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Motorhead Node#

Verwenden Sie den Motorhead-Node, um Motorhead als Memory-Server zu verwenden.

Auf dieser Seite finden Sie eine Liste der Operationen, die der Motorhead-Node unterstützt, sowie Links zu weiteren Ressourcen.

Anmeldedaten

Informationen zur Authentifizierung für diesen Node finden Sie hier.

Node-Parameter#

  • Session-ID: Geben Sie die ID ein, die zum Speichern des Speichers in den Workflow-Daten verwendet werden soll.

Node-Referenz#

Parameter resolution in sub-nodes

Sub-nodes behave differently to other nodes when processing multiple items using an expression.

Most nodes, including root nodes, take any number of items as input, process these items, and output the results. You can use expressions to refer to input items, and the node resolves the expression for each item in turn. For example, given an input of five name values, the expression {{ $json.name }} resolves to each name in turn.

In sub-nodes, the expression always resolves to the first item. For example, given an input of five name values, the expression {{ $json.name }} always resolves to the first name.

Verwandte Ressourcen#

Weitere Informationen zum Dienst finden Sie in der Motorhead-Dokumentation von LangChain.

View Localmind Automate's Advanced AI documentation.

Einzelne Speicherinstanz#

If you add more than one Motorhead node to your workflow, all nodes access the same memory instance by default. Be careful when doing destructive actions that override existing memory contents, such as the override all messages operation in the Chat Memory Manager node. If you want more than one memory instance in your workflow, set different session IDs in different memory nodes.

AI glossary#

  • completion: Completions are the responses generated by a model like GPT.
  • hallucinations: Hallucination in AI is when an LLM (large language model) mistakenly perceives patterns or objects that don't exist.
  • vector database: A vector database stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.
  • vector store: A vector store, or vector database, stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.