Documentation Index
Fetch the complete documentation index at: https://docs.mixpeek.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Alerts let you attach retriever pipelines to collections so that every ingested document is automatically checked against your search criteria. When matches are found, notifications fire to your configured channels (webhook, Slack, or email).
How It Works
- Create a retriever that defines your search criteria (e.g., semantic similarity, attribute filters)
- Create an alert referencing that retriever, with notification channels configured
- Attach the alert to a collection via
alert_applications with input mappings
- Ingest documents — alerts execute automatically during post-processing (Phase 3)
- Receive notifications when matches are found
Architecture
Alerts execute during the post-processing pipeline after document ingestion completes:
| Phase | System | Purpose |
|---|
| 1 | Taxonomies | Vector-based classification |
| 2 | Clusters | Document grouping |
| 3 | Alerts | Retriever execution + notifications |
| 4 | Retriever Enrichments | Field write-back |
Parallel Execution
Within a single alert, document-level retriever calls execute in parallel as independent Ray tasks. If a batch ingests 100 documents, all 100 retriever calls fan out simultaneously rather than running sequentially. Results are aggregated after all calls complete, and a single notification is sent if any document produced matches.
Multiple alerts on the same collection execute sequentially to avoid race conditions in notification delivery.
Configuration
Create an Alert
from mixpeek import Mixpeek
client = Mixpeek(api_key="your-api-key")
alert = client.alerts.create(
name="safety_content_monitor",
description="Detect potentially harmful content on ingestion",
retriever_id="ret_safety_classifier",
notification_config={
"channels": [
{
"channel_type": "webhook",
"config": {"url": "https://your-app.com/webhooks/alerts"}
},
{
"channel_type": "slack",
"config": {"channel": "#content-alerts"}
}
],
"include_matches": True,
"include_scores": True
},
enabled=True
)
Attach to a Collection
Attach alerts to collections via alert_applications when creating or updating a collection:
client.collections.create(
collection_name="user_uploads",
source={"type": "bucket", "bucket_ids": [bucket_id]},
feature_extractor={
"feature_extractor_name": "text_extractor",
"version": "v1",
"input_mappings": {"text": "content"},
},
alert_applications=[
{
"alert_id": alert.alert_id,
"execution_mode": "on_ingest",
"input_mappings": [
{
"input_key": "query_text",
"source": {
"source_type": "document_field",
"path": "content"
}
}
]
}
]
)
| Source Type | Description | Example |
|---|
document_field | Extract value from the ingested document using a dot-notation path | {"source_type": "document_field", "path": "metadata.category"} |
constant | Pass a fixed value to the retriever | {"source_type": "constant", "value": "safety_check"} |
Execution Modes
| Mode | Behavior |
|---|
on_ingest | Execute automatically when documents are ingested (default) |
scheduled | Execute on a schedule (does not trigger on ingest) |
on_demand | Execute only when manually triggered |
Notification Channels
Webhook
{
"channel_type": "webhook",
"config": {"url": "https://your-app.com/webhooks/alerts"}
}
Slack
{
"channel_type": "slack",
"config": {"channel": "#alerts-channel"}
}
Email
{
"channel_type": "email",
"config": {"to": ["alerts@your-company.com"]}
}
Monitoring Executions
Track alert execution history to monitor performance and debug issues:
executions = client.alerts.list_executions(alert_id="alert_id")
for execution in executions.results:
print(f"Execution {execution.execution_id}: "
f"triggered={execution.triggered}, "
f"matches={execution.match_count}, "
f"duration={execution.duration_ms}ms")
Comparison with Other Enrichment Types
| Feature | Taxonomies | Clusters | Alerts | Retriever Enrichments |
|---|
| Purpose | Vector-based classification | Document grouping | Notifications on match | Arbitrary retriever pipelines |
| Output | Label + score fields | Cluster assignments | Webhook/Slack/email notifications | Configurable field write-back |
| Phase | 1 | 2 | 3 | 4 |
| Execution | Parallel per document | Batch | Parallel per document | Sequential per document |
| Use cases | Face matching, entity linking | Segmentation, pattern discovery | Content monitoring, safety checks | LLM classification, cross-collection joins |
