About Grok 4
Grok 4 is a cutting-edge AI service designed to boost business productivity by providing precise strategic planning, troubleshooting, and research capabilities. It leverages a multi-agent system and advanced reasoning to deliver fast, accurate, and contextually relevant outputs, including step-by-step problem-solving and real-time web and social media data integration. Businesses benefit from its ability to analyze market trends, customer feedback, and competitive landscapes quickly, enabling informed decision-making and prioritization. The platform supports voice interaction and visual scene analysis, facilitating hands-free and context-aware assistance. With enterprise-grade security and compliance, Grok 4 is suitable for large-scale deployment in diverse business environments seeking to automate complex cognitive tasks.
AI Agent Use Cases
• Autonomous AI agents can utilize Grok 4 to perform real-time market research by querying live data from social media and the web, delivering up-to-date competitor and trend analysis for business strategy. They can automate customer feedback processing by categorizing themes, scoring satisfaction metrics, and generating prioritized product roadmaps to enhance product management workflows. Additionally, AI agents can leverage Grok 4's multimodal capabilities to conduct voice-driven interactive troubleshooting and strategic planning sessions, enabling businesses to streamline decision-making and operational efficiency.
Available Actions
These are the specific actions that AI agents can perform with this tool
Extract Invoice Details As Structured Json
5 inputs
Extracts structured invoice data from unstructured invoice text and returns it in a predefined JSON schema.
api_key
API key used for authentication, must be included as 'Authorization: Bearer <api_key>' in the request headers.
model
The model used for invoice extraction, must be set to a supported model for structured outputs.
system_prompt
A prompt that instructs the model to extract invoice data, e.g., 'Given a raw invoice, carefully analyze the text and extract the relevant invoice data into JSON format.'
invoice_text
The raw, unstructured text content of an invoice to be parsed (can include multiple lines, must include all relevant invoice info).
invoice_schema
The schema to define what fields and structure should be returned in the JSON output; must comply with the structured output requirements.
Generate Chat Conversation Reply
6 inputs
Creates a conversational response from chat (text or image) prompts using a selected AI model.
model
ID of the model to use for the chat completion. Must be a valid model available to your API key (e.g., 'grok-4').
messages
Conversation messages as a list of objects. Each message must include a 'role' ('system', 'user', etc.) and 'content' (string for text or relevant info for images). Must provide enough context for the model to generate a response.
reasoning_effort
Configures the model's reasoning effort. Optional, typical values like 'low', 'medium', or 'high' may influence response quality vs speed.
n
Number of response choices to generate and return. If omitted, defaults to 1. Must be a positive integer.
max_tokens
Maximum number of tokens to generate in the completion. If omitted, model default is used.
temperature
Sampling temperature to use. Higher values (e.g., 1.0) produce more diverse outputs, lower values (e.g., 0.1) are more deterministic. Optional.
Recognize Image Content
1 input
Analyzes the contents of an image and returns detected objects, text, or scene information.
image
The image to be analyzed. This must be provided as a binary file upload, such as a JPEG or PNG file, for the API to detect content within it.
Search With Live Data And Citations
3 inputs
Performs a chat completion query with live real-time search from multiple sources, optionally filtered, and returns a response with citations to data sources.
model
The model name to use for chat completion; required, must be set to a supported model with live search capability.
messages
An ordered list of chat message objects, with at least one user message; determines prompt and conversation history.
search_parameters
Configuration object for live search; must include at least the 'mode' field to activate search. All other fields are optional.
Send Tool Function Results To Model For Response
1 input
Sends the return values of tool functions back to the language model to obtain a final message response.
messages
Message history, including user, assistant, and tool messages, where each tool message should contain the tool function's result and the tool_call_id as required by the model.