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GNN simulation script execution with result capture. Use when running generated simulation scripts, managing execution environments, handling framework dependencies, or capturing simulation outputs and metrics.
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SOC 職業分類に基づく
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-simulation-execution |
| description | GNN simulation script execution with result capture. Use when running generated simulation scripts, managing execution environments, handling framework dependencies, or capturing simulation outputs and metrics. |
Executes rendered simulation scripts across all supported frameworks with robust error handling, circuit breaker patterns, retry logic, and comprehensive result capture.
# Execute all frameworks
python src/12_execute.py --target-dir input/gnn_files --output-dir output --verbose
# Specific frameworks only
python src/12_execute.py --frameworks "pymdp,jax" --verbose
# Lite preset (PyMDP, JAX, DisCoPy)
python src/12_execute.py --frameworks "lite" --verbose
from execute import (
ExecutionEngine, GNNExecutor, execute_gnn_model, run_simulation,
execute_pymdp_simulation_from_gnn, execute_pymdp_simulation,
validate_execution_environment, process_execute,
execute_script_safely
)
# Process execution step (used by pipeline)
process_execute(target_dir, output_dir, verbose=True)
# Execute a GNN model directly
result = execute_gnn_model(gnn_spec, framework="pymdp")
# Run a simulation configuration
result = run_simulation(config)
# Validate execution environment before running
env_report = validate_execution_environment()
# Use the ExecutionEngine class
engine = ExecutionEngine()
process_execute — main pipeline processing functionExecutionEngine / GNNExecutor — execution engine classesexecute_gnn_model / run_simulation — model execution functionsexecute_pymdp_simulation_from_gnn / execute_pymdp_simulation — PyMDP-specificvalidate_execution_environment — pre-execution validationexecute_script_safely — safe script execution with error handlingThe execute processor follows this pipeline:
output/11_render_output/ for .py and .jl files--frameworks parameter (presets or explicit list)| Preset | Frameworks | Use Case |
|---|---|---|
all | PyMDP, RxInfer, ActiveInference.jl, JAX, DisCoPy | Full execution (default) |
lite | PyMDP, JAX, DisCoPy | Python-only, no Julia required |
pymdp,jax | PyMDP, JAX | Fast Python subset |
# Core execution (PyMDP)
uv sync
# For Julia frameworks
# Requires Julia installed + packages
julia -e 'using Pkg; Pkg.add(["RxInfer", "ActiveInference"])'
# For DisCoPy
uv sync --extra graphs
output/12_execute_output/This module registers tools with the GNN MCP server (see mcp.py):
check_execute_dependenciesexecute_gnn_modelexecute_pymdp_simulationget_execute_module_infoprocess_execute