Call LLM
Generate text, JSON, or tabular data using a large language model.
Sends a prompt to a language model and emits what comes back.
executionMode decides whether the prompt runs once for the whole input or once per row; outputMode decides what the response port carries — free text, parsed JSON against jsonSchema, or a frame built to outputSchema. Durable by default: the call is a paid side effect that should be retried by the workflow, not re-run on every reactive tick.
At a glance
Module type
CallLLM
Category
Intelligence
Default tier
durable
Runs on
reactive, durable
Starts a flow
no
Holds a body
no
Keeps state between runs
no
Available in
every application type
Parameters
provider
string · required · defaults to ""
Which model provider to call.
model
string · required · defaults to ""
The model id on that provider.
systemPrompt
string · required · defaults to ""
The system prompt, sent unchanged on every call.
userPromptTemplate
string · required · defaults to ""
The user prompt; {{...}} interpolates from the context port and, per row, the row.
executionMode
"once" | "perRow" · required · defaults to "once"
Call once for the whole input, or once per row of it.
outputMode
"text" | "json" | "dataframe" · required · defaults to "text"
What response carries: free text, JSON parsed against jsonSchema, or a frame.
dataframeMode
"generateTable" | "enrichRows" · optional
In dataframe mode: build a new table, or add columns to the rows that went in.
outputSchema
SchemaEntryModel[] · optional
The columns a dataframe response is built to.
jsonSchema
string · optional
The JSON Schema a json response is validated against.
maxTokens
number · optional
Cap on the response length.
credentialSlotId
string · optional
The slot holding the provider key, when not using the platform's own.
Inputs
on
event
no
Implicit on every module that does not itself start a flow: wire an event here to make this module the start of what that event runs.
context
json
no
Values the prompt template interpolates; also the rows, in perRow mode.
Outputs
response
text
text, scalar, signal
What the model returned, shaped by outputMode. The port stays text whatever outputMode is, so in dataframe mode the frame it carries cannot be wired to a dataframe in-port — a known mismatch between this handler and the wiring layer, not a rule.
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