Hang Event - Interactly API

The hang event is triggered when the assistant fails to respond for 5+ seconds during a conversation. This indicates potential issues with LLM processing, connectivity, or system overload.

Hang events signal critical performance problems that can lead to poor user experience and call abandonment. Immediate investigation is recommended.

When It’s Triggered

This event is sent when:

The assistant takes longer than 5 seconds to generate a response
LLM API calls experience high latency or timeouts
System processing queues become backlogged
Network connectivity issues affect response generation

Event Structure

{
    "message": {
        "timestamp": 1772702490000,
        "type": "hang",
        "call": { /* Call Object */ },
        "assistant": { /* Assistant Object */ },
        "messages": [ /* Conversation up to hang */ ],
        "phone": { /* Phone Object */ },
        "customer": { /* Customer Object */ },
        "analysis": { /* Empty during hang */ }
    }
}

Key Fields

Field	Type	Description
`message.type`	string	Always “hang” for this event
`message.timestamp`	number	Unix timestamp when hang was detected
`call.status`	string	Typically “ongoing” when hang occurs
`messages`	array	Conversation history up to the point of hang

Call Object

The call object contains comprehensive information about the call session.

Field	Type	Description
`id`	string	Unique call identifier (e.g., “WC-82015760-c3bd-427d-a23b-ba9b07e4ab85”)
`teamId`	string	Organization/team identifier
`assistantId`	string	ID of the assistant handling this call
`callType`	string	Type of call: “web”, “phone”, etc.
`direction`	string	Call direction: “inbound” or “outbound”
`startAt`	string	ISO timestamp when call started
`endAt`	string	ISO timestamp when call ended (only in end-of-call-report)
`userNumber`	string	User’s phone number or identifier
`assistantNumber`	string	Assistant’s number or identifier
`status`	string	Current call status: “queued”, “ongoing”, “finished”, “forwarded”
`phoneCallStatus`	string	Detailed phone status: “in-progress”, “completed”, etc.
`phoneCallStatusReason`	string	Human-readable status reason
`callEndTriggerBy`	string	What triggered call end: “bot”, “user”, “system”
`assistantCallDuration`	number	Duration of call in milliseconds
`analysis`	analysis-object	Call analysis results
`recording`	object	Recording information with S3 bucket and path
`assistantOverrides`	object	Dynamic variables and validation overrides
`metadata`	object	Custom metadata associated with the call
`cost`	object	Cost breakdown (only in end-of-call-report)
`metrics`	object	Detailed call metrics (only in end-of-call-report)

Assistant Object

The assistant object contains the configuration and settings of the assistant handling the call.

In some webhook events, the assistant object may be truncated for brevity. The full assistant configuration is typically included in status-update events.

Field	Type	Description
`_id`	string	Unique assistant identifier
`name`	string	Display name of the assistant
`welcomeMessage`	string	Message played when call starts
`welcomeMessageMode`	string	How welcome message is triggered: “automatic”, “manual”
`welcomeMessageInterruptionsEnabled`	boolean	Whether users can interrupt welcome message
`endCallMessage`	string	Message played when call ends
`endCallPhrases`	array	Phrases that trigger call termination
`bargeInEnabled`	boolean	Whether users can interrupt assistant responses
`assistantProvider`	string	LLM provider: “openai”, “anthropic”, “gemini”, etc.
`assistantModel`	string	Specific model being used
`assistantSystemPrompt`	string	System prompt defining assistant behavior
`assistantTemperature`	number	LLM creativity setting (0.0 to 1.0)
`assistantMaxTokens`	number	Maximum tokens per response
`assistantAnalysis`	object	Configuration for call analysis features
`assistantServer`	object	Webhook configuration for this assistant
`config`	object	Speech-to-text and text-to-speech configurations

Key Subobjects

assistantAnalysis: Contains settings for summary generation, success evaluation, and structured data extraction
assistantServer: The webhook configuration that triggered this event
config.speech: STT/TTS vendor settings, voice configuration, and language options

Messages Object

The messages array contains the conversation history between the user and assistant.

Each conversation-update event includes all messages from the start of the call up to that point, not just the latest message. This ensures that if any individual event is missed, you still have the complete conversation context.

