ax-python-ai

AxAI Providers 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

• Create provider clients or normalize provider options.
• Choose a named deployment profile separately from the model ID served by that deployment.
• Attach renewable per-request credentials for expiring cloud tokens.
• Resolve structured-output modes from the selected profile and model.
• Choose between model-list routing, ordered failover, and adaptive operational routing.
• Route multimodal requests without flattening native images when the selected provider supports them.
• Use scripted transports for deterministic no-key examples.
• Use provider-api examples only when explicit provider credentials are available.

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

import os
from axllm import ai

llm = ai("openai", api_key=os.environ["OPENAI_API_KEY"])

Named Deployment Profiles

• The first ai / NewAI factory argument selects deployment behavior. The model option selects a model only inside that deployment; never infer request rules from a vendor-looking model ID.
• openai is the official OpenAI deployment. openai-compatible is the conservative custom-endpoint profile and requires an explicit base URL. Unknown profile names are errors.
• A Together-hosted DeepSeek model uses the together profile's URL, authentication, reasoning fields, and effort mapping. Native DeepSeek thinking fields apply only to the deepseek profile.
• Verified DeepSeek, Grok, Groq, Cerebras, and DeepInfra model rules default an omitted thinking level to logical max, mapped to the strongest documented deployment effort.
• Send none only where the selected deployment and model document reasoning disablement. Unsupported levels fail before network I/O; dynamic Hugging Face Router routes remain conservative.
• Structured output is an ordered model-aware capability: native, function, and json_object. Exact caller model metadata overrides the first matching profile rule, which overrides the profile default.
• An explicit unsupported structured-output mode fails before transport. structuredOutputs / structured_outputs remains the compatibility alias for native JSON Schema only.
• The exact Vertex google/gemma-4-26b-a4b-it-maas rule prefers json_object, excludes native schema, defaults thinking to max, writes nested enable_thinking, and extracts/replays reasoning_content. Unknown Vertex models stay conservative.
• Use named factories for Azure OpenAI, Cohere, DeepSeek, DeepSeek Responses, Mistral, Reka, Grok, routers, hosted inference, and configurable runtimes. Profile-only branded client constructors were removed.
• Retained client classes are transport/runtime boundaries: OpenAI-compatible Chat Completions, OpenAI Responses, Anthropic Messages, and Gemini GenerateContent. Build ordinary applications through the named factory.
• Provider descriptors and conformance fixtures are generated from the shared profile manifest. Do not add provider-name switches or cross-profile model normalization in a generated package.