chore: import upstream snapshot with attribution
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@@ -0,0 +1,124 @@
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import type { QuiverImageToSvgParams, QuiverSvgResponse } from '@/tools/quiver/types'
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import type { ToolConfig } from '@/tools/types'
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export const quiverImageToSvgTool: ToolConfig<QuiverImageToSvgParams, QuiverSvgResponse> = {
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id: 'quiver_image_to_svg',
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name: 'Quiver Image to SVG',
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description: 'Convert raster images into vector SVG format using QuiverAI',
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version: '1.0.0',
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params: {
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apiKey: {
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type: 'string',
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required: true,
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visibility: 'user-only',
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description: 'QuiverAI API key',
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},
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model: {
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type: 'string',
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required: true,
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visibility: 'user-only',
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description: 'The model to use for vectorization (e.g., "arrow-preview")',
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},
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image: {
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type: 'file',
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required: true,
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visibility: 'user-or-llm',
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description: 'The raster image to vectorize into SVG',
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},
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temperature: {
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type: 'number',
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required: false,
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visibility: 'user-or-llm',
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description: 'Sampling temperature (0-2, default 1)',
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},
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top_p: {
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type: 'number',
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required: false,
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visibility: 'user-or-llm',
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description: 'Nucleus sampling probability (0-1, default 1)',
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},
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max_output_tokens: {
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type: 'number',
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required: false,
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visibility: 'user-or-llm',
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description: 'Maximum output tokens (1-131072)',
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},
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presence_penalty: {
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type: 'number',
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required: false,
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visibility: 'user-or-llm',
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description: 'Token penalty for prior output (-2 to 2, default 0)',
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},
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auto_crop: {
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type: 'boolean',
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required: false,
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visibility: 'user-or-llm',
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description: 'Automatically crop the image before vectorizing',
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},
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target_size: {
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type: 'number',
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required: false,
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visibility: 'user-or-llm',
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description: 'Square resize target in pixels (128-4096)',
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},
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},
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request: {
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url: '/api/tools/quiver/image-to-svg',
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method: 'POST',
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headers: () => ({ 'Content-Type': 'application/json' }),
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body: (params) => ({
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apiKey: params.apiKey,
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model: params.model,
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image: params.image,
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temperature: params.temperature,
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top_p: params.top_p,
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max_output_tokens: params.max_output_tokens,
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presence_penalty: params.presence_penalty,
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auto_crop: params.auto_crop,
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target_size: params.target_size,
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}),
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},
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transformResponse: async (response) => {
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const data = await response.json()
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if (!data.success) {
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throw new Error(data.error || 'Failed to vectorize image')
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}
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return data
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},
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outputs: {
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success: { type: 'boolean', description: 'Whether the vectorization succeeded' },
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output: {
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type: 'object',
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description: 'Vectorized SVG output',
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properties: {
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file: {
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type: 'file',
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description: 'Generated SVG file',
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},
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svgContent: {
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type: 'string',
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description: 'Raw SVG markup content',
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},
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id: {
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type: 'string',
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description: 'Vectorization request ID',
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},
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usage: {
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type: 'json',
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description: 'Token usage statistics',
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properties: {
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totalTokens: { type: 'number', description: 'Total tokens used' },
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inputTokens: { type: 'number', description: 'Input tokens used' },
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outputTokens: { type: 'number', description: 'Output tokens used' },
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},
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},
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},
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},
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},
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}
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