operations:
  - name: classify
    operation: ml
    config:
      model: '@cf/microsoft/resnet-50'
      input: ${input.image_url}

config:
  model: string     # Model identifier
  input: any        # Input data (image URL, text, etc.)
  options: object   # Model-specific options

operations:
  - name: classify-image
    operation: ml
    config:
      model: '@cf/microsoft/resnet-50'
      input: ${input.image_url}

operations:
  - name: detect-objects
    operation: ml
    config:
      model: '@cf/facebook/detr-resnet-50'
      input: ${input.image_url}

operations:
  - name: embed-text
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.text}

operations:
  - name: embed-image
    operation: ml
    config:
      model: '@cf/openai/clip-vit-base-patch32'
      input: ${input.image_url}

operations:
  - name: analyze-image
    operation: think
    config:
      provider: openai
      model: gpt-4o
      prompt: |
        Analyze this image and provide:
        - Main subject
        - Colors and composition
        - Mood and style
        - Any text visible

        Be detailed and specific.
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}

operations:
  - name: classify-image
    operation: think
    config:
      provider: openai
      model: gpt-4o
      temperature: 0.2
      responseFormat: json
      prompt: |
        Classify this image into one of these categories:
        - product
        - person
        - landscape
        - food
        - animal
        - other

        Return JSON: {"category": "...", "confidence": 0.0-1.0}
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}

operations:
  - name: detect-objects
    operation: think
    config:
      provider: openai
      model: gpt-4o
      responseFormat: json
      prompt: |
        List all objects visible in this image.
        Return JSON array:
        [
          {"object": "name", "location": "description", "confidence": 0.0-1.0}
        ]
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}

operations:
  - name: extract-text
    operation: think
    config:
      provider: openai
      model: gpt-4o
      temperature: 0.1
      prompt: |
        Extract all text visible in this image.
        Return the text exactly as it appears, preserving formatting.
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}

operations:
  - name: compare-images
    operation: think
    config:
      provider: openai
      model: gpt-4o
      responseFormat: json
      prompt: |
        Compare these two images and provide:
        - Similarities
        - Differences
        - Overall similarity score (0-1)

        Return JSON: {
          "similarities": ["..."],
          "differences": ["..."],
          "score": 0.0-1.0
        }
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image1_url}
            - type: image_url
              image_url:
                url: ${input.image2_url}

operations:
  - name: embed-text
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.text}

  - name: store-embedding
    operation: storage
    config:
      type: vectorize
      action: insert
      id: ${input.doc_id}
      vector: ${embed-text.output}
      metadata:
        text: ${input.text}

operations:
  - name: embed-query
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.query}

  - name: search
    operation: storage
    config:
      type: vectorize
      action: query
      vector: ${embed-query.output}
      topK: 5

# Future: Direct image classification
operations:
  - name: classify
    operation: ml
    config:
      model: '@cf/microsoft/resnet-50'
      input: ${input.image_url}
      options:
        topK: 5

# Future: Custom model inference
operations:
  - name: predict
    operation: ml
    config:
      model: 'custom:my-model'
      input: ${input.features}
      runtime: onnx

# Future: Audio transcription
operations:
  - name: transcribe
    operation: ml
    config:
      model: '@cf/openai/whisper-large-v3'
      input: ${input.audio_url}

# Future: Video understanding
operations:
  - name: analyze-video
    operation: ml
    config:
      model: '@cf/meta/video-analysis'
      input: ${input.video_url}
      options:
        frameRate: 1  # frames per second

# Good: Rich analysis with vision model
operations:
  - name: analyze
    operation: think
    config:
      model: gpt-4o
      prompt: Detailed image analysis...

# Limited: Simple classification only
operations:
  - name: classify
    operation: ml
    config:
      model: '@cf/microsoft/resnet-50'

# Good: Optimized image
operations:
  - name: analyze
    operation: think
    config:
      model: gpt-4o
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}
                detail: low  # or 'high' for more detail

operations:
  - name: embed
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.text}
    cache:
      ttl: 86400  # 24 hours
      key: embed-${input.text}

operations:
  - name: embed-batch
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.texts}  # Array of texts

ensemble: image-classification

inputs:
  image_url: string

operations:
  - name: classify
    operation: think
    config:
      provider: openai
      model: gpt-4o
      temperature: 0.2
      responseFormat: json
      prompt: |
        Classify this image:
        Categories: product, person, landscape, food, animal, vehicle, building, other
        Return: {"category": "...", "confidence": 0-1, "description": "..."}
      messages:
        - role: user
          content:
            - type: image_url
              image_url:
                url: ${input.image_url}

  - name: validate
    operation: code
    config:
      code: |
        const result = JSON.parse('${classify.output}');
        return {
          valid: result.confidence > 0.7,
          category: result.category,
          needsReview: result.confidence < 0.7
        };

outputs:
  category: ${validate.output.category}
  needsReview: ${validate.output.needsReview}

ensemble: semantic-search

inputs:
  query: string

operations:
  - name: embed-query
    operation: ml
    config:
      model: '@cf/baai/bge-base-en-v1.5'
      input: ${input.query}

  - name: search-vectors
    operation: storage
    config:
      type: vectorize
      action: query
      vector: ${embed-query.output}
      topK: 10

  - name: rerank
    operation: think
    config:
      provider: openai
      model: gpt-4o-mini
      temperature: 0.2
      prompt: |
        Query: ${input.query}

        Results:
        ${search-vectors.output.matches}

        Rerank these results by relevance to the query.
        Return top 5 as JSON array.

outputs:
  results: ${rerank.output}

operations:
  - name: analyze
    operation: think
    config:
      model: gpt-4o
      prompt: Analyze image...

operations:
  - name: analyze
    operation: ml
    config:
      model: '@cf/meta/llama-vision'
      input: ${input.image_url}