Scientific Schematics

# Generate for journal paper (highest quality threshold: 8.5/10)
python scripts/generate_schematic.py "CONSORT participant flow diagram with 500 screened, 150 excluded, 350 randomized" -o figures/consort.png --doc-type journal

# Generate for presentation (lower threshold: 6.5/10 - faster)
python scripts/generate_schematic.py "Transformer encoder-decoder architecture showing multi-head attention" -o figures/transformer.png --doc-type presentation

# Generate for poster (moderate threshold: 7.0/10)
python scripts/generate_schematic.py "MAPK signaling pathway from EGFR to gene transcription" -o figures/mapk_pathway.png --doc-type poster

# Custom max iterations (max 2)
python scripts/generate_schematic.py "Complex circuit diagram with op-amp, resistors, and capacitors" -o figures/circuit.png --iterations 2 --doc-type journal

export OPENROUTER_API_KEY='your_api_key_here'

python scripts/generate_schematic.py "your diagram description" -o output.png

┌─────────────────────────────────────────────────────┐
│  1. Generate image with Nano Banana 2             │
│                    ↓                                │
│  2. Review quality with Gemini 3.1 Pro Preview                │
│                    ↓                                │
│  3. Score >= threshold?                             │
│       YES → DONE! (early stop)                      │
│       NO  → Improve prompt, go to step 1            │
│                    ↓                                │
│  4. Repeat until quality met OR max iterations      │
└─────────────────────────────────────────────────────┘

Scientific diagram guidelines + User request

SCORE: 8.0

STRENGTHS:
- Clear flow from top to bottom
- All phases properly labeled
- Professional typography

ISSUES:
- Participant counts slightly small
- Minor overlap on exclusion box

VERDICT: ACCEPTABLE (for poster, threshold 7.0)

{
  "user_prompt": "CONSORT participant flow diagram...",
  "doc_type": "poster",
  "quality_threshold": 7.0,
  "iterations": [
    {
      "iteration": 1,
      "image_path": "figures/consort_v1.png",
      "score": 7.5,
      "needs_improvement": false,
      "critique": "SCORE: 7.5\nSTRENGTHS:..."
    }
  ],
  "final_score": 7.5,
  "early_stop": true,
  "early_stop_reason": "Quality score 7.5 meets threshold 7.0 for poster"
}

from scripts.generate_schematic_ai import ScientificSchematicGenerator

# Initialize generator
generator = ScientificSchematicGenerator(
    api_key="your_openrouter_key",
    verbose=True
)

# Generate with iterative refinement (max 2 iterations)
results = generator.generate_iterative(
    user_prompt="Transformer architecture diagram",
    output_path="figures/transformer.png",
    iterations=2
)

# Access results
print(f"Final score: {results['final_score']}/10")
print(f"Final image: {results['final_image']}")

# Review individual iterations
for iteration in results['iterations']:
    print(f"Iteration {iteration['iteration']}: {iteration['score']}/10")
    print(f"Critique: {iteration['critique']}")

# Basic usage (default threshold 7.5/10)
python scripts/generate_schematic.py "diagram description" -o output.png

# Specify document type for appropriate quality threshold
python scripts/generate_schematic.py "diagram" -o out.png --doc-type journal      # 8.5/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type conference   # 8.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type poster       # 7.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type presentation # 6.5/10

# Custom max iterations (1-2)
python scripts/generate_schematic.py "complex diagram" -o diagram.png --iterations 2

# Verbose output (see all API calls and reviews)
python scripts/generate_schematic.py "flowchart" -o flow.png -v

# Provide API key via flag
python scripts/generate_schematic.py "diagram" -o out.png --api-key "sk-or-v1-..."

# Combine options
python scripts/generate_schematic.py "neural network" -o nn.png --doc-type journal --iterations 2 -v

✓ "Flowchart with vertical flow, top to bottom"
✓ "Architecture diagram with encoder on left, decoder on right"
✓ "Circular pathway diagram with clockwise flow"

✓ "Neural network with input layer (784 nodes), hidden layer (128 nodes), output (10 nodes)"
✓ "Flowchart showing n=500 screened, n=150 excluded, n=350 randomized"
✓ "Circuit with 1kΩ resistor, 10µF capacitor, 5V source"

✓ "Minimalist block diagram with clean lines"
✓ "Detailed biological pathway with protein structures"
✓ "Technical schematic with engineering notation"

✓ "Label all arrows with activation/inhibition"
✓ "Include layer dimensions in each box"
✓ "Show time progression with timestamps"

✓ "Use colorblind-friendly colors"
✓ "Grayscale-compatible design"
✓ "Color-code by function: blue for input, green for processing, red for output"

python scripts/generate_schematic.py \
  "CONSORT participant flow diagram for randomized controlled trial. \
   Start with 'Assessed for eligibility (n=500)' at top. \
   Show 'Excluded (n=150)' with reasons: age<18 (n=80), declined (n=50), other (n=20). \
   Then 'Randomized (n=350)' splits into two arms: \
   'Treatment group (n=175)' and 'Control group (n=175)'. \
   Each arm shows 'Lost to follow-up' (n=15 and n=10). \
   End with 'Analyzed' (n=160 and n=165). \
   Use blue boxes for process steps, orange for exclusion, green for final analysis." \
  -o figures/consort.png

python scripts/generate_schematic.py \
  "Transformer encoder-decoder architecture diagram. \
   Left side: Encoder stack with input embedding, positional encoding, \
   multi-head self-attention, add & norm, feed-forward, add & norm. \
   Right side: Decoder stack with output embedding, positional encoding, \
   masked self-attention, add & norm, cross-attention (receiving from encoder), \
   add & norm, feed-forward, add & norm, linear & softmax. \
   Show cross-attention connection from encoder to decoder with dashed line. \
   Use light blue for encoder, light red for decoder. \
   Label all components clearly." \
  -o figures/transformer.png --iterations 2

python scripts/generate_schematic.py \
  "MAPK signaling pathway diagram. \
   Start with EGFR receptor at cell membrane (top). \
   Arrow down to RAS (with GTP label). \
   Arrow to RAF kinase. \
   Arrow to MEK kinase. \
   Arrow to ERK kinase. \
   Final arrow to nucleus showing gene transcription. \
   Label each arrow with 'phosphorylation' or 'activation'. \
   Use rounded rectangles for proteins, different colors for each. \
   Include membrane boundary line at top." \
  -o figures/mapk_pathway.png

python scripts/generate_schematic.py \
  "IoT system architecture block diagram. \
   Bottom layer: Sensors (temperature, humidity, motion) in green boxes. \
   Middle layer: Microcontroller (ESP32) in blue box. \
   Connections to WiFi module (orange box) and Display (purple box). \
   Top layer: Cloud server (gray box) connected to mobile app (light blue box). \
   Show data flow arrows between all components. \
   Label connections with protocols: I2C, UART, WiFi, HTTPS." \
  -o figures/iot_architecture.png

# Basic usage
python scripts/generate_schematic.py "diagram description" -o output.png

# Custom iterations (max 2)
python scripts/generate_schematic.py "complex diagram" -o diagram.png --iterations 2

# Verbose mode
python scripts/generate_schematic.py "diagram" -o out.png -v