Getting Started with AI Agents API

Beta Notice: This project is in rapid development and may not be stable for production use.

AI Agents in IO Intelligence are specialized assistants designed to handle a variety of tasks, from reasoning and summarization to sentiment analysis and translation. These agents leverage advanced AI capabilities to automate complex workflows, enhance decision-making, and streamline information processing. Each AI Agent is tailored for a specific function — whether it is extracting key information, classifying data, moderating content, or translating languages. By integrating these agents into your applications, you can harness powerful AI-driven automation with ease.

Important Note on Usage Limits

Each model within IO Intelligence has its own value and credit consumption rate based on its complexity, capability, and computational cost. For plan subscribers (Basic, Professional, or higher tiers), all model interactions draw from a shared usage pool. This means you can use any model available under your plan, and your total usage will count toward a single shared credit allowance — rather than having separate limits for each model. This shared system provides maximum flexibility, allowing you to switch between models seamlessly while staying within your daily or hourly quota. This limit is designed to ensure fair and balanced usage for all users. If you anticipate needing a higher request limit, please consider optimizing your implementation or reach out to us for assistance. For further details on usage limits, full breakdown of rates, and how IO Credits are billed, refer to the IO Intelligence Payments page.

Introduction

You can interact with the API using HTTP requests from any programming language or by using the official Python. To install the official Python library, run the following command:

pip install iointel

Example: Using the AI Agents API in Python

The following is an example of how you can use the iointel Python library to interact with the IO Intelligence APIs:

from iointel import (
    Agent,
    Workflow
)

import os
import asyncio

api_key = os.environ["OPENAI_API_KEY"]  # Replace with your actual IO.net API key

text = """In the rapidly evolving landscape of artificial intelligence, the ability to condense vast amounts of information into concise and meaningful summaries is crucial. From research papers and business reports to legal documents and news articles, professionals across industries rely on summarization to extract key insights efficiently. Traditional summarization techniques often struggle with maintaining coherence and contextual relevance. However, advanced AI models now leverage natural language understanding to identify core ideas, eliminate redundancy, and generate human-like summaries. As organizations continue to deal with an ever-growing influx of data, the demand for intelligent summarization tools will only increase. Whether enhancing productivity, improving decision-making, or streamlining workflows, AI-powered summarization is set to become an indispensable asset in the digital age."""

agent = Agent(
    name="Summarize Agent",
    instructions="You are an assistant specialized in summarization.",
    model="meta-llama/Llama-3.3-70B-Instruct",
    api_key=api_key,
    base_url="https://api.intelligence.io.solutions/api/v1"
)

workflow = Workflow(objective=text, client_mode=False)

async def run_workflow():
    results = (await workflow.summarize_text(max_words=50,agents=[agent]).run_tasks())["results"]
    return results

results = asyncio.run(run_workflow())
print(results)

This snippet demonstrates how to configure the client, send a chat completion request using the Llama-3.3-70B-Instruct agent, and retrieve a response.

run_tasks() is now asynchronous. All usage must be wrapped inside an async function. Use asyncio.run() to execute it.

Authentication

API Keys

IO Intelligence APIs authenticate requests using API keys. You can generate API keys from the API Keys tab under IO Intelligence.

Always treat your API key as a secret. Do not share it or expose it in client-side code (e.g., browsers or mobile apps). Instead, store it securely in an environment variable or a key management service on your backend server.

Include the API key in an Authorization HTTP header for all API requests:

Authorization: Bearer \$IOINTELLIGENCE_API_KEY

Example: List Available Agents

The following is an example curl command to list all agents available in IO Intelligence:

curl https://api.intelligence.io.solutions/api/v1/agents /
  -H "Authorization: Bearer \$IOINTELLIGENCE_API_KEY" 

This request should return a response as follows:

{
  "agents": {
    "reasoning_agent": {
      "name": "Reasoning Agent",
      "description": "A logic-driven problem solver that breaks down complex scenarios into clear, step-by-step conclusions. Whether evaluating arguments, making inferences, or troubleshooting issues, this agent excels at structured thinking and insightful analysis.",
      "persona": null,
      "metadata": {
        "image_url": null,
        "tags": [
          "text"
        ]
      }
    },
    "summary_agent": {
      ...
    },
    "sentiment_analysis_agent": {
     ...
    },
    ...
  }
}

With these steps, you have successfully made your first request to the IO Intelligence Agents API. For further details on Agents, Workflows, and API Endpoints, check out the IO Intelligence Agent Framework.

IO Explorer

IO Intelligence

IO Cloud

Getting Started with AI Agents API

Important Note on Usage Limits

Introduction

Example: Using the AI Agents API in Python

Authentication

API Keys

Example: List Available Agents

​Important Note on Usage Limits

​Introduction

​Example: Using the AI Agents API in Python

​Authentication

​API Keys

​Example: List Available Agents

Important Note on Usage Limits

Introduction

Example: Using the AI Agents API in Python

Authentication

API Keys

Example: List Available Agents