Quick Start
Get started quickly with Clarifai in a few simple steps
Clarifai provides an intuitive interface and a robust API designed to get you up and running quickly. In just a few simple steps or a few lines of code, you can bring your AI projects to life within minutes.
Try Out Our Community Models
We offer a diverse collection of Community models that you can browse, test, and integrate into your projects.
Step 1: Find a Model
You can easily find a model to use by heading to the homepage and exploring the Trending AI models section, which showcases popular and ready-to-use options.
After finding the model, click the TEST IN PLAYGROUND button in the bottom left corner of its information card.
For this example, we'll use the Llama-3.2-3B-Instruct model.
Alternatively, you can select the Playground option in the top navigation bar.
Step 2: Run Your Inference in Playground
You'll be taken to the AI Playground, which is a testing battleground that allows you to quickly interact with powerful AI models without additional setup.
In the chat interface at the bottom of the Playground, enter your desired prompt to generate text with the selected model. Note that if the model supports image or video inputs as prompts, you can also upload them directly into the interface.
Alternatively, in the upper-left section of the Playground, you can choose the model you'd like to use for inference.
Then, click the arrow icon to submit your request.
The results will be streamed directly in the interface, allowing you to see the output in real time. Note that since we support streaming capabilities, you can interact with language models as they generate responses token by token — just like in a live chat experience.
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For this example, we're using the default settings for deployment (
Clarifai Shared), inference parameters, and others. You can customize these settings as needed for more advanced use cases. -
You can toggle the button in the upper-left section of the Playground to display ready-to-use API code snippets in various programming languages. Simply copy and use them in your project.
Call Your First Model With Our API
You can get started quickly by using the Clarifai Python SDK to make your first API call.
Step 1: Get a PAT Key
You need a PAT (Personal Access Token) key to authenticate your connection to the Clarifai platform. You can generate the PAT key in your personal settings page by navigating to the Security section.
Step 2: Install Python SDK
Install the latest version of the Clarifai Python SDK package.
- Python SDK
pip install --upgrade clarifai
On Windows, the Clarifai Python SDK expects a HOME environment variable, which isn’t set by default. To ensure compatibility with file paths used by the SDK, set HOME to the value of your USERPROFILE. You can set it in your Command Prompt this way: set HOME=%USERPROFILE%.
Step 3: Send an API Request
For this example, let's use the Qwen3 model to generate text based on a given prompt.
- Python SDK
- Node.js SDK
import os
from clarifai.client import Model
# Set your Personal Access Token (PAT)
os.environ["CLARIFAI_PAT"] = "YOUR_PAT_HERE"
# Initialize with model URL
model = Model(url="https://clarifai.com/qwen/qwenLM/models/Qwen3-30B-A3B-GGUF")
response = model.predict(prompt="What is the future of AI?")
print(response)
import { Model } from "clarifai-nodejs";
const model = new Model({
url: "https://clarifai.com/qwen/qwenLM/models/Qwen3-30B-A3B-GGUF",
authConfig: {
pat: process.env.CLARIFAI_PAT,
},
});
const response = await model.predict({
// see available methodNames using model.availableMethods()
methodName: "predict",
prompt: "What is the future of AI?",
});
console.log(JSON.stringify(response));
// get response data from the response object
Model.getOutputDataFromModelResponse(response);
Output Example
<think>
Okay, so I need to figure out the future of AI. Let me start by recalling what I know about AI. AI has been around for a while, but recently there's been a lot of advancements, especially in machine learning and deep learning. I've heard terms like neural networks, big data, and algorithms. But what's next?
First, maybe I should think about current trends. AI is already used in many areas like healthcare, finance, autonomous vehicles, and even in everyday things like voice assistants. But where is it headed? I remember reading about AI becoming more integrated into daily life. Maybe it will become more personalized? Like, AI that adapts to individual users better.
Then there's the question of ethics and regulation. As AI becomes more powerful, there are concerns about bias, privacy, and job displacement. I think governments and organizations are starting to create regulations. But how will that shape the future? Maybe more transparency and accountability in AI systems?
Another point is the advancement in AI capabilities. Current AI is good at specific tasks, but general AI (AGI) is still a long way off. AGI would be able to handle any intellectual task a human can. But is that even possible? Some experts think it's a distant future, while others are more optimistic. What about AI surpassing human intelligence? That's the concept of the singularity. But is that realistic?
Also, the impact on jobs. AI might automate many jobs, leading to some job losses but also creating new ones. How will the economy adapt? Maybe there's a need for reskilling and education. But how does that affect different industries?
Then there's the technical side. Improvements in natural language processing, computer vision, and other areas. Maybe AI will become more efficient, requiring less data and computation. Quantum computing could play a role here, right? If quantum computers become more mainstream, they might revolutionize AI by solving complex problems faster.
Collaboration between humans and AI is another aspect. AI as a tool to augment human capabilities, not replace them. For example, in medicine, AI could help doctors diagnose diseases more accurately. In creative fields, AI might assist artists or writers.
But there are also risks. Malicious use of AI, like deepfakes or autonomous weapons. How can we prevent that? International cooperation might be necessary. Also, the environmental impact of training large AI models, which consume a lot of energy. Sustainable practices could be a focus in the future.
I should also consider the societal implications. AI could help solve global challenges like climate change, by optimizing energy use or predicting natural disasters. But there's also the risk of increased inequality if AI benefits only certain groups or countries.
Another thought: the development of AI in different regions. Some countries might lead in AI research, while others lag behind. This could affect global power dynamics. Also, the role of open-source AI versus proprietary systems. Open-source might promote innovation but could also have security issues.
I need to make sure I cover different aspects: technological, ethical, economic, social, and geopolitical. Maybe structure the answer into sections. But I should avoid making it too technical. Also, check if there are any recent developments or predictions from experts that I should mention.
Wait, I should verify some points. For example, is AGI really a distant goal? Some companies are investing heavily in it, but there's no consensus. Also, the timeline for AI becoming more integrated into society. Maybe in the next decade, we'll see more AI in education, healthcare, etc.
Another angle: AI in education. Personalized learning, adaptive tutoring systems. That could revolutionize how people learn. But also, issues like access to technology and the digital divide.
In the legal field, AI could assist in legal research, predict case outcomes, but there's the question of bias in algorithms. How to ensure fairness?
In terms of challenges, there's the problem of explainability. Many AI models, especially deep learning, are "black boxes." Future AI might need to be more transparent so that decisions can be understood and trusted.
I think that's a good start. Now, organize these thoughts into coherent points, making sure to address different areas and provide a balanced view, acknowledging both the potential benefits and the challenges.
</think>
The future of AI is a multifaceted and rapidly evolving landscape, shaped by technological advancements, ethical considerations, economic shifts, and societal needs. Here's a structured overview of key trends, challenges, and possibilities:
### **1. Technological Advancements**
- **General AI (AGI) and Beyond**: While current AI excels at specific tasks (narrow AI), achieving **Artificial General Intelligence (AGI)** —systems capable of understanding or learning any intellectual task a human can—remains a distant goal. Experts debate timelines, with some predicting AGI by 2050, while others remain skeptical. Superintelligent AI (stronger than humans) is speculative but raises critical questions about control and alignment.
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Click here to learn more about how to make inference requests using our API. You'll discover how to list all the available inference methods defined in a model's configuration, generate example code, leverage our Compute Orchestration capabilities for various types of inference requests, and more.
Congratulations — you've just get started with the Clarifai platform!