# Real estate agent (API) (/docs/examples/real-estate)
> Build a voice agent that handles property inquiries, schedules viewings, and manages client interactions via the API.
Build an inbound real estate voice agent end to end with the
OmniDimension Python SDK. The agent presents property listings, matches
client requirements, schedules viewings, and tracks call analytics.
### Get your API key [#get-your-api-key]
Get an API key from the OmniDimension dashboard, in the API section.
### Create the real estate assistant [#create-the-real-estate-assistant]
Start by creating your voice agent with real estate-specific
configuration.
```python
from omnidimension import Client
client = Client("your_api_key_here")
real_estate_agent = client.agent.create(
name="Sarah - Premier Properties Assistant",
welcome_message="Hello! This is Sarah from Premier Properties. I'm here to help you find your dream home or assist with any property inquiries. How can I help you today?",
context_breakdown=[
{
"title": "Available Properties",
"body": """RESIDENTIAL PROPERTIES:
- 3BR Luxury Condo: $450,000 | 2,200 sq ft | Downtown
- 4BR Family Home: $650,000 | 3,500 sq ft | Suburbs
- 2BR Starter Home: $325,000 | 1,800 sq ft | City Center
RENTAL PROPERTIES:
- 2BR Apartment: $2,200/month | 1,200 sq ft | Downtown
- 3BR Townhouse: $3,500/month | 2,000 sq ft | Suburbs
- 1BR Studio: $1,500/month | 800 sq ft | City Center
COMMERCIAL PROPERTIES:
- Office Space: $25/sq ft | 5,000 sq ft | Business District
- Retail Space: $30/sq ft | 3,000 sq ft | Shopping Center
- Warehouse: $15/sq ft | 10,000 sq ft | Industrial Zone"""
},
{
"title": "Inquiry Process",
"body": "1. Greet client professionally 2. Understand property requirements 3. Match with available listings 4. Schedule viewings if interested 5. Collect contact information 6. Provide market information"
},
{
"title": "Service Areas",
"body": "We serve the entire metropolitan area including Downtown, Suburbs, and surrounding neighborhoods. Our agents specialize in residential, commercial, and rental properties."
}
],
call_type="Incoming",
voice={
"provider": "eleven_labs",
"voice_id": "EXAVITQu4vr4xnSDxMaL"
},
model={
"provider": "anthropic",
"model": "gpt-4o-mini",
"temperature": 0.6
}
)
agent_id = real_estate_agent["json"]["id"]
print(f"Real estate agent created with ID: {agent_id}")
```
**Key components:**
* `welcome_message`: professional greeting establishing expertise
* Property listings: comprehensive inventory with prices and details
* Inquiry process: step-by-step workflow for handling inquiries
* Service areas: geographic coverage information
* Voice configuration: professional, trustworthy voice
### Upload property documentation [#upload-property-documentation]
Enhance your agent's knowledge by uploading property brochures.
```python
import base64
def upload_property_documentation(agent_id, brochure_path):
"""Upload property brochure to knowledge base and attach to agent"""
# Read and encode the PDF file
with open(brochure_path, "rb") as file:
file_data = base64.b64encode(file.read()).decode('utf-8')
# Upload to knowledge base
kb_response = client.knowledge_base.create(file_data, "Property_Brochure.pdf")
file_id = kb_response["json"]["file"]["id"]
# Attach to agent
attach_response = client.knowledge_base.attach([file_id], agent_id)
print(f"Property documentation uploaded successfully. File ID: {file_id}")
return file_id
# Upload your property brochure
brochure_file_id = upload_property_documentation(agent_id, "property_brochure.pdf")
```
### Handle incoming client calls [#handle-incoming-client-calls]
Your agent is now ready to handle incoming calls. When clients call your
office number, the agent will:
* Greet clients with the welcome message
* Understand requirements (property type, budget, location)
* Present matching properties based on client preferences
* Schedule viewings for interested properties
* Collect contact information for follow-up
* Provide market information and next steps
### Monitor performance and analytics [#monitor-performance-and-analytics]
Track your real estate agent's performance.
```python
def get_real_estate_analytics(agent_id, days=7):
"""Get comprehensive analytics for real estate agent"""
# Get recent call logs
call_logs = client.call.get_call_logs(agent_id=agent_id, page_size=100)
calls_data = call_logs.get('data', [])
# Calculate metrics
total_calls = len(calls_data)
successful_calls = sum(1 for call in calls_data if call.get('status') == 'completed')
average_duration = sum(call.get('duration', 0) for call in calls_data) / total_calls if total_calls > 0 else 0
# Generate report
analytics_report = {
"period_days": days,
"total_calls": total_calls,
"successful_calls": successful_calls,
"completion_rate": f"{(successful_calls/total_calls*100):.1f}%" if total_calls > 0 else "0%",
"average_call_duration": f"{average_duration:.1f} seconds",
"recent_calls": calls_data[:5] # Last 5 calls
}
return analytics_report
# Get weekly performance report
weekly_report = get_real_estate_analytics(agent_id, days=7)
print("Real Estate Agent Performance Report")
print(f"Total Calls: {weekly_report['total_calls']}")
print(f"Successful Calls: {weekly_report['successful_calls']}")
print(f"Completion Rate: {weekly_report['completion_rate']}")
print(f"Average Call Duration: {weekly_report['average_call_duration']}")
```
### Update agent configuration [#update-agent-configuration]
Modify your agent settings as needed.
