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GNN multi-format export generation. Use when exporting GNN models to JSON, XML, GraphML, GEXF, Pickle, or other interchange formats for use in external tools and frameworks.
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基于 SOC 职业分类
Generalized Notation Notation (GNN) processing pipeline for Active Inference generative models. Use when working with GNN files, running the 25-step pipeline, parsing model specifications, generating simulations, or producing visualizations and reports from GNN model definitions.
GNN command-line interface dispatch and health checks. Use when invoking the `gnn` CLI, validating subcommand availability, or checking command-line access to pipeline modules.
GNN LLM-enhanced analysis and model interpretation. Use when generating natural language descriptions of GNN models, getting AI-assisted model explanations, or performing LLM-powered analysis of Active Inference specifications.
GNN Language Server Protocol integration. Use when starting editor diagnostics, checking hover behavior, or validating LSP support for GNN files.
GNN Model Context Protocol processing and tool registration. Use when registering GNN operations as MCP tools, building MCP server configurations, or integrating GNN capabilities with LLM tool-use workflows.
GNN pipeline orchestration and configuration management. Use when configuring pipeline execution, setting step inclusion/exclusion, managing pipeline state, or customizing the 25-step execution flow.
| name | gnn-export |
| description | GNN multi-format export generation. Use when exporting GNN models to JSON, XML, GraphML, GEXF, Pickle, or other interchange formats for use in external tools and frameworks. |
Exports parsed GNN models to multiple interchange formats for interoperability with external tools, visualization platforms, and analysis frameworks.
# Run export
python src/7_export.py --target-dir input/gnn_files --output-dir output --verbose
# As part of pipeline
python src/main.py --only-steps 7 --verbose
| Format | Extension | Use Case |
|---|---|---|
| JSON | .json | General interchange, web tools |
| XML | .xml | Enterprise integration |
| GraphML | .graphml | Graph analysis tools (Gephi, yEd) |
| GEXF | .gexf | Dynamic graph visualization |
| Pickle | .pkl | Python-native serialization |
from export import (
export_model, generate_exports, export_single_gnn_file,
Exporter, MultiFormatExporter, get_supported_formats,
export_to_json, export_to_xml, export_to_graphml, export_to_gexf,
process_export
)
# Export single file to all formats
export_single_gnn_file("model.md", "output/")
# Use the Exporter class
exporter = Exporter()
result = exporter.export_gnn_model(gnn_content, "json")
# Multi-format export
mf_exporter = MultiFormatExporter()
results = mf_exporter.export_to_multiple_formats(content, ["json", "xml", "graphml"])
# Query supported formats
formats = get_supported_formats()
# Run full export step (used by pipeline)
process_export(target_dir, output_dir, verbose=True)
export_model / export_single_gnn_file — export a single modelgenerate_exports — batch export for a directoryExporter / MultiFormatExporter — class-based export interfacesexport_to_json, export_to_xml, export_to_graphml, export_to_gexf — format-specificprocess_export — main pipeline processing functionoutput/7_export_output/This module registers tools with the GNN MCP server (see mcp.py):
export_single_gnn_filelist_export_formatsprocess_exportvalidate_export_format