Examples

Customer Support Agent

Track and analyze customer support conversations to improve response quality and resolution rates.

from whispey import LivekitObserve

# Initialize Whispey
whispey = LivekitObserve(
    agent_id="support-agent-001",
    apikey="your-api-key"
)

# Start session with customer info
session_id = whispey.start_session(
    session=your_livekit_session,
    customer_name="Sarah Johnson",
    conversation_type="customer_support",
    metadata={
        "department": "technical_support",
        "priority": "medium",
        "product": "mobile_app"
    }
)

# Export on shutdown via callback
async def whispey_shutdown():
    await whispey.export(session_id)

ctx.add_shutdown_callback(whispey_shutdown)

# Start your LiveKit session
await session.start(...)

Sales Assistant

Monitor sales conversations to track conversion rates and optimize sales strategies.

# Initialize for sales tracking
whispey = LivekitObserve(
    agent_id="sales-agent-002",
    apikey="your-api-key"
)

session_id = whispey.start_session(
    session=your_livekit_session,
    customer_name="Mike Chen",
    conversation_type="sales_call",
    metadata={
        "product": "enterprise_plan",
        "lead_source": "website",
        "budget_range": "5000-10000"
    }
)

# Export on shutdown via callback
async def whispey_shutdown():
    await whispey.export(session_id)

ctx.add_shutdown_callback(whispey_shutdown)

# Start your LiveKit session
await session.start(...)

Appointment Scheduler

Optimize appointment booking conversations for better user experience.

# Initialize for appointment tracking
whispey = LivekitObserve(
    agent_id="scheduler-003",
    apikey="your-api-key"
)

session_id = whispey.start_session(
    session=your_livekit_session,
    conversation_type="appointment_booking",
    metadata={
        "service_type": "consultation",
        "location": "downtown_office"
    }
)

# Export on shutdown via callback
async def whispey_shutdown():
    await whispey.export(session_id)

ctx.add_shutdown_callback(whispey_shutdown)

# Start your LiveKit session
await session.start(...)

Multi-Agent Analytics

Compare performance across multiple agents and identify best practices.

# Track multiple agents
agents = {
    "agent_1": LivekitObserve(agent_id="agent-001", apikey="your-api-key"),
    "agent_2": LivekitObserve(agent_id="agent-002", apikey="your-api-key"),
    "agent_3": LivekitObserve(agent_id="agent-003", apikey="your-api-key")
}

# Start sessions for comparison
sessions = {}
for name, agent in agents.items():
    sessions[name] = agent.start_session(
        session=your_livekit_session,
        metadata={"agent_name": name, "test_scenario": "customer_inquiry"}
    )

# Track consistent metrics across agents
for name, session_id in sessions.items():
    async def whispey_shutdown():
        await agents[name].export(session_id)
    ctx.add_shutdown_callback(whispey_shutdown)
    await your_livekit_session.start(...)

# Export all sessions for comparison
for name, session_id in sessions.items():
    await agents[name].export(session_id)

Bug Reporting Integration

Enable automatic bug detection and reporting in your conversations.

# Initialize with bug reporting
whispey = LivekitObserve(
    agent_id="bug-reporting-004",
    apikey="your-api-key",
    bug_reports_enable=True,
    bug_reports_config={
        "bug_start_command": ["report issue", "there's a problem", "bug report"],
        "bug_end_command": ["issue resolved", "problem fixed", "bug resolved"],
        "response": "Please describe the issue.",
        "collection_prompt": "Got it, anything else?"
    }
)

session_id = whispey.start_session(session=your_livekit_session)

async def whispey_shutdown():
    await whispey.export(session_id)
ctx.add_shutdown_callback(whispey_shutdown)
await session.start(...)

OpenTelemetry Integration

Enable detailed telemetry collection for advanced monitoring.

# Initialize with OpenTelemetry
whispey = LivekitObserve(
    agent_id="otel-enabled-005",
    apikey="your-api-key",
    enable_otel=True
)

session_id = whispey.start_session(session=your_livekit_session)

async def whispey_shutdown():
    await whispey.export(session_id)
ctx.add_shutdown_callback(whispey_shutdown)
await session.start(...)

Dashboard Integration

Integrate Whispey analytics with your existing dashboard and reporting systems.

# Initialize for dashboard integration
whispey = LivekitObserve(
    agent_id="dashboard-integration-006",
    apikey="your-api-key"
)

session_id = whispey.start_session(
    session=your_livekit_session,
    metadata={
        "dashboard_id": "main_dashboard",
        "reporting_frequency": "real_time"
    }
)

async def whispey_shutdown():
    await whispey.export(session_id)
ctx.add_shutdown_callback(whispey_shutdown)
result = await session.start(...)

# Send to dashboard API
if result.get("success"):
    dashboard_data = {
        "session_id": session_id,
        "metrics": result.get("data", {}),
        "timestamp": datetime.now().isoformat()
    }
    # Send to your dashboard API
    await send_to_dashboard(dashboard_data)

Best Practices

Event Tracking

Use consistent event names across all agents
Include relevant metadata with each event
Track both user actions and system responses
Monitor error rates and failure points

Metrics Collection

Focus on actionable metrics that drive improvements
Track both quantitative (time, cost) and qualitative (satisfaction) metrics
Set up alerts for performance thresholds
Regular analysis of trends and patterns

Privacy and Compliance

Ensure customer data is handled according to privacy regulations
Implement data retention policies
Use anonymized data for analytics where possible
Regular security audits of data handling

Performance Optimization

Monitor response times and optimize slow operations
Track token usage to manage costs effectively
Analyze conversation patterns to improve agent responses
Regular review of analytics to identify improvement opportunities

More Examples

For additional examples and advanced use cases, visit our GitHub Examples Repository.

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