Message Structure

Field	Type	Description
`messageId`	string	Unique message identifier
`role`	string	Message sender: “user” or “assistant”
`text`	string	Transcribed or generated message content
`timestamp`	number	Unix timestamp in milliseconds
`metrics`	object	Performance metrics for this message
`skippedAssistantMessages`	array	Assistant messages that were skipped due to interruptions

Message Metrics

Each message includes detailed performance metrics:

Timeline Metrics

totalElapsedTimeMs: Total time since call start
offsetFromPreviousTurnMs: Time gap from previous message

Audio Metrics

totalAudioReceivedMs: Total audio duration received
audioDelayPerTurnMs: Audio processing delay for this turn
delayedPacketsPerTurnCount: Count of delayed network packets

Speech-to-Text (STT) Metrics

timestampMs: When transcription was completed
startOffsetMs/endOffsetMs: Audio segment boundaries
confidence: Transcription confidence score (0.0 to 1.0)
vadMs: Voice activity detection duration

Text-to-Speech (TTS) Metrics

audioDurationMs: Duration of generated audio
generationTimeMs: Time to generate audio
queueLatencyMs: Processing queue delay
isCachePlaying: Whether audio was served from cache

LLM Metrics

responseLatencyMs: Time for LLM to generate response
queueLatencyMs: Processing queue delay

Message Types

Welcome Messages: Have messageId starting with “welcome-”
User Messages: Have messageId starting with “user-”
Assistant Messages: Have complex messageId with user reference and timestamp

Hang Detection Logic

Example Payload

{
  "message": {
    "timestamp": 1772702490000,
    "type": "hang",
    "call": {
      "id": "WC-82015760-c3bd-427d-a23b-ba9b07e4ab85",
      "teamId": "67c0231ae6880fe48ef929ee",
      "assistantId": "697769ef5e6d94d5ad83e01e",
      "status": "ongoing",
      "assistantCallDuration": 15000
    },
    "assistant": {
      "_id": "697769ef5e6d94d5ad83e01e",
      "name": "Mary Dental - main",
      "assistantProvider": "gemini",
      "assistantModel": "gemini-3-flash-preview"
    },
    "messages": [
      {
        "messageId": "welcome-1",
        "role": "assistant",
        "text": "Welcome to Apollo clinic!!",
        "timestamp": 1772702480279
      },
      {
        "messageId": "user-1",
        "role": "user",
        "text": "I need to book an appointment for a complex procedure",
        "timestamp": 1772702485138
      }
    ],
    "customer": {
      "number": "web-Ramesh Naik"
    }
  }
}

Common Causes

LLM Provider Issues

API rate limiting or throttling
Provider service outages or degraded performance
Model capacity limitations during peak hours
Authentication or billing issues

System Resource Constraints

High CPU or memory usage on Interactly servers
Processing queue backlog
Database connection limitations
Network bandwidth constraints

Complex Queries

User requests requiring extensive reasoning
Long conversation context requiring more processing time
Queries that trigger multiple LLM function calls
Malformed or problematic user input

Response Strategies

Immediate Alerting

def handle_hang_event(event_data):
    call = event_data["message"]["call"]
    assistant = event_data["message"]["assistant"]
    timestamp = event_data["message"]["timestamp"]

    # Immediate alert to operations team
    alert_data = {
        "alert_type": "assistant_hang",
        "call_id": call["id"],
        "assistant_id": assistant["_id"],
        "assistant_name": assistant["name"],
        "provider": assistant["assistantProvider"],
        "model": assistant["assistantModel"],
        "hang_duration": "5+ seconds",
        "timestamp": timestamp,
        "severity": "high"
    }

    send_immediate_alert(alert_data)

    # Log for analysis
    logger.critical(f"Assistant hang detected: {call['id']}")

Performance Monitoring

def track_hang_metrics(event_data):
    call = event_data["message"]["call"]
    assistant = event_data["message"]["assistant"]

    # Increment hang counters
    metrics.increment("assistant.hang.count", tags={
        "assistant_id": assistant["_id"],
        "provider": assistant["assistantProvider"],
        "model": assistant["assistantModel"]
    })

    # Track by time of day for pattern analysis
    hour_of_day = datetime.fromtimestamp(
        event_data["message"]["timestamp"] / 1000
    ).hour

    metrics.increment("assistant.hang.by_hour", tags={
        "hour": hour_of_day,
        "provider": assistant["assistantProvider"]
    })

