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Quickstart

Run Inference (POST) - Execute a Model
  • Endpoint: POST /models/v2/openai-community/{model}
  • Purpose: Run inference on an open-source model.
Request Body
{
  "text": "Hello, how are you?",
  "stream": false,
  "params": {
    "min_length": 10,
    "max_length": 50
  }
}
Response
{
  "output": "I am doing well, thank you!"
}

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Unified Input Formats

Bytez simplifies building with 175k+ Open Source and Closed Source AI models by standardizing inputs across 33 ML tasks. This consistency eliminates the need to adjust for varying input structures, allowing seamless integration for text, messages, image, or multiple inputs.

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Why Standardization?

  • Reduces integration complexity.
  • Enables task/provider switching without reformatting inputs.

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Input Schemas

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Text

For models that process text:
json
{
  "text": "Input text",
  "stream": false,
  "params": { "max_length": 100, "temperature": 0.7 }
}
Tasks: fill-mask, summarization, text-to-speech, translation, text-generation

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Messages

For chat, audio-text-to-text, image-text-to-text, and video-text-to-text tasks:
json
{
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    { "role": "user", "content": "What's the weather like today?" }
  ]
}
Tasks: chat, audio-text-to-text, image-text-to-text, and video-text-to-text

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Image

For image processing, use either: URL:
json
{ "url": "https://example.com/image.jpg" }
Base64:
json
{ "base64": "data:image/webp;base64,..." }
Tasks: image-classification, object-detection, image-to-Text.

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Multi-Input

For models needing both text and image or audio or video:
json
{
  "text": "What's in the image?",
  "url": "https://example.com/image.jpg"
}
Tasks: visual-question-answering, zero-shot-classification, etc. This unified schema accelerates development and ensures compatibility across diverse AI tasks.