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Documentation Index

Fetch the complete documentation index at: https://docs.perceptron.inc/llms.txt

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Isaac 0.1 is supported for existing integrations. New projects should use Isaac 0.2 or Perceptron Mk1.
Isaac 0.1 is the first generation of Perceptron’s open-weights image-based vision-language family. Ask questions about images, detect objects, read text, get captions — through the hosted API or by self-hosting the open weights on Hugging Face.

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Try Isaac 0.1 in 30 seconds

Create an API key

Get your key from the Perceptron platform

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Get started with Image

Step through this example interactively
Or pick your preferred method: 
curl -X POST "https://api.perceptron.inc/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $PERCEPTRON_API_KEY" \
  -d '{
  "model": "isaac-0.1",
  "messages": [
    {
      "role": "user",
      "content": [
        {"type": "image_url", "image_url": {"url": "https://raw.githubusercontent.com/perceptron-ai-inc/perceptron/main/cookbook/_shared/assets/capabilities/qna/studio_scene.webp"}},
        {"type": "text", "text": "What stands out in this scene?"}
      ]
    }
  ]
}'
Using Python? Install with pip install perceptron or pip install openai. Isaac 0.1 does not support reasoning; the SDK silently drops reasoning=True and warns. To trigger grounding via raw chat completions, use <hint>BOX</hint> or <hint>POINT</hint> as a system-role message.
Supported image formats: JPEG, PNG, WebP — pass a URL or local file path. Outputs are deterministic by default (temperature defaults to 0.0). See API Reference for all parameters.

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Explore Isaac 0.1 capabilities

Image Q&A

Ask questions about images and get grounded answers

Object Detection

Locate targets with precise bounding boxes

OCR

Extract text from images and documents

Image Captioning

Generate descriptions of images

In-Context Learning

Adapt Isaac 0.1 to image tasks with a handful of examples

Structured Outputs

Constrain replies to Pydantic, JSON schemas, or regex