= pinecone
:type: output
:status: experimental
:categories: ["AI"]



////
     THIS FILE IS AUTOGENERATED!

     To make changes, edit the corresponding source file under:

     https://github.com/redpanda-data/connect/tree/main/internal/impl/<provider>.

     And:

     https://github.com/redpanda-data/connect/tree/main/cmd/tools/docs_gen/templates/plugin.adoc.tmpl
////

// © 2024 Redpanda Data Inc.


component_type_dropdown::[]


Inserts items into a Pinecone index.

Introduced in version 4.31.0.


[tabs]
======
Common::
+
--

```yml
# Common config fields, showing default values
output:
  label: ""
  pinecone:
    max_in_flight: 64
    batching:
      count: 0
      byte_size: 0
      period: ""
      check: ""
    host: "" # No default (required)
    api_key: "" # No default (required)
    operation: upsert-vectors
    id: "" # No default (required)
    vector_mapping: root = this.embeddings_vector # No default (optional)
    metadata_mapping: root = @ # No default (optional)
```

--
Advanced::
+
--

```yml
# All config fields, showing default values
output:
  label: ""
  pinecone:
    max_in_flight: 64
    batching:
      count: 0
      byte_size: 0
      period: ""
      check: ""
      processors: [] # No default (optional)
    host: "" # No default (required)
    api_key: "" # No default (required)
    operation: upsert-vectors
    namespace: ""
    id: "" # No default (required)
    vector_mapping: root = this.embeddings_vector # No default (optional)
    metadata_mapping: root = @ # No default (optional)
```

--
======


== Performance

This output benefits from sending multiple messages in flight in parallel for improved performance. You can tune the max number of in flight messages (or message batches) with the field `max_in_flight`.

This output benefits from sending messages as a batch for improved performance. Batches can be formed at both the input and output level. You can find out more xref:configuration:batching.adoc[in this doc].

== Fields

=== `max_in_flight`

The maximum number of messages to have in flight at a given time. Increase this to improve throughput.


*Type*: `int`

*Default*: `64`

=== `batching`

Allows you to configure a xref:configuration:batching.adoc[batching policy].


*Type*: `object`


```yml
# Examples

batching:
  byte_size: 5000
  count: 0
  period: 1s

batching:
  count: 10
  period: 1s

batching:
  check: this.contains("END BATCH")
  count: 0
  period: 1m
```

=== `batching.count`

A number of messages at which the batch should be flushed. If `0` disables count based batching.


*Type*: `int`

*Default*: `0`

=== `batching.byte_size`

An amount of bytes at which the batch should be flushed. If `0` disables size based batching.


*Type*: `int`

*Default*: `0`

=== `batching.period`

A period in which an incomplete batch should be flushed regardless of its size.


*Type*: `string`

*Default*: `""`

```yml
# Examples

period: 1s

period: 1m

period: 500ms
```

=== `batching.check`

A xref:guides:bloblang/about.adoc[Bloblang query] that should return a boolean value indicating whether a message should end a batch.


*Type*: `string`

*Default*: `""`

```yml
# Examples

check: this.type == "end_of_transaction"
```

=== `batching.processors`

A list of xref:components:processors/about.adoc[processors] to apply to a batch as it is flushed. This allows you to aggregate and archive the batch however you see fit. Please note that all resulting messages are flushed as a single batch, therefore splitting the batch into smaller batches using these processors is a no-op.


*Type*: `array`


```yml
# Examples

processors:
  - archive:
      format: concatenate

processors:
  - archive:
      format: lines

processors:
  - archive:
      format: json_array
```

=== `host`

The host for the Pinecone index.


*Type*: `string`


=== `api_key`

The Pinecone api key.
[CAUTION]
====
This field contains sensitive information that usually shouldn't be added to a config directly, read our xref:configuration:secrets.adoc[secrets page for more info].
====



*Type*: `string`


=== `operation`

The operation to perform against the Pinecone index.


*Type*: `string`

*Default*: `"upsert-vectors"`

Options:
`update-vector`
, `upsert-vectors`
, `delete-vectors`
.

=== `namespace`

The namespace to write to - writes to the default namespace by default.
This field supports xref:configuration:interpolation.adoc#bloblang-queries[interpolation functions].


*Type*: `string`

*Default*: `""`

=== `id`

The ID for the index entry in Pinecone.
This field supports xref:configuration:interpolation.adoc#bloblang-queries[interpolation functions].


*Type*: `string`


=== `vector_mapping`

The mapping to extract out the vector from the document. The result must be a floating point array. Required if not a delete operation.


*Type*: `string`


```yml
# Examples

vector_mapping: root = this.embeddings_vector

vector_mapping: root = [1.2, 0.5, 0.76]
```

=== `metadata_mapping`

An optional mapping of message to metadata in the Pinecone index entry.


*Type*: `string`


```yml
# Examples

metadata_mapping: root = @

metadata_mapping: root = metadata()

metadata_mapping: 'root = {"summary": this.summary, "foo": this.other_field}'
```