Automated Remediation

def auto_remediate_hang(event_data):
    call = event_data["message"]["call"]
    assistant = event_data["message"]["assistant"]

    # Check for patterns indicating system issues
    recent_hangs = get_recent_hangs(assistant["_id"], minutes=10)

    if len(recent_hangs) >= HANG_THRESHOLD:
        # Multiple hangs suggest systematic issue

        # Option 1: Switch to backup provider/model
        if assistant["assistantProvider"] == "openai":
            switch_assistant_provider(call["id"], "anthropic")

        # Option 2: Reduce response complexity
        adjust_assistant_parameters(call["id"], {
            "maxTokens": 100,  # Shorter responses
            "temperature": 0.3  # More deterministic
        })

        # Option 3: Graceful degradation message
        queue_fallback_response(call["id"],
            "I apologize for the delay. Let me help you with that.")

Pattern Analysis

def analyze_hang_patterns():
    # Get recent hang events
    recent_hangs = db.hang_events.find({
        "timestamp": {"$gte": datetime.utcnow() - timedelta(hours=24)}
    })

    # Group by various dimensions
    patterns = {
        "by_provider": defaultdict(int),
        "by_model": defaultdict(int),
        "by_assistant": defaultdict(int),
        "by_hour": defaultdict(int),
        "by_conversation_length": defaultdict(int)
    }

    for hang in recent_hangs:
        assistant = hang["message"]["assistant"]
        timestamp = hang["message"]["timestamp"]
        messages = hang["message"]["messages"]

        patterns["by_provider"][assistant["assistantProvider"]] += 1
        patterns["by_model"][assistant["assistantModel"]] += 1
        patterns["by_assistant"][assistant["_id"]] += 1

        hour = datetime.fromtimestamp(timestamp / 1000).hour
        patterns["by_hour"][hour] += 1

        msg_count = len(messages)
        patterns["by_conversation_length"][f"{msg_count//5*5}-{msg_count//5*5+4}"] += 1

    # Generate insights
    generate_hang_insights(patterns)

User Experience Impact

Hang events directly affect user experience:

User Behavior During Hangs

Users may repeat their question
Users might hang up if wait is too long
Users experience frustration and reduced trust
Call abandonment rate increases significantly

Mitigation Strategies

def implement_hang_mitigation():
    # Strategy 1: Proactive timeout warnings
    # After 3 seconds of processing, play hold message

    # Strategy 2: Streaming responses
    # Start playing response as it's generated

    # Strategy 3: Fallback responses
    fallback_responses = [
        "Let me think about that for a moment...",
        "I'm processing your request, please hold on...",
        "That's a great question, give me just a second..."
    ]

    # Strategy 4: Context reduction
    # If conversation is very long, summarize for faster processing

Prevention Best Practices

Assistant Configuration

{
    "assistantModel": "gpt-4o-mini",  // Faster models for time-sensitive uses
    "assistantMaxTokens": 150,        // Limit response length
    "assistantTemperature": 0.3,      // More deterministic = faster
    "assistantSystemPrompt": "Keep responses concise and direct. Aim for 1-2 sentences maximum."
}

Monitoring Thresholds

# Set up monitoring for early warning signs
MONITORING_RULES = {
    "response_time_p95": {
        "threshold": 3000,  # 3 seconds
        "alert": "warning"
    },
    "hang_rate": {
        "threshold": 0.05,  # 5% of calls
        "window": "1h",
        "alert": "critical"
    },
    "provider_error_rate": {
        "threshold": 0.02,  # 2% error rate
        "alert": "warning"
    }
}

Load Balancing

def implement_provider_fallback():
    # Primary: Fast, reliable provider
    # Secondary: Backup with different characteristics

    provider_config = {
        "primary": {
            "provider": "openai",
            "model": "gpt-4o-mini",
            "max_tokens": 150
        },
        "fallback": {
            "provider": "anthropic",
            "model": "claude-3-haiku",
            "max_tokens": 100
        }
    }

Recovery Actions

When hang events occur:

Monitor: Track if response eventually comes through
Alert: Notify engineering team for investigation
Document: Record context for post-incident analysis
Optimize: Adjust assistant settings to prevent recurrence
Communicate: Update users about potential temporary delays

Related Events

Hang events often precede error events if the underlying issue persists

Hang Event Example

This is a complete example of a hang webhook event payload.

