AI KestraKVStore

AI KestraKVStore
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Persist chat memory in Kestra KV

Caches chat messages in-memory and saves them to a namespace KV entry keyed by memoryId; TTL sets KV expiry, but some backends may ignore it. drop=AFTER_TASKRUN deletes the KV after use.

yaml
type: io.kestra.plugin.ai.memory.KestraKVStore

Examples

Store chat memory inside a KV pair

yaml
id: chat_with_memory
namespace: company.ai

inputs:
  - id: first
    type: STRING
    defaults: Hello, my name is John and I'm from Paris
  - id: second
    type: STRING
    defaults: What's my name and where am I from?

tasks:
  - id: first
    type: io.kestra.plugin.ai.rag.ChatCompletion
    chatProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-2.5-flash
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddingProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-embedding-001
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.KestraKVStore
    memory:
      type: io.kestra.plugin.ai.memory.KestraKVStore
    systemMessage: You are a helpful assistant, answer concisely
    prompt: "{{ inputs.first }}"

  - id: second
    type: io.kestra.plugin.ai.rag.ChatCompletion
    chatProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-2.5-flash
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddingProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-embedding-001
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.KestraKVStore
    memory:
      type: io.kestra.plugin.ai.memory.KestraKVStore
      drop: AFTER_TASKRUN
    systemMessage: You are a helpful assistant, answer concisely
    prompt: "{{ inputs.second }}"

Properties

drop string

DefaultNEVER

Possible Values

NEVERBEFORE_TASKRUNAFTER_TASKRUN

Drop memory: never, before, or after the agent's task run

By default, the memory ID is the value of the system.correlationId label, meaning that the same memory will be used by all tasks of the flow and its subflows. If you want to remove the memory eagerly (before expiration), you can set drop: AFTER_TASKRUN to erase the memory after the taskrun. You can also set drop: BEFORE_TASKRUN to drop the memory before the taskrun.

memoryId string

Default{{ labels.system.correlationId }}

Memory ID - defaults to the value of the system.correlationId label. This means that a memory is valid for the entire flow execution including its subflows.

messages integerstring

Default10

Maximum number of messages to keep in memory. If memory is full, the oldest messages will be removed in a FIFO manner. The last system message is always kept.

ttl string

DefaultPT1H

Memory duration - defaults to 1h