Create generator.py

utils/generator.py

@@ -0,0 +1,166 @@
+"""
+Generator utilities for creating JSON and Markdown outputs
+"""
+
+import json
+from datetime import datetime
+
+def generate_json_output(metadata, top_level, processes, generator_version):
+    """
+    Generate JSON output for the model card
+    
+    Args:
+        metadata: Dictionary of metadata fields
+        top_level: Dictionary of top-level elements (Figure 6)
+        processes: Dictionary of data & process elements (Figure 7)
+        generator_version: Version of the generator
+    
+    Returns:
+        String containing JSON data ready for file download
+    """
+    output = {
+        "df_model_card_metadata": metadata,
+        "df_mc_0_top_level": {
+            k: v for k, v in top_level.items() 
+            if v.get("applicable") and v.get("description")
+        },
+        "df_mc_1_data_processes": {
+            k: v for k, v in processes.items()
+            if v.get("applicable") and v.get("description")
+        },
+        "generated_at": datetime.utcnow().isoformat() + "Z",
+        "generator_version": generator_version,
+        "schema_version": "1.0"
+    }
+    
+    return json.dumps(output, indent=2)
+
+
+def generate_markdown_output(metadata, top_level, processes, generator_version):
+    """
+    Generate Markdown README output for the model card
+    
+    Args:
+        metadata: Dictionary of metadata fields
+        top_level: Dictionary of top-level elements (Figure 6)
+        processes: Dictionary of data & process elements (Figure 7)
+        generator_version: Version of the generator
+    
+    Returns:
+        String containing Markdown content ready for file download
+    """
+    
+    md = []
+    
+    # Header
+    md.append("# Digital Forensics Model Card\n")
+    md.append(f"**Generated:** {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')} UTC\n")
+    md.append("---\n")
+    
+    # Metadata Section
+    md.append("## Metadata\n")
+    md.append(f"- **Identifier (MMCID):** {metadata.get('mmcid', 'Not specified')}")
+    md.append(f"- **Version (MCV):** {metadata.get('version', 'N/A')}")
+    md.append(f"- **Owner:** {metadata.get('owner', 'Not specified')}")
+    md.append(f"- **Usage Context:** {metadata.get('use_context', 'Not specified')}")
+    md.append(f"- **Layer/Stage (Ln):** {metadata.get('layer_n', 'N/A')}\n")
+    
+    # Case Statement
+    if metadata.get('case_statement'):
+        md.append("### Case Statement")
+        md.append(f"{metadata['case_statement']}\n")
+    
+    # Hypothesis
+    if metadata.get('hypothesis'):
+        md.append("### Hypothesis")
+        md.append(f"{metadata['hypothesis']}\n")
+    
+    # Classification
+    if metadata.get('classification'):
+        md.append("### Classification")
+        for item in metadata['classification']:
+            md.append(f"- {item}")
+        md.append("")
+    
+    # Reasoning Type
+    if metadata.get('reasoning_type'):
+        md.append("### Type of Reasoning")
+        for item in metadata['reasoning_type']:
+            md.append(f"- {item}")
+        md.append("")
+    
+    # Bias
+    if metadata.get('bias'):
+        md.append("### Identified Bias")
+        for item in metadata['bias']:
+            md.append(f"- {item}")
+        md.append("")
+        
+        if metadata.get('cause_of_bias'):
+            md.append("**Cause(s) of Bias:**")
+            for item in metadata['cause_of_bias']:
+                md.append(f"- {item}")
+            md.append("")
+    
+    # Error
+    if metadata.get('error'):
+        md.append("### Error")
+        md.append(f"{metadata['error']}\n")
+        
+        if metadata.get('cause_of_error'):
+            md.append("**Cause(s) of Error:**")
+            for item in metadata['cause_of_error']:
+                md.append(f"- {item}")
+            md.append("")
+    
+    md.append("---\n")
+    
+    # Top Level Elements (Figure 6)
+    md.append("## Top Level Elements (DF MC 0)\n")
+    md.append("*Based on Figure 6 - Top Level Elements*\n")
+    
+    applicable_top_level = {
+        k: v for k, v in top_level.items() 
+        if v.get("applicable") and v.get("description")
+    }
+    
+    if applicable_top_level:
+        for key, value in applicable_top_level.items():
+            title = key.replace("_", " ").title()
+            md.append(f"### {title}")
+            md.append(f"{value['description']}\n")
+    else:
+        md.append("*No top-level elements specified.*\n")
+    
+    md.append("---\n")
+    
+    # Data & Processes (Figure 7)
+    md.append("## Data Types and Analytical Processes (DF MC 1)\n")
+    md.append("*Based on Figure 7 - DF Data types and analytical processes (Hargreaves et al., 2024)*\n")
+    
+    applicable_processes = {
+        k: v for k, v in processes.items()
+        if v.get("applicable") and v.get("description")
+    }
+    
+    if applicable_processes:
+        for key, value in applicable_processes.items():
+            title = key.replace("_", " ").title()
+            md.append(f"### {title}")
+            md.append(f"{value['description']}\n")
+    else:
+        md.append("*No data processes specified.*\n")
+    
+    md.append("---\n")
+    
+    # References
+    md.append("## References\n")
+    md.append("This model card is based on the following works:\n")
+    md.append("1. **Di Maio, P.** (2024). Towards Open Standards for Systemic Complexity in Digital Forensics. https://papers.cool/arxiv/2512.12970")
+    md.append("2. **Hargreaves, C., Nelson, A., & Casey, E.** (2024). An abstract model for digital forensic analysis tools—A foundation for systematic error mitigation analysis. *Forensic Science International: Digital Investigation*, 48.\n")
+    
+    # Footer
+    md.append("---\n")
+    md.append(f"*Generated by [Digital Forensics Model Card Generator](https://huggingface.co/spaces/forensic-model-card-generator) v{generator_version}*")
+    
+    return "\n".join(md)