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98323e7910
### What problem does this PR solve? Package refactor and PDF post process. ### Type of change - [x] Refactoring --------- Co-authored-by: Claude <noreply@anthropic.com>
99 lines
3.2 KiB
Go
99 lines
3.2 KiB
Go
package post
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import (
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"context"
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"errors"
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"image"
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)
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// ImageDescriber describes an image using a vision language model.
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type ImageDescriber interface {
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DescribeImage(ctx context.Context, img image.Image, prompt string) (string, error)
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}
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// maxDescribeConcurrency limits how many concurrent VLM calls are in flight.
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const maxDescribeConcurrency = 10
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// minImageSide is the minimum width or height (in pixels) for an image
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// to be sent to a VLM. Tiny crops fail provider image-size limits.
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const minImageSide = 11
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// describePrompt is the default prompt for image/table description.
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// Python: vision_llm_figure_describe_prompt.md
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const describePrompt = `## ROLE
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You are an expert visual data analyst.
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## GOAL
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Analyze the image and produce a textual representation strictly based on what is visible in the image.
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## DECISION RULE (CRITICAL)
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First, determine whether the image contains an explicit visual data representation with enumerable data units forming a coherent dataset.
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## OUTPUT RULES (STRICT)
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- Produce output in exactly one of the two modes defined below.
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- Do NOT mention, label, or reference the modes in the output.
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- Do NOT combine content from both modes.
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- Do NOT explain or justify the choice of mode.
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- Do NOT add any headings, titles, or commentary beyond what the mode requires.
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---
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## MODE 1: STRUCTURED VISUAL DATA OUTPUT
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(Use only if the image contains enumerable data units forming a coherent dataset.)
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Output only the following fields, in list form:
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- Visual Type:
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- Title:
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- Axes / Legends / Labels:
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- Data Points:
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- Captions / Annotations:
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---
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## MODE 2: GENERAL FIGURE CONTENT
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(Use only if the image does NOT contain enumerable data units.)
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Write the content directly, starting from the first sentence.
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Do NOT add any introductory labels, titles, headings, or prefixes.
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Requirements:
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- Describe visible regions and components in a stable order (e.g., top-to-bottom, left-to-right).
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- Explicitly name interface elements or visual objects exactly as they appear.
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- Transcribe all visible text verbatim; do not paraphrase, summarize, or reinterpret labels.
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- Describe spatial grouping, containment, and alignment of elements.
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- Do NOT interpret intent, behavior, workflows, gameplay rules, or processes.
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- Avoid narrative or stylistic language unless it is a dominant and functional visual element.
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Use concise, information-dense sentences.
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Do not use bullet lists or structured fields in this mode.`
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// DescribeImage calls the VLM to produce a natural-language description of
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// the given image. Returns the description text or an error.
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//
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// Images smaller than minImageSide in either dimension are silently skipped
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// (returning an empty string and no error), matching Python's behavior.
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func DescribeImage(ctx context.Context, img image.Image, prompt string, client ImageDescriber) (string, error) {
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if img == nil {
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return "", errors.New("DescribeImage: nil image")
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}
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b := img.Bounds()
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if b.Dx() == 0 || b.Dy() == 0 {
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return "", errors.New("DescribeImage: empty image (0x0)")
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}
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if b.Dx() < minImageSide || b.Dy() < minImageSide {
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return "", nil // skip tiny crops, Python compatible
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}
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if err := ctx.Err(); err != nil {
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return "", err
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}
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return client.DescribeImage(ctx, img, prompt)
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}
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