ax-python-gen

Generate Python AxGen code for typed structured generation workflows.

2.9k|186|Updated Feb 23, 2023

Search Tags:#python #streaming #tools #structured generation #axgen #output parsing #axllm

Ready to run

npx skills add https://github.com/ax-llm/ax --skill ax-python-gen

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ax-python-gen
Source: https://github.com/ax-llm/ax/tree/main/website/static/python/.well-known/agent-skills/ax-python-gen
Command: npx skills add https://github.com/ax-llm/ax --skill ax-python-gen

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you write Python code for Ax structured generation with axllm, so you can create typed generation flows without guessing the correct API shape.

Core Features & Use Cases

Structured Generation: Build programs from signatures and produce typed outputs with AxGen.
Tool Integration: Attach Python tools or MCP-derived tools to generation calls.
Practical Workflow Support: Use examples and package docs for forward calls, streaming, assertions, traces, usage tracking, and output parsing.
Use Case: A developer can quickly turn a product question, extraction task, or tool-driven workflow into a reliable Python generation program using the generated axllm package.

Quick Start

Ask the agent to create a Python axllm AxGen program for your signature, then wire in the LLM, tools, and output handling needed for your task.

Frequently Asked Questions about ax-python-gen

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate typed structured outputs in Python using AxGen?▼

You generate typed structured outputs by building AxGen programs from signatures, wiring in the LLM, and applying output parsing. This produces typed results for extraction tasks or tool-driven workflows.

Can I attach MCP tools to Python streaming generation calls?▼

Yes, you can attach MCP-derived tools or Python tools directly to generation calls. This enables tool-enabled workflows alongside streaming outputs and structured generation within the axllm package.

What is the best way to track usage and traces in axllm generation programs?▼

The best way to track usage and traces is to use the built-in workflow support in the axllm package. You implement assertions, traces, and usage tracking natively within your AxGen program to monitor forward calls.

Do I need API keys to use no-key transport for structured generation?▼

No, you do not need API keys to use the no-key transport feature. You configure provider calls and runtime profiles within the axllm package to execute structured generation workflows without standard authentication.

How do I parse structured outputs from streaming LLM responses in Python?▼

You parse structured outputs from streaming responses by applying native output parsing during forward calls. The axllm package handles the conversion of streams into typed generation results for your program.

Does axllm support runtime profiles for Python tool-enabled workflows?▼

Yes, axllm supports runtime profiles for managing tool-enabled generation workflows. You configure capability manifests and runtime profiles to handle provider calls, MCP tools, and no-key transport within Python programs.