoint: str, data: dict = None) -> dict: """Make API request to VAPI.""" url = f"{self.base_url}{endpoint}" try: if method == "GET": response = requests.get(url, headers=self.headers, timeout=30) elif method == "POST": response = requests.post(url, headers=self.headers, json=data, timeout=30) elif method == "DELETE": response = requests.delete(url, headers=self.headers, timeout=30) else: return {"error": f"Unsupported method: {method}"} if response.status_code in [200, 201]: return response.json() if response.text else {"status": "success"} else: return {"error": response.text, "status_code": response.status_code} except Exception as e: return {"error": str(e)} def create_client_agent(self, business_info: dict) -> dict: """Create a customized agent for a client.""" # Get template industry = business_info.get("industry", "generic") template = self.templates.get(industry, self.templates["generic"]) # Build system prompt with client details ai_name = business_info.get("ai_name", "Alex") system_prompt = template["system_prompt"].format( ai_name=ai_name, business_name=business_info.get("business_name", "the business"), service_type=business_info.get("service_type", "our services"), service_areas=business_info.get("service_areas", "local area"), operating_hours=business_info.get("hours", "9am-5pm weekdays"), emergency_contact=business_info.get("emergency_contact", "the owner"), role=business_info.get("role", "team member"), location=business_info.get("location", ""), staff_names=business_info.get("staff_names", "our team") ) first_message = template["greeting"].format( ai_name=ai_name, business_name=business_info.get("business_name", "our business") ) # Select voice voice_key = business_info.get("voice", "female_au") voice_config = self.voices.get(voice_key, self.voices["female_au"]) # Create agent payload payload = { "name": f"{business_info.get('business_name', 'Client')} - ReceptionistAI", "firstMessage": first_message, "firstMessageMode": "assistant-speaks-first", "voice": { **voice_config, "stability": 0.5, "similarityBoost": 0.75 }, "model": { "provider": "openai", "model": "gpt-4o", "temperature": 0.7, "messages": [{"role": "system", "content": system_prompt}] }, "transcriber": { "provider": "deepgram", "model": "nova-3", "language": "en-AU" }, "backgroundDenoisingEnabled": True } print(f"🤖 Creating agent for: {business_info.get('business_name')}") result = self._make_request("POST", "/assistant", payload) if "id" in result: print(f"✅ Agent created! ID: {result['id']}") else: print(f"❌ Failed: {result.get('error')}") return result def list_agents(self) -> list: """List all agents in the account.""" print("📋 Fetching agents...") result = self._make_request("GET", "/assistant") if isinstance(result, list): print(f"Found {len(result)} agents:") for agent in result: print(f" - {agent.get('name', 'Unnamed')} | ID: {agent.get('id', 'N/A')}") return result else: print(f"Error: {result.get('error')}") return [] def get_agent(self, agent_id: str) -> dict: """Get details of a specific agent.""" return self._make_request("GET", f"/assistant/{agent_id}") def create_test_call(self, agent_id: str, phone_number: str) -> dict: """Initiate a test call to verify agent.""" print(f"📞 Initiating test call to {phone_number}...") payload = { "assistantId": agent_id, "customer": { "number": phone_number } } result = self._make_request("POST", "/call/phone", payload) if "id" in result: print(f"✅ Call initiated! Call ID: {result['id']}") else: print(f"❌ Failed: {result.get('error')}") return result def main(): parser = argparse.ArgumentParser(description="VAPI Client Agent Template for ReceptionistAI") parser.add_argument("--create", type=str, help="Create agent for business name") parser.add_argument("--type", type=str, default="generic", help="Industry type (trades/medical/legal/generic)") parser.add_argument("--list", action="store_true", help="List all agents") parser.add_argument("--get", type=str, help="Get agent details by ID") parser.add_argument("--test-call", type=str, help="Agent ID for test call") parser.add_argument("--phone", type=str, help="Phone number for test call") args = parser.parse_args() manager = VAPIClientTemplate() if args.create: business_info = { "business_name": args.create, "industry": args.type, "ai_name": "Maya", "service_type": args.type, "hours": "Monday-Friday 8am-5pm", "role": "team" } manager.create_client_agent(business_info) elif args.list: manager.list_agents() elif args.get: result = manager.get_agent(args.get) print(json.dumps(result, indent=2)) elif args.test_call and args.phone: manager.create_test_call(args.test_call, args.phone) else: parser.print_help() if __name__ == "__main__": main()