Chat Memory backed by Redis
Persist chat memory in a Redis store using the memory ID as the key. The Redis entry will expire after the provided TTL. Ensure your Redis instance is reachable and configured via environment or plugin properties.
type: "io.kestra.plugin.ai.memory.Redis"Examples
Use Redis-based chat memory for a conversation
id: "redis"
type: "io.kestra.plugin.ai.memory.Redis"
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: "{{ kv('GEMINI_API_KEY') }}"
    embeddingProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-embedding-exp-03-07
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.KestraKVStore
    memory:
      type: io.kestra.plugin.ai.memory.Redis
      host: localhost
      port: 6379
    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: "{{ kv('GEMINI_API_KEY') }}"
    embeddingProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-embedding-exp-03-07
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.KestraKVStore
    memory:
      type: io.kestra.plugin.ai.memory.Redis
      host: localhost
      port: 6379
      drop: AFTER_TASKRUN
    systemMessage: You are a helpful assistant, answer concisely
    prompt: "{{inputs.second}}"
Properties
host *Requiredstring
Redis host
The hostname of your Redis server (e.g., localhost or redis-server)
drop string
NEVERNEVERBEFORE_TASKRUNAFTER_TASKRUNDrop 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
{{ 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
10Maximum 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.
port integerstring
6379Redis port
The port of your Redis server
ttl string
PT1HdurationMemory duration - defaults to 1h
