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Ollama Chat Model#

The Ollama Chat Model node allows you use local Llama 2 models with conversational agents.

On this page, you'll find the node parameters for the Ollama Chat Model node, and links to more resources.


You can find authentication information for this node here.

Examples and templates

For usage examples and templates to help you get started, refer to n8n's Ollama Chat Model integrations page.

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 {{ $ }} 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 {{ $ }} always resolves to the first name.

Node parameters#

  • Model: the model that generates the completion. Choose from:
    • Llama2
    • Llama2 13B
    • Llama2 70B
    • Llama2 Uncensored

Node options#

  • Sampling Temperature: controls the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
  • Top K: the number of token choices the model uses to generate the next token.
  • Top P: use a lower value to ignore less probable options.

View example workflows and related content on n8n's website.

Refer to LangChains's Ollama Chat Model documentation for more information about the service.

View n8n's Advanced AI documentation.