LLM Tools API Endpoint

• API Endpoint Access URL
• Description
• HTTP Methods
• HTTP Parameters
• HTTP Response
• Code Samples
• Similar API Endpoints

API Endpoint Access URL

https://llm.pixlab.io/llmtools

Description

The PixLab Tool Listing API provides a robust and production-grade implementation of the OpenAI Function Calling Specification ↗, allowing large language models (LLMs) to seamlessly invoke external tools and services in a structured, schema-driven format. This capability empowers developers to integrate LLMs into real-world workflows by bridging model predictions with actionable operations, such as document parsing, image analysis, image editing data scraping, GitHub interactions, and much more. Each tool is defined as a callable function with a machine-readable JSON schema, including fields like name, description, parameters, and expected output. These schemas are automatically compatible with any OpenAI-based or OpenAI-compatible model, including DeepSeek, Claude, Mistral, Gemini, Qwen, Gemma, and others deployed via frameworks such as OpenRouter, DeepInfra, or your own custom inference pipelines.

A Tool is a discrete, callable unit of logic such as “transcribe audio,” “remove image background,” or “query arXiv.” that can executed immediately once you pass them verbatim (as returned by your large language model) to the LLM-TOOL-CALL REST-API endpoint. Tools are grouped into Toolkits, which are collections of related functionality serving a focused purpose (e.g., file operations, media processing, spreadsheet parsing, terminal commands, etc.). This structure improves modularity, discoverability, and fine-grained control for LLM-based agents. Tools are defined in a way that supports runtime invocation with JSON-serialized arguments and structured JSON output, fully aligned with OpenAI's function call protocol. This enables easy chaining, programmatic orchestration, and interaction with external APIs or systems without sacrificing safety or transparency.

Developers integrating with PixLab's Vision Platform can register or consume pre-built toolkits that expose dozens of callable tools. These are particularly well-suited for automating workflows in domains like computer vision, media processing, document understanding, knowledge retrieval, and human-AI collaboration. For example, the ImageAnalysisToolkit integrates tightly with PixLab's vision endpoints, enabling AI agents to answer questions about images, detect objects, OCR text, or identify faces. The BrowserToolkit lets models simulate browser navigation and extract live web content, while the CodeExecutionToolkit allows LLMs to safely run Python or Jupyter cells in isolated sandboxes.

Every tool and toolkit provided by PixLab is versioned, documented, and exposed via a consistent schema that you can query directly from the API or import into your LLM runtime. Whether you're building autonomous agents, data processing pipelines, developer copilots, or interactive chat interfaces, PixLab's Tool Call API provides the necessary building blocks to connect your models with real-world functionality; reliably, securely, and at scale.

Below is a categorized listing of all built-in toolkits currently available through the PixLab Tool Call API. These are fully compatible with OpenAI's tool calling specification and are ready to be integrated into any LLM-supported application or agent runtime.

For image analysis, we recommend leveraging the PixLab APIs, such as the QUERY, TAG-IMG and DESCRIBE API endpoints, in addition to the comprehensive suite of Vision Language Models API endpoints.

HTTP Methods

GET

HTTP Parameters

HTTP Response

application/json

An array or list with an OpenAI compatible tool call format of the PixLab Tools listed above.

LLM Tools Response Example

// List of tools returned by the llm-tools API endpoint
[{...
    "type": "function",
    "name": "analyze_image",
    "description": "Analyze image content, and respond to user query.",
    "parameters": {
        "type": "object",
        "properties": {
            "image": {
                "type": "URL",
                "description": "Input Image URL or Base64 Image Body Encoding"
            }
        },
        "required": [
            "image"
        ],
        "additionalProperties": False
      }
}]

Code Samples

# For a comprehensive list of production-ready code samples, please consult the PixLab Github Repository: https://github.com/symisc/pixlab.

// For a comprehensive list of production-ready code samples, please consult the PixLab Github Repository: https://github.com/symisc/pixlab.

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# For a comprehensive list of production-ready code samples, please consult the PixLab Github Repository: https://github.com/symisc/pixlab.