AI Agent
Description
Runs an LLM agent using the task prompt and available tools, returning either text or structured output. The component is available after at least one AI integration is configured in the Admin Panel.
Parameters and configuration
| Name | Description |
|---|---|
| LLM Integration | LLM integration to use. |
| Chat model name | The chat model to use. The available models depend on the LLM Integration selected. |
| Prompt | Description of the concrete task to be performed. |
| MCP tools access | You can choose here which tools exposed by the defined MCP integrations can be used. |
| Output variable name | Variable name under which node result will be available in a subsequent nodes. |
Advanced parameters:
| Name | Description |
|---|---|
| System message | Reusable rules that define how the agent should behave. Some AI agents providers use 'agent instructions' term here. |
| Max iterations | Maximum reasoning/tool-use loop count. |
| Output schema | Optional; a JSON Schema describing the desired response. When provided, the agent's final answer becomes a typed record — see Structured output on the Chat LLM page for details. |
| Temperature | Temperature is a hyperparameter that controls the randomness of text generation. Lower values (e.g., 0.2) make the model’s output more focused and deterministic by favoring the most likely tokens, while higher values (e.g., 0.8 or above) produce more diverse and creative responses by flattening the probability distribution. |
Returned value
By default the component returns the agent's final answer as plain text (String).
When an Output schema is provided, the agent's final answer is typed against the schema in exactly the same way as the Chat LLM component: the returned value becomes a record with a raw field (the answer as text) and a structured field (the answer parsed and typed against the schema, or null when it is not valid JSON or does not match the schema). See Structured output for a full description and example.
Additional considerations
- You can use string template during prompt creation to use data available in the scenario (e.g., documents retrieved from the vector store)
- Currently only selected models are available. Contact us if you need to use additional ones.