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2025-12-11 18:37:06 -08:00

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4.9 KiB
Python

#!/usr/bin/env python3
"""
Scientific schematic generation using Nano Banana Pro.
Generate any scientific diagram by describing it in natural language.
Nano Banana Pro handles everything automatically with smart iterative refinement.
Smart iteration: Only regenerates if quality is below threshold for your document type.
Quality review: Uses Gemini 3 Pro for professional scientific evaluation.
Usage:
# Generate for journal paper (highest quality threshold)
python generate_schematic.py "CONSORT flowchart" -o flowchart.png --doc-type journal
# Generate for presentation (lower threshold, faster)
python generate_schematic.py "Transformer architecture" -o transformer.png --doc-type presentation
# Generate for poster
python generate_schematic.py "MAPK signaling pathway" -o pathway.png --doc-type poster
"""
import argparse
import os
import subprocess
import sys
from pathlib import Path
def main():
"""Command-line interface."""
parser = argparse.ArgumentParser(
description="Generate scientific schematics using AI with smart iterative refinement",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
How it works:
Simply describe your diagram in natural language
Nano Banana Pro generates it automatically with:
- Smart iteration (only regenerates if quality is below threshold)
- Quality review by Gemini 3 Pro
- Document-type aware quality thresholds
- Publication-ready output
Document Types (quality thresholds):
journal 8.5/10 - Nature, Science, peer-reviewed journals
conference 8.0/10 - Conference papers
thesis 8.0/10 - Dissertations, theses
grant 8.0/10 - Grant proposals
preprint 7.5/10 - arXiv, bioRxiv, etc.
report 7.5/10 - Technical reports
poster 7.0/10 - Academic posters
presentation 6.5/10 - Slides, talks
default 7.5/10 - General purpose
Examples:
# Generate for journal paper (strict quality)
python generate_schematic.py "CONSORT participant flow" -o flowchart.png --doc-type journal
# Generate for poster (moderate quality)
python generate_schematic.py "Transformer architecture" -o arch.png --doc-type poster
# Generate for slides (faster, lower threshold)
python generate_schematic.py "System diagram" -o system.png --doc-type presentation
# Custom max iterations
python generate_schematic.py "Complex pathway" -o pathway.png --iterations 2
# Verbose output
python generate_schematic.py "Circuit diagram" -o circuit.png -v
Environment Variables:
OPENROUTER_API_KEY Required for AI generation
"""
)
parser.add_argument("prompt",
help="Description of the diagram to generate")
parser.add_argument("-o", "--output", required=True,
help="Output file path")
parser.add_argument("--doc-type", default="default",
choices=["journal", "conference", "poster", "presentation",
"report", "grant", "thesis", "preprint", "default"],
help="Document type for quality threshold (default: default)")
parser.add_argument("--iterations", type=int, default=2,
help="Maximum refinement iterations (default: 2, max: 2)")
parser.add_argument("--api-key",
help="OpenRouter API key (or use OPENROUTER_API_KEY env var)")
parser.add_argument("-v", "--verbose", action="store_true",
help="Verbose output")
args = parser.parse_args()
# Check for API key
api_key = args.api_key or os.getenv("OPENROUTER_API_KEY")
if not api_key:
print("Error: OPENROUTER_API_KEY environment variable not set")
print("\nFor AI generation, you need an OpenRouter API key.")
print("Get one at: https://openrouter.ai/keys")
print("\nSet it with:")
print(" export OPENROUTER_API_KEY='your_api_key'")
print("\nOr use --api-key flag")
sys.exit(1)
# Find AI generation script
script_dir = Path(__file__).parent
ai_script = script_dir / "generate_schematic_ai.py"
if not ai_script.exists():
print(f"Error: AI generation script not found: {ai_script}")
sys.exit(1)
# Build command
cmd = [sys.executable, str(ai_script), args.prompt, "-o", args.output]
if args.doc_type != "default":
cmd.extend(["--doc-type", args.doc_type])
# Enforce max 2 iterations
iterations = min(args.iterations, 2)
if iterations != 2:
cmd.extend(["--iterations", str(iterations)])
if api_key:
cmd.extend(["--api-key", api_key])
if args.verbose:
cmd.append("-v")
# Execute
try:
result = subprocess.run(cmd, check=False)
sys.exit(result.returncode)
except Exception as e:
print(f"Error executing AI generation: {e}")
sys.exit(1)
if __name__ == "__main__":
main()