ax-python-gen

AxGen Structured Generation For Python

This skill helps an agent write Python code with the generated Ax package axllm. Use the generated package API, examples, and manifests; do not import TypeScript-only APIs unless you are editing the TypeScript package.

When To Use

• Build a structured generation program from a signature.
• Attach typed tools or MCP-derived tools to a generation call.
• Generate multiple validated structured samples and select a winner with a native callback.
• Use package examples for no-key scripted clients and provider-api calls.

Package Facts

• Language: Python.
• Package: axllm.
• Package API docs: API.md and axir-api.json.
• Capability manifest: axir-capabilities.json.
• Runnable examples: examples/.
• Real network support: yes.
• Scripted no-key transport support: yes.
• Runtime profiles: javascript-quickjs, python-pyodide.

Core Pattern

from axllm import ax

program = ax("question:string -> answer:string")
out = program.forward(llm, {"question": "What is Ax?"})

OpenAI Decisions

The openai-decisions provider uses /v1/decisions with gpt-6-luna by default. Required boolean fields become predicates; required class fields become choices; score fields become labelled native rubrics. Use normal AxGen signatures with (evidence) to retain probabilities, provider-selected values, native confidence, and trusted provenance; use (evidence, refusal return) for an answered/refused union. See the Typesafe/Jev skill for decision evidence and reranking across both providers. trueThreshold (or true_threshold) defaults to 0.5, is finite in [0,1], and uses an inclusive comparison. Field value descriptions become criteria instructions or choice descriptions. Raw answers remain in providerMetadata.openaiDecisions.answers; usage uses existing program APIs.

Use openai_decisions for explicit provider request shapes and native JSON input. Its create operation (Go: Create) accepts input and an ordered questions array. Each question has string instructions and an optional unique string name; unnamed answers retain name: null. Predicate returns probability. Choice requires 2-255 string or boolean choices and returns choice, confidence, and probabilities. Score requires 2-10 explicitly labelled levels and returns a fractional zero-based score, confidence, and probabilities. Handle type: refusal before accessing answer values. Preserve full model, answer order, and usage.