EmpirioLabs

tip

If you installed lfx directly (not as part of langflow), install the EmpirioLabs bundle separately:

1. Run uv pip install lfx-empiriolabs.
2. Restart Langflow.
3. To confirm the bundle loaded, run lfx extension list.

If you installed Langflow with uv pip install langflow, these bundle components are already included.

For more information, see Install LFX with bundle components.

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

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

For more information about EmpirioLabs features and functionality used by EmpirioLabs components, see the EmpirioLabs documentation.

EmpirioLabs AI text generation

This component generates text using EmpirioLabs' language models through the EmpirioLabs OpenAI-compatible endpoints.

It can output either a Model Response (Message) or a Language Model (LanguageModel).

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

For more information, see Language model components.

EmpirioLabs AI parameters

Some parameters are hidden by default in the visual editor. You can modify all component parameters through the component inspection panel that appears when you select a component.

Name	Type	Description
api_key	SecretString	Input parameter. Your EmpirioLabs API Key for authentication.
model_name	String	Input parameter. The id of the EmpirioLabs model to use. The component automatically fetches the latest available models from EmpirioLabs when you provide a valid API key. For information about supported models, see the EmpirioLabs documentation.
input_value	String	Input parameter. The input text to send to the model.
system_message	String	Input parameter. A system message that helps set the behavior of the assistant.
max_tokens	Integer	Input parameter. The maximum number of tokens to generate. Set to 0 for unlimited tokens.
temperature	Float	Input parameter. Controls randomness in the output. Range: [0.0, 1.0]. Default: 0.1.
seed	Integer	Input parameter. The seed controls the reproducibility of the job.
model_kwargs	Dict	Input parameter. Additional keyword arguments to pass to the model.
json_mode	Boolean	Input parameter. If True, it will output JSON regardless of passing a schema.
stream	Boolean	Input parameter. Whether to stream the response. Default: false.
model	LanguageModel	Output parameter. An instance of ChatOpenAI configured with EmpirioLabs parameters.

EmpirioLabs AI image generation

This component generates an image from a text prompt using EmpirioLabs' image models (such as Seedream, Qwen-Image, FLUX, Nova Canvas, and HunyuanImage) through the EmpirioLabs OpenAI-compatible Images endpoint.

It outputs the API response as Data, including the generated image URL (or base64 content) when available.

EmpirioLabs AI image generation parameters

Name	Type	Description
api_key	SecretString	Input parameter. Your EmpirioLabs API Key for authentication.
prompt	String	Input parameter. The text prompt to generate the image from.
model_name	String	Input parameter. The EmpirioLabs image model to use for generation. The component automatically fetches the latest available image models from EmpirioLabs when you provide a valid API key.
aspect_ratio	String	Input parameter. The aspect ratio of the generated image. Used when the selected model supports it.
size	String	Input parameter. Optional explicit pixel size such as 1024x1024. Takes priority over aspect ratio when the selected model supports an explicit size.
n	Integer	Input parameter. The number of images to generate.
seed	Integer	Input parameter. Makes generation deterministic. Used when the selected model supports it.
negative_prompt	String	Input parameter. The text prompt describing what to avoid in the generated image. Used when the selected model supports it.
image_generation_results	Data	Output parameter. The EmpirioLabs API response, including the generated image URL or base64 content.

Use EmpirioLabs in a flow

1. Sign up for an EmpirioLabs account.

2. Obtain your API key from the EmpirioLabs dashboard.

3. In Langflow, add the EmpirioLabs component to your flow.

4. Enter your API key in the EmpirioLabs API Key field.

5. Select your preferred model from the Model Name menu.

6. Configure other parameters as needed for your use case.

7. Add other components to your flow as needed.

   To perform a basic test, add Chat Input and Chat Output components to your flow, connect them to the EmpirioLabs component accordingly, and then click Playground to test the connection and chat with your model.

   For more advanced use cases, you can connect the EmpirioLabs component to other components like Prompt Template, Agent, or Smart Transform components.