```python
def update_agent_details(agent_id, **kwargs):
"""Update agent configuration"""
response = client.agent.update(agent_id, **kwargs)
print(f"Agent updated successfully")
return response
# Update welcome message for weekend hours
update_agent_details(
agent_id,
welcome_message="Good morning! Welcome to Premier Properties. Our weekend open houses are ready! How can I help you find your dream home?"
)
# Switch back to incoming calls
update_agent_details(
agent_id,
call_type="Incoming"
)
```
### Complete setup [#complete-setup]
Here's the complete setup for a production-ready real estate agent.
```python
from omnidimension import Client
import base64
class RealEstateVoiceAgent:
def __init__(self, api_key):
self.client = Client(api_key)
self.agent_id = None
def setup_complete_real_estate_agent(self):
"""Set up a complete real estate voice agent with all features"""
# Create the main agent
agent = self.client.agent.create(
name="Premier Properties - Voice Assistant",
welcome_message="Hello! This is Sarah from Premier Properties. I'm here to help you find your dream home or assist with any property inquiries. How can I help you today?",
context_breakdown=[
{
"title": "Complete Property Listings",
"body": """
RESIDENTIAL PROPERTIES:
- 3BR Luxury Condo: $450,000 | 2,200 sq ft | Downtown | Amenities: Pool, Gym, Doorman
- 4BR Family Home: $650,000 | 3,500 sq ft | Suburbs | Features: Large Yard, 2-Car Garage
- 2BR Starter Home: $325,000 | 1,800 sq ft | City Center | Features: Renovated Kitchen, Hardwood Floors
- 5BR Executive Home: $850,000 | 4,200 sq ft | Gated Community | Features: Home Office, Pool
RENTAL PROPERTIES:
- 2BR Apartment: $2,200/month | 1,200 sq ft | Downtown | Utilities Included
- 3BR Townhouse: $3,500/month | 2,000 sq ft | Suburbs | Pet-Friendly
- 1BR Studio: $1,500/month | 800 sq ft | City Center | Furnished Option Available
- 4BR House: $4,000/month | 2,800 sq ft | Suburbs | 12-month Lease
COMMERCIAL PROPERTIES:
- Office Space: $25/sq ft | 5,000 sq ft | Business District | Class A Building
- Retail Space: $30/sq ft | 3,000 sq ft | Shopping Center | High Foot Traffic
- Warehouse: $15/sq ft | 10,000 sq ft | Industrial Zone | Loading Docks
- Restaurant Space: $35/sq ft | 2,500 sq ft | Downtown | Former Restaurant
"""
},
{
"title": "Client Service Guidelines",
"body": "Always be professional and helpful. Listen carefully to client requirements. Suggest properties that match their needs. Offer virtual tours when possible. Follow up within 24 hours of initial inquiry."
},
{
"title": "Operational Details",
"body": "Office hours: 9 AM - 7 PM weekdays, 10 AM - 5 PM weekends. Service areas: Downtown, Suburbs, and surrounding neighborhoods. Specialties: Residential, Commercial, and Rental properties. Viewing appointments: 1-hour slots."
}
],
call_type="Incoming",
voice={
"provider": "eleven_labs",
"voice_id": "EXAVITQu4vr4xnSDxMaL"
},
model={
"provider": "anthropic",
"model": "gpt-4o-mini",
"temperature": 0.6
}
)
self.agent_id = agent["json"]["id"]
print(f"Real estate agent created: {self.agent_id}")
return self.agent_id
def get_performance_summary(self):
"""Get a quick performance summary"""
if not self.agent_id:
return "No agent configured"
calls = self.client.call.get_call_logs(agent_id=self.agent_id, page_size=50)
total_calls = len(calls.get('data', []))
return {
"agent_id": self.agent_id,
"total_calls_handled": total_calls,
"status": "Active and ready for inquiries!"
}
def upload_property_brochure(self, brochure_path):
"""Upload property brochure to knowledge base"""
if not self.agent_id:
print("Please create agent first")
return None
with open(brochure_path, "rb") as file:
file_data = base64.b64encode(file.read()).decode('utf-8')
kb_response = self.client.knowledge_base.create(file_data, "Property_Brochure.pdf")
file_id = kb_response["json"]["file"]["id"]
self.client.knowledge_base.attach([file_id], self.agent_id)
print(f"Property brochure uploaded: {file_id}")
return file_id
# Initialize and deploy real estate agent
real_estate = RealEstateVoiceAgent("your_api_key_here")
agent_id = real_estate.setup_complete_real_estate_agent()
# Upload brochure if you have a PDF
# real_estate.upload_property_brochure("property_brochure.pdf")
print("\nYour real estate voice agent is now live!")
print(f"Agent ID: {agent_id}")
```
## Key features [#key-features]
### Property management [#property-management]
* Complete property listings with prices and details
* Property matching through natural conversation
* Viewing scheduling and coordination
* Property information and market updates
### Call handling [#call-handling]
* Incoming client calls for property inquiries
* Natural conversation flow
* Professional real estate service experience
* Efficient lead qualification
### Analytics and monitoring [#analytics-and-monitoring]
* Call volume tracking
* Call completion rates
* Average call duration
* Detailed call logs and history
### Knowledge base [#knowledge-base]
* Upload property brochures for enhanced knowledge
* Attach multiple documents to your agent
* Comprehensive property and market information
* Easy knowledge management
### Agent management [#agent-management]
* Update agent configuration anytime
* Modify welcome messages and context
* Real-time agent performance monitoring
* Easy property listing updates