{
    "message": {
        "timestamp": 1772702490000,
        "type": "hang",
        "call": {
            "id": "WC-82015760-c3bd-427d-a23b-ba9b07e4ab85",
            "teamId": "67c0231ae6880fe48ef929ee",
            "assistantId": "697769ef5e6d94d5ad83e01e",
            "callType": "web",
            "direction": "inbound",
            "startAt": "2026-03-05T09:21:20.063Z",
            "userNumber": "web-Ramesh Naik",
            "assistantNumber": "697769ef5e6d94d5ad83e01e",
            "status": "ongoing",
            "phoneCallStatus": "in-progress",
            "phoneCallStatusReason": "Call is in progress",
            "callEndTriggerBy": "",
            "assistantCallDuration": 15000,
            "analysis": {
                "summary": "",
                "successEvaluation": ""
            },
            "recording": {
                "s3Bucket": "",
                "path": ""
            },
            "assistantOverrides": {
                "dynamicVariables": {
                    "serial_number": ""
                },
                "variablesValidations": {
                    "serial_number": "none"
                }
            },
            "metadata": {}
        },
        "assistant": {
            "_id": "697769ef5e6d94d5ad83e01e",
            "name": "Mary Dental - main",
            "welcomeMessage": "Welcome to Apollo clinic!!",
            "assistantProvider": "gemini",
            "assistantModel": "gemini-3-flash-preview",
            "assistantSystemPrompt": "You here are a voice assistant for Apollo clinic clinic, located at 123 North Face Place, Anaheim, California. Your name is Rachel...",
            "assistantTemperature": 0,
            "assistantMaxTokens": 256
        },
        "messages": [
            {
                "messageId": "welcome-1",
                "role": "assistant",
                "text": "Welcome to Apollo clinic!!",
                "timestamp": 1772702480279,
                "metrics": {
                    "tts": {
                        "audioDurationMs": 1442,
                        "generationTimeMs": 7,
                        "isCachePlaying": true
                    }
                }
            },
            {
                "messageId": "user-1",
                "role": "user",
                "text": "I need to book an appointment for a complex orthopedic procedure that requires consultation with multiple specialists and coordination between different departments.",
                "timestamp": 1772702485138,
                "metrics": {
                    "stt": {
                        "confidence": 0.7364502,
                        "durationMs": 4200
                    }
                },
                "skippedAssistantMessages": []
            }
        ],
        "phone": {
            "provider": {
                "name": ""
            }
        },
        "customer": {
            "number": "web-Ramesh Naik"
        },
        "analysis": {}
    }
}

Context

This hang event occurred after a user made a complex request that required significant LLM processing time. The assistant failed to respond within the 5-second threshold, triggering the hang event. The system continued processing the request and may eventually deliver a response or trigger an error event if processing ultimately fails.

​When It’s Triggered

​Event Structure

​Key Fields

​Call Object

​Assistant Object

​Key Subobjects

​Messages Object

​Message Structure

​Message Metrics

​Timeline Metrics

​Audio Metrics

​Speech-to-Text (STT) Metrics

​Text-to-Speech (TTS) Metrics

​LLM Metrics

​Message Types

​Hang Detection Logic

​Example Payload

​Common Causes

​LLM Provider Issues

​System Resource Constraints

​Complex Queries

​Response Strategies

​Immediate Alerting

​Performance Monitoring

​Automated Remediation

​Pattern Analysis

​User Experience Impact

​User Behavior During Hangs

​Mitigation Strategies

​Prevention Best Practices

​Assistant Configuration

​Monitoring Thresholds

​Load Balancing

​Recovery Actions

Related Events

​Hang Event Example

​Context

When It’s Triggered

Event Structure

Key Fields

Call Object

Assistant Object

Key Subobjects

Messages Object

Message Structure

Message Metrics

Timeline Metrics

Audio Metrics

Speech-to-Text (STT) Metrics

Text-to-Speech (TTS) Metrics

LLM Metrics

Message Types

Hang Detection Logic

Example Payload

Common Causes

LLM Provider Issues

System Resource Constraints

Complex Queries

Response Strategies

Immediate Alerting

Performance Monitoring

Automated Remediation

Pattern Analysis

User Experience Impact

User Behavior During Hangs

Mitigation Strategies

Prevention Best Practices

Assistant Configuration

Monitoring Thresholds

Load Balancing

Recovery Actions

Hang Event Example

Context