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from __future__ import annotations
def build_parse_prompt() -> str:
return (
"You are a strict parser for neural network architecture specs. "
"Input is natural language. Return ONLY a JSON object with fields: "
"nodes: string[], edges: [fromIndex, toIndex][], constraints: object. "
"No prose."
)
def build_plan_prompt() -> str:
return (
"Given a structured NN spec (JSON), produce a concise, fillable template text "
"that preserves nodes, edges, and key constraints for diagram rendering. "
"Emphasize left-to-right flow, explicit layer counts, and unambiguous labels."
)
def build_promptgen_prompt(K: int, spec_text: str) -> str:
# Stage G1: lighter, cleaner skeleton-only prompts (no hard stylistic numbers)
return (
"Create K concise prompts for an image model to draw ONLY the skeleton of a neural network diagram (no text).\n"
"Aim for a clean paper-figure look: flat 2D, simple shapes, balanced margins, and a calm palette. Use rectangles for modules and clear left→right arrows.\n"
"If the spec implies repetition (e.g., Encoder × L), you may show a dashed grouping around the repeated blocks. Avoid flashy effects (no 3D or heavy glow).\n"
"Return ONLY a JSON array of exactly K strings; each item is one full prompt for image generation.\n"
f"K={K}.\n"
f"Spec (summary):\n{spec_text}\n"
"Each prompt must mention: 'skeleton-only, no text'."
)
def build_judge_prompt() -> str:
# Judge content & style, optimized for two-stage (skeleton→labels) flow
return (
"You are a strict publication-figure QA judge. Given a spec (JSON) and a NN diagram image, "
"evaluate (A) Content correctness and (B) Paper-style compliance.\n"
"(A) Content (0.6): required modules present; edges/arrows reflect correct order; arrows left→right; labels exist and are spelled correctly; "
"layer count L indicated when applicable. If the image has no labels, include violation EXACTLY 'HARD: labels: missing'.\n"
"(B) Style (0.4): flat 2D; white background; minimal color (black/gray + ≤2 accents); no gradients/3D/glow/shadows/neon; "
"consistent stroke width; consistent sans-serif font; adequate spacing; dashed boxes for repeated blocks; high print readability.\n"
"Return ONLY strict JSON: {score: number in [0,1], violations: string[]}. Violations must be concrete and actionable."
)
def build_image_edit_prompt(instructions: str) -> str:
# G2 and later edits: add/adjust labels only; keep geometry fixed (light constraints)
base = (
"Add or adjust labels INSIDE each block, without changing any shapes, arrows, layout, spacing, or colors. "
"Keep a clean, readable look: flat 2D, simple sans-serif font, good contrast, and consistent size across blocks. "
"Center labels within blocks; use at most two short lines; avoid covering arrows; do not add legends or titles. "
"Use each label string exactly as provided (no translation or paraphrase). "
)
return base + f"Instructions: {instructions}"
def build_image_fusion_prompt(instructions: str) -> str:
# Compose multiple images guided by text while preserving key visual constraints
return (
"Compose a new, clean technical diagram by integrating the following reference images. "
"Preserve the overall paper-style look: flat 2D, white background, minimal color, consistent line width, and sans-serif text. "
"Follow the instructions precisely; keep geometry aligned and readable; avoid extra decorations. "
f"Instructions: {instructions}"
)
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