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Get ODI Trends

GET
/api/system/monitoring/odi/trends

Retrieve historical ODI metrics trends for performance analysis and visualization

Parameters

Section titled “ Parameters ”

Query Parameters

Section titled “Query Parameters ”
hours
Hours

Time range in hours (1-168)

integer
default: 24 >= 1 <= 168

Time range in hours (1-168)

Responses

Section titled “ Responses ”

200

Section titled “200 ”

Successful Response

ODITrendsData

Historical ODI metrics for trend analysis.

Time-series data for ODI metrics enabling trend visualization and performance analysis over time for ODI dashboard and trend monitoring.

Fields:

  • metrics: List of ODI metrics over time (list of ODIMetrics)
  • time_range_hours: Time range covered in hours (minimum 1 hour)
  • aggregation_interval: Interval between data points in seconds (minimum 60 seconds)
  • trends: Calculated trends for each metric (dict mapping metric name to trend: improving/degrading/stable)

Usage: GET /api/monitoring/odi/trends returns this response model for historical ODI metrics visualization and trend analysis.

JSON Example:

{
  "metrics": [
    {
      "agentCollaborationScore": 0.75,
      "consultationResponseTime": 2.5,
      "learningCycleLatency": 180.0,
      "patternRecognitionAccuracy": 0.85,
      "startupOptimizationRate": 0.30,
      "crashRecoverySuccessRate": 0.95,
      "userOverrideRate": 0.10,
      "timestamp": "2025-01-30T10:00:00Z"
    }
  ],
  "timeRangeHours": 24,
  "aggregationInterval": 3600,
  "trends": {
    "agent_collaboration": "improving",
    "learning_latency": "stable",
    "startup_optimization": "improving"
  }
}
object
metrics
required
Metrics

List of ODI metrics over time

Array<object>
ODIMetrics

Orchestrated Distributed Intelligence performance metrics.

Comprehensive ODI metrics tracking system performance, agent collaboration, learning efficiency, and human-AI interaction patterns for distributed intelligence monitoring and optimization.

Fields:

  • agent_collaboration_score: Cross-agent consultation rate per workflow (0.0-1.0)
  • consultation_response_time: Average agent consultation latency in seconds (non-negative)
  • learning_cycle_latency: Time from failure to learned pattern application in seconds (non-negative)
  • pattern_recognition_accuracy: Percentage of predicted issues that occurred (0.0-1.0)
  • startup_optimization_rate: Startup time improvement via Startup Intelligence (0.0-1.0)
  • crash_recovery_success_rate: Auto-recovery success rate by MIME (0.0-1.0)
  • user_override_rate: User override frequency for AI suggestions (0.0-1.0)
  • timestamp: Metric collection timestamp (ISO 8601 datetime)

Usage: GET /api/monitoring/odi/metrics returns this response model for ODI dashboard integration, real-time metrics visualization, and performance monitoring.

JSON Example:

{
  "agentCollaborationScore": 0.75,
  "consultationResponseTime": 2.5,
  "learningCycleLatency": 180.0,
  "patternRecognitionAccuracy": 0.85,
  "startupOptimizationRate": 0.30,
  "crashRecoverySuccessRate": 0.95,
  "userOverrideRate": 0.10,
  "timestamp": "2025-01-30T10:00:00Z"
}
object
agentCollaborationScore
required
Agentcollaborationscore

Cross-agent consultation rate per workflow (0.0-1.0)

number
<= 1
consultationResponseTime
required
Consultationresponsetime

Average agent consultation response time in seconds

number
learningCycleLatency
required
Learningcyclelatency

Time from failure to learned pattern application in seconds

number
patternRecognitionAccuracy
required
Patternrecognitionaccuracy

Percentage of predicted issues that actually occurred (0.0-1.0)

number
<= 1
startupOptimizationRate
required
Startupoptimizationrate

Startup time improvement via Startup Intelligence (0.0-1.0)

number
<= 1
crashRecoverySuccessRate
required
Crashrecoverysuccessrate

Percentage of crashes auto-recovered by MIME (0.0-1.0)

number
<= 1
userOverrideRate
required
Useroverriderate

Frequency of user overriding AI suggestions (0.0-1.0)

number
<= 1
timestamp
Timestamp

Timestamp when metrics were collected

string format: date-time
timeRangeHours
required
Timerangehours

Time range covered in hours

integer
>= 1
aggregationInterval
required
Aggregationinterval

Interval between data points in seconds

integer
>= 60
trends
Trends

Calculated trends: improving, degrading, stable

object
key
additional properties
string

422

Section titled “422 ”

Validation Error

HTTPValidationError
object
detail
Detail
Array<object>
ValidationError
object
loc
required
Location
Array
msg
required
Message
string
type
required
Error Type
string
input
Input
ctx
Context
object