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What is OpenAI Decisions API?

The Decisions API is engineered to convert text and images into structured decisions that can be utilized by applications, boasting a processing speed approximately ten times faster than the Responses API. To use it effectively, developers are required to submit a model along with shared input evidence and one or more questions that define the evaluation parameters, after which the API provides organized responses that are ideal for various tasks such as content classification, request routing, prioritizing work, or making decisions based on established thresholds. It supports three types of inquiries: predicate questions, which determine the truth of a condition and yield a probability between 0 and 1; choice questions, which select a single option from a specified set while offering corresponding probabilities and confidence levels; and score questions, which evaluate an input against a series of ordered rubric levels, resulting in a probability-weighted score. The API's flexibility allows it to handle inputs as simple text or as user messages that incorporate both text and images, making it suitable for a wide array of scenarios including detecting visible product damage, interpreting request intent, classifying various document types, assessing the severity of issues, or gauging answer relevance. By enabling this level of processing, the system significantly enhances the ability of developers to build applications that are not only more responsive but also smarter, ultimately catering better to the needs of users. Furthermore, this advanced capability means that applications can adapt to changing user requirements in real-time, further increasing their effectiveness.

What is ModelScope?

This advanced system employs a complex multi-stage diffusion model to translate English text descriptions into corresponding video outputs. It consists of three interlinked sub-networks: the first extracts features from the text, the second translates these features into a latent space for video, and the third transforms this latent representation into a final visual video format. With around 1.7 billion parameters, the model leverages the Unet3D architecture to facilitate effective video generation through a process of iterative denoising that starts with pure Gaussian noise. This cutting-edge methodology enables the production of engaging video sequences that faithfully embody the stories outlined in the input descriptions, showcasing the model's ability to capture intricate details and maintain narrative coherence throughout the video. Furthermore, this system opens new avenues for creative expression and storytelling in digital media.

Media

Media

Integrations Supported

OpenAI

Integrations Supported

01.AI
CodeQwen
GLM-4.5
Qwen
Qwen-7B
Qwen-Image
Qwen2.5
Qwen2.5-Coder
Qwen3.6-27B
Qwen3.6-35B-A3B
Qwen3.6-Max-Preview
Qwen3.7-Max
Qwen3.8-2.4T-A95B
Qwen3.8-27B
Qwen3.8-Max
Qwen3.8-Omni-Flash
Step 3.5 Flash
Step 5 Preview
Yi-Large

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

developers.openai.com/api/docs/guides/decisions

Company Facts

Organization Name

Alibaba Cloud

Company Location

China

Company Website

modelscope.cn/

Categories and Features

AI Decision Models

Not specified

Categories and Features

AI Gateways

Not specified

AI Inference

Not specified

AI Tools

Not specified

AI Video Generators

Not specified

ML Model Deployment

Not specified

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