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Add docs for Vector Store observability

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Mark Pollack
2024-08-22 11:07:35 -04:00
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spring-ai-docs/src/main/antora/modules/ROOT/pages/observabilty/index.adoc
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@@ -176,4 +176,43 @@ Spring AI supports storing these fields as events in OpenTelemetry and will prov
== Vector Stores
TBD
All vector store implementations in Spring AI are instrumented to provide metrics and distributed tracing data through Micrometer.
.Low Cardinality Keys
[cols="a,a"]
|===
|Name | Description
|`spring.ai.kind` |Spring AI kind - `vector_store`
|`db.system` | The database management system (DBMS) product as identified by the client instrumentation. One of `pg_vector`, `azure`, `cassandra`, `chroma`, `elasticsearch`, `milvus`, `neo4j`, `opensearch`, `qdrant`, `redis`, `typesense`, `weaviate`, `pinecone`, `oracle`, `mongodb`, `gemfire`, `hana`, `simple`
|`db.operation.name` |The name of the operation or command being executed. One of `add`, `delete`, or `query`.
|===
.High Cardinality Keys
[cols="a,a"]
|===
|Name | Description
|`db.collection.name` | The name of a collection (table, container) within the database.
|`db.vector.dimension_count` | The dimension of the vector.
|`db.vector.field_name` | The name field as of the vector (e.g. a field name).
|`db.vector.query.filter` | The metadata filters used in the search query.
|`db.namespace` | The namespace of the database.
|`db.vector.query.content` | The content of the search query being executed.
|`db.vector.query.response.documents` | Returned documents from a similarity search query. Needs to be enabled with auto-configuration and use of OpenTelemetry events.
|`db.vector.similarity_metric` | The metric used in similarity search.
|`db.vector.query.similarity_threshold` | Similarity threshold that accepts all search scores. A threshold value of 0.0 means any similarity is accepted or disable the similarity threshold filtering. A threshold value of 1.0 means an exact match is required.
|`db.vector.query.top_k` | The top-k most similar vectors returned by a query.
|===
=== Vector Store response data
The Vector Store response data are typically too big to be included in an observation as span attributes.
The preferred way to store large data it is as span events, which are supported by OpenTelemetry but not yet surfaced through the Micrometer APIs.
Spring AI supports storing these fields as events in OpenTelemetry and will provide a more general event based solution once the issue https://github.com/micrometer-metrics/micrometer/issues/5238 is resolved.
[cols="6,3,1"]
|===
| Property | Description | Default
| `spring.ai.vectorstore.observations.include-query-response` | `true` or `false` | `false`
|===