mirror of
https://github.com/K-Dense-AI/claude-scientific-skills.git
synced 2026-03-27 07:09:27 +08:00
140 lines
4.9 KiB
Python
140 lines
4.9 KiB
Python
#!/usr/bin/env python3
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"""
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Scientific schematic generation using Nano Banana 2.
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Generate any scientific diagram by describing it in natural language.
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Nano Banana 2 handles everything automatically with smart iterative refinement.
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Smart iteration: Only regenerates if quality is below threshold for your document type.
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Quality review: Uses Gemini 3.1 Pro Preview for professional scientific evaluation.
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Usage:
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# Generate for journal paper (highest quality threshold)
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python generate_schematic.py "CONSORT flowchart" -o flowchart.png --doc-type journal
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# Generate for presentation (lower threshold, faster)
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python generate_schematic.py "Transformer architecture" -o transformer.png --doc-type presentation
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# Generate for poster
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python generate_schematic.py "MAPK signaling pathway" -o pathway.png --doc-type poster
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"""
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import argparse
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import os
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import subprocess
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import sys
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from pathlib import Path
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def main():
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"""Command-line interface."""
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parser = argparse.ArgumentParser(
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description="Generate scientific schematics using AI with smart iterative refinement",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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How it works:
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Simply describe your diagram in natural language
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Nano Banana 2 generates it automatically with:
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- Smart iteration (only regenerates if quality is below threshold)
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- Quality review by Gemini 3.1 Pro Preview
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- Document-type aware quality thresholds
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- Publication-ready output
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Document Types (quality thresholds):
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journal 8.5/10 - Nature, Science, peer-reviewed journals
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conference 8.0/10 - Conference papers
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thesis 8.0/10 - Dissertations, theses
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grant 8.0/10 - Grant proposals
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preprint 7.5/10 - arXiv, bioRxiv, etc.
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report 7.5/10 - Technical reports
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poster 7.0/10 - Academic posters
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presentation 6.5/10 - Slides, talks
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default 7.5/10 - General purpose
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Examples:
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# Generate for journal paper (strict quality)
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python generate_schematic.py "CONSORT participant flow" -o flowchart.png --doc-type journal
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# Generate for poster (moderate quality)
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python generate_schematic.py "Transformer architecture" -o arch.png --doc-type poster
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# Generate for slides (faster, lower threshold)
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python generate_schematic.py "System diagram" -o system.png --doc-type presentation
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# Custom max iterations
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python generate_schematic.py "Complex pathway" -o pathway.png --iterations 2
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# Verbose output
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python generate_schematic.py "Circuit diagram" -o circuit.png -v
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Environment Variables:
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OPENROUTER_API_KEY Required for AI generation
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"""
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)
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parser.add_argument("prompt",
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help="Description of the diagram to generate")
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parser.add_argument("-o", "--output", required=True,
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help="Output file path")
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parser.add_argument("--doc-type", default="default",
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choices=["journal", "conference", "poster", "presentation",
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"report", "grant", "thesis", "preprint", "default"],
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help="Document type for quality threshold (default: default)")
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parser.add_argument("--iterations", type=int, default=2,
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help="Maximum refinement iterations (default: 2, max: 2)")
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parser.add_argument("--api-key",
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help="OpenRouter API key (or use OPENROUTER_API_KEY env var)")
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parser.add_argument("-v", "--verbose", action="store_true",
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help="Verbose output")
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args = parser.parse_args()
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# Check for API key
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api_key = args.api_key or os.getenv("OPENROUTER_API_KEY")
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if not api_key:
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print("Error: OPENROUTER_API_KEY environment variable not set")
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print("\nFor AI generation, you need an OpenRouter API key.")
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print("Get one at: https://openrouter.ai/keys")
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print("\nSet it with:")
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print(" export OPENROUTER_API_KEY='your_api_key'")
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print("\nOr use --api-key flag")
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sys.exit(1)
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# Find AI generation script
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script_dir = Path(__file__).parent
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ai_script = script_dir / "generate_schematic_ai.py"
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if not ai_script.exists():
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print(f"Error: AI generation script not found: {ai_script}")
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sys.exit(1)
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# Build command
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cmd = [sys.executable, str(ai_script), args.prompt, "-o", args.output]
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if args.doc_type != "default":
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cmd.extend(["--doc-type", args.doc_type])
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# Enforce max 2 iterations
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iterations = min(args.iterations, 2)
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if iterations != 2:
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cmd.extend(["--iterations", str(iterations)])
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if api_key:
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cmd.extend(["--api-key", api_key])
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if args.verbose:
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cmd.append("-v")
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# Execute
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try:
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result = subprocess.run(cmd, check=False)
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sys.exit(result.returncode)
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except Exception as e:
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print(f"Error executing AI generation: {e}")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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