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OATDA Vision Analysis

by @devcsde

Analyze images using vision-capable AI models through OATDA's unified API. Triggers when the user wants to analyze, describe, or understand images; extract t...

πŸ’‘ Examples

User: "Describe this image: https://example.com/photo.jpg"

export OATDA_API_KEY="${OATDA_API_KEY:-$(cat ~/.oatda/credentials.json 2>/dev/null | jq -r '.profiles[.defaultProfile].apiKey' 2>/dev/null)}" && \
curl -s -X POST "https://oatda.com/api/v1/llm/image" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OATDA_API_KEY" \
  -d '{
    "provider": "openai",
    "model": "gpt-4o",
    "contents": [
      {"type": "text", "text": "Describe this image in detail"},
      {"type": "image", "image": {"url": "https://example.com/photo.jpg", "detail": "auto"}}
    ]
  }'

πŸ“‹ Tips & Best Practices

  • Endpoint is /api/v1/llm/image β€” NOT /api/v1/llm/generate-image (that's for generation)
  • Body uses contents array format, NOT a simple prompt string
  • Only HTTPS image URLs accepted β€” no HTTP, no local paths
  • Image tokens are included in prompt token count and affect cost
  • For OCR tasks, use "detail": "high"
  • Use oatda-generate-image for creating images
  • Use oatda-list-models for available vision models
  • View on ClawHub
    TERMINAL
    clawhub install oatda-vision-analysis

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