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arg2p for Python

Arg2P, structured argumentation in Prolog (ASPIC+, ABA, ABA+, abstract frameworks, ...), from Python: the API of the library of the JVM, in snake case, run through JPype on the Java runtime the wheel bundles.

pip install arg2p
from arg2p import Arg2p, Flags, Semantics

arg2p = Arg2p.of("""
r1 : [] => a.
r2 : [] => -a.
sup(r1, r2).
""")

arg2p.answer("a").in_statements                 # ['a']
(graph,) = arg2p.graphs()
graph.conclusions("out")                        # ['-a']

preferred = Arg2p.of("f1 :=> d.\nf2 :=> -d.", Flags.defaults().argument_labelling_mode(Semantics.PREFERRED))
len(preferred.graphs())                         # 2

Arg2p.of("r1 :=> a.\nr2 : a => b.").causality.but_for("a", "b")   # True

See the documentation for the whole API: flags, graphs, Prolog goals, causality, the parallel solver and the command line (arg2p theory.pl -q a).

The MCP server

arg2p mcp runs the MCP server of Arg2P, for AI assistants to solve theories with it, on the Java runtime of the wheel: uvx arg2p mcp with uv, nothing to install first. See AI assistants for its tools, the clients, and the plugin with the skills of Arg2P.

Building

The package is a project of the Gradle build of Arg2P, which gives it its jars, its version and its Java runtime:

./gradlew :python:pythonJars :python:pythonVersion :python:pythonRuntime
pip install "./python[test]"
pytest python/tests

Without the runtime (pythonRuntime), the package runs on the Java of the system (21 or later). The variables choosing another JVM, other jars and the options of the JVM (ARG2P_JVM, ARG2P_CLASSPATH, ARG2P_STACK, ARG2P_JVM_OPTIONS) are in the documentation.

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