Groq | Documentation

The Groq component is an AI component that allows users to connect the AI models served on GroqCloud. It can carry out the following tasks:

Text Generation Chat

#Release Stage

Alpha

#Configuration

The component definition and tasks are defined in the definition.json and tasks.json files respectively.

#Setup

In order to communicate with Groq, the following connection details need to be provided. You may specify them directly in a pipeline recipe as key-value pairs within the component's setup block, or you can create a Connection from the Integration Settings page and reference the whole setup as setup: ${connection.<my-connection-id>}.

Field	Field ID	Type	Note
API Key	`api-key`	string	Fill in your GroqCloud API key. To find your keys, visit the GroqCloud API Keys page.

#Supported Tasks

#Text Generation Chat

Groq serves open source text generation models (often called generative pre-trained transformers or large language models) have been trained to understand natural language, code, and images. The models provide text outputs in response to their inputs. The inputs to these models are also referred to as "prompts". Designing a prompt is essentially how you “program” a large language model model, usually by providing instructions or some examples of how to successfully complete a task.

Input	ID	Type	Description
Task ID (required)	`task`	string	`TASK_TEXT_GENERATION_CHAT`
Model (required)	`model`	string	The OSS model to be used.
Prompt (required)	`prompt`	string	The prompt text.
System Message	`system-message`	string	The system message helps set the behavior of the assistant. For example, you can modify the personality of the assistant or provide specific instructions about how it should behave throughout the conversation. By default, the model’s behavior is set using a generic message as "You are a helpful assistant.".
Prompt Images	`prompt-images`	array[string]	The prompt images (Note: Only a subset of OSS models support image inputs).
Chat History	`chat-history`	array[object]	Incorporate external chat history, specifically previous messages within the conversation. Please note that System Message will be ignored and will not have any effect when this field is populated. Each message should adhere to the format: : {"role": "The message role, i.e. 'system', 'user' or 'assistant'", "content": "message content"}.
Seed	`seed`	integer	The seed.
Temperature	`temperature`	number	The temperature for sampling.
Top K	`top-k`	integer	Integer to define the top tokens considered within the sample operation to create new text.
Max New Tokens	`max-new-tokens`	integer	The maximum number of tokens for model to generate.
Top P	`top-p`	number	Float to define the tokens that are within the sample operation of text generation. Add tokens in the sample for more probable to least probable until the sum of the probabilities is greater than top-p (default=0.5).
User	`user`	string	The user name passed to GroqPlatform.

Input Objects in Text Generation Chat

Chat History

Incorporate external chat history, specifically previous messages within the conversation. Please note that System Message will be ignored and will not have any effect when this field is populated. Each message should adhere to the format: : {"role": "The message role, i.e. 'system', 'user' or 'assistant'", "content": "message content"}.

Field	Field ID	Type	Note
Content	`content`	array	The message content.
Role	`role`	string	The message role, i.e. 'system', 'user' or 'assistant'.

Content

The message content.

Field	Field ID	Type	Note
Image URL	`image-url`	object	The image URL.
Text	`text`	string	The text content.
Type	`type`	string	The type of the content part. Enum values `text` `image_url`

Image URL

The image URL.

Field	Field ID	Type	Note
URL	`url`	string	Either a URL of the image or the base64 encoded image data.

Output	ID	Type	Description
Text	`text`	string	Model Output.
Usage (optional)	`usage`	object	Token usage on the GroqCloud platform text generation models.

Output Objects in Text Generation Chat

Usage

Field	Field ID	Type	Note
Input Tokens	`input-tokens`	number	The input tokens used by GroqCloud OSS models.
Output Tokens	`output-tokens`	number	The output tokens generated by GroqCloud OSS models.

#Example Recipes

Recipe for the Groq Interview Helper pipeline.

version: v1beta
component:
  groq-0:
    type: groq
    task: TASK_TEXT_GENERATION_CHAT
    input:
      max-new-tokens: 300
      model: llama3-groq-70b-8192-tool-use-preview
      prompt: |-
        Rewrite this experience using the STAR (Situation, Task, Action, Result) method for a resume or CV:
        ${variable.experience}
      system-message: You are a helpful resume assistant.
      temperature: 0.05
      top-k: 10
      top-p: 0.5
      user: instill-ai
    setup:
      api-key: ${secret.INSTILL_SECRET}
variable:
  experience:
    title: experience
    description: describe your work experience
    format: string
    instill-ui-multiline: true
output:
  resume_format:
    title: resume_format
    value: ${groq-0.output.text}