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export const GLASS_EFFECTS = {
BASE_FREQUENCY: 0.008,
NUM_OCTAVES: 2,
SCALE: 77,
COLORS: {
DEFAULT_BG: "rgba(0, 0, 0, 0.25)",
SUCCESS_BG: "rgba(0, 50, 0, 0.25)",
ERROR_BG: "rgba(50, 0, 0, 0.25)",
BUTTON_BG: "rgba(59, 130, 246, 0.25)",
HIGHLIGHT: "rgba(255, 255, 255, 0.15)",
TEXT: "#ffffff",
},
} as const;
export const LAYOUT = {
MARGINS: {
DEFAULT: 20,
BOTTOM: 20,
},
DIMENSIONS: {
PROMPT_WIDTH: 420,
CAPTION_WIDTH: 150,
CAPTION_HEIGHT: 45,
},
TRANSITIONS: {
SCALE_DURATION: 200,
OPACITY_DURATION: 200,
TRANSFORM_DURATION: 400,
},
} as const;
export const TIMING = {
FRAME_CAPTURE_DELAY: 50,
VIDEO_RECOVERY_INTERVAL: 1000,
RESIZE_DEBOUNCE: 50,
SUGGESTION_DELAY: 50,
} as const;
const DEFAULT_PROMPT = "Describe what you see in one sentence.";
export const PROMPTS = {
default: DEFAULT_PROMPT,
placeholder: DEFAULT_PROMPT,
suggestions: [
DEFAULT_PROMPT,
"What is the color of my shirt?",
"Identify any text or written content visible.",
"What emotions or actions are being portrayed?",
"Name the object I am holding in my hand.",
],
fallbackCaption: "Waiting for first caption...",
processingMessage: "Starting analysis...",
} as const;
export const FASTVLM_BOXING_PROMPT =
"You are an object detection assistant. Analyze the image and respond with a JSON array of detected objects. Each object should have a 'label' (string) and 'bbox_2d' (an array of 4 integers: [x_min, y_min, x_max, y_max]). Only include objects relevant to the user's prompt. Do not include any other text besides the JSON. The JSON should be wrapped in a markdown code block like so: ```json\\n[...json_array...]\\n```";