ActionHugging FaceUpdated June 2026

How do I run chat completion on Hugging Face?

Short answer: Drop the "Hugging FaceHugging Face Chat Completion" action anywhere in your workflow, map the inputs from upstream nodes, and publish.

Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

FieldTypeRequiredDescription
Model
model
optionsRequiredWhich model to use
User Message
message
stringRequiredUser message to send to the model
System Prompt
system_prompt
stringOptionalOptional system instructions that shape the model's behavior
Temperature
temperature
stringOptionalSampling temperature (0–2). Higher = more random.
Max Tokens
max_tokens
stringOptionalMaximum tokens to generate in the response
Top P
top_p
stringOptionalNucleus sampling threshold (0–1)
Sample request
{
"model": "{{trigger.model}}",
"message": "e.g. Summarize this article in 3 bullets",
"system_prompt": "e.g. You are a helpful assistant.",
"temperature": "0.7",
"max_tokens": "1024"
}
Returns
{
"id": "chatcmpl-abc123",
"model": "meta-llama/Llama-3.3-70B-Instruct",
"usage": {
"total_tokens": 60,
"prompt_tokens": 10,
"completion_tokens": 50
},
"choices": [
{
"message": {
"role": "assistant",
"content": "Sample response"
},
"finish_reason": "stop"
}
]
}

Use these fields in downstream nodes for routing, logging, or error handling.

Triggered by

Apps that pair well as the trigger for Hugging Face Chat Completion.

Any of these apps can fire this action as part of a workflow.

FAQ

Questions about Hugging Face Chat Completion.

What does the Hugging Face Chat Completion action do in Hugging Face?
Runs chat completion against any text-generation model on Hugging Face Hub that supports the TGI server. OpenAI-compatible message-array shape. Model selection via model ID (e.g., meta-llama/Llama-3.3-70B-Instruct).
What inputs does Hugging Face Chat Completion require?
Required: Model, User Message. Every input accepts a static value or a variable from any upstream node in your workflow.
Can I use dynamic inputs from earlier workflow nodes?
Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.
What happens if Hugging Face returns an error?
The workflow pauses on the failed node, the error message is captured in the run log, and you can retry the run with one click. Auto-retry policies are configurable per workflow with exponential backoff up to 5 attempts.
Does Hugging Face Chat Completion support batch operations?
Yes. Run Hugging Face Chat Completion inside a Loop node to process arrays. Tiny Command handles Hugging Face's rate limits automatically so you don't have to throttle manually.
More actions

Other Hugging Face actions.

Action
HF Feature Extraction (Embeddings)
Generates sentence embeddings from any sentence-transformers or BGE-class model on the HF Hub. For RAG-pipeline vector generation when you want a specific HF-hosted embedding model.
Action
HF Text Classification
Runs any classifier model from HF Hub on text input — sentiment, toxicity, NER, intent. Pick the right classifier for your use case from the broad Hub catalog.
Action
HF Text to Image
Generates images from text using any HF-hosted image model (SDXL, SD3.5, Flux variants, community fine-tunes). For accessing niche or specific image models from the broad HF catalog.

Send hugging face chat completion from your workflows.

Triggered by anything in the catalog. Free tier available. No credit card.