Groq

tip

This provider is an extra of the lfx-bundles metapackage. It is opt-in for both Langflow and standalone LFX installs:

uv pip install "lfx-bundles[<bundle>]"

Replace <bundle> with this page's provider name, for example qdrant. For a torch-free full Langflow install, run uv pip install "langflow[bundles]". For standalone LFX with every provider in lfx-bundles, including PyTorch-based providers, run uv pip install "lfx[bundles]". See Additional bundles for the exact extra name.

Bundles contain custom components that support specific third-party integrations with Langflow.

This page describes the components that are available in the Groq bundle.

For more information, see the Groq documentation.

Groq text generation

This component generates text using Groq's language models.

It can output either a Model Response (Message) or a Language Model (LanguageModel). Specifically, the Language Model output is an instance of ChatGroq configured according to the component's parameters.

Use the Language Model output when you want to use a Groq model as the LLM for another LLM-driven component, such as an Agent or Smart Transform component.

For more information, see Language model components.

Groq text generation parameters

Name	Type	Description
groq_api_key	SecretString	Your Groq API key.
groq_api_base	String	Base URL path for API requests. Default: https://api.groq.com.
max_tokens	Integer	The maximum number of tokens to generate.
temperature	Float	Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.1.
n	Integer	Number of chat completions to generate for each prompt.
model_name	String	The name of the Groq model to use. Options are dynamically fetched from the Groq API after entering your API key and URL. To refresh your list of models, click Refresh.
tool_mode_enabled	Boolean	If enabled, the component only displays models that work with tools.