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    Temporal

    Temporal Event Detection & Alerting

    Sliding window search + temporal aggregation + threshold alerts. This is just retrieval + time—not a special system.

    video
    audio
    text
    Production
    43.0K runs
    Deploy Recipe

    Why This Matters

    Temporal queries are retrieval operations with time constraints. Frame-level embeddings enable precise event detection.

    from mixpeek import Mixpeek
    client = Mixpeek(api_key="your-api-key")
    # Create alert condition retriever
    alert_retriever = client.retrievers.create(
    retriever_name="safety_monitor",
    stages=[
    {
    "stage_id": "feature_search",
    "config": {
    "query_text": "violence OR weapons OR threatening behavior"
    }
    },
    {
    "stage_id": "score_filter",
    "config": {
    "min_score": 0.85
    }
    }
    ],
    webhook_url="https://api.company.com/alerts"
    )
    # Monitor live stream
    stream_results = client.retrievers.execute(
    retriever_id=alert_retriever.id,
    inputs={
    "collection_id": "live_streams",
    "time_window": "last_5_minutes"
    }
    )
    # Trigger alert if matches found
    if len(stream_results['documents']) > 0:
    client.webhooks.trigger(
    webhook_url=alert_retriever.webhook_url,
    payload=stream_results
    )

    Retrieval Flow

    1

    Semantic match against alert conditions

    2

    Time window filtering

    3
    score filter(filter)

    Confidence threshold

    Feature Extractors

    Video Embedding

    Generate vector embeddings for video content

    610K runs

    Audio Transcription

    Transcribe audio content to text

    450K runs

    Text Embedding

    Extract semantic embeddings from documents, transcripts and text content

    827K runs

    Retriever Stages

    feature search

    Search collections using multimodal embeddings

    search

    attribute filter

    Filter documents by metadata attributes

    filter

    score filter

    Filter documents by relevance score threshold

    filter

    Documentation