AxAI Providers For Java

Use when writing Java code with dev.axllm:ax for provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.

Install

Install only this skill for Java:

npx skills add https://ax-llm.github.io/ax/java/ --skill 'ax-java-ai'

Published skill file: ax-java-ai/SKILL.md.

Source

• Source: packages/java/skills/ax-java-ai/SKILL.md
• Version: 23.0.5

Skill Instructions

This skill helps an agent write Java code with the generated Ax package dev.axllm:ax. 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 between model-list routing, ordered failover, and adaptive operational routing.
• Use scripted transports for deterministic no-key examples.
• Use provider-api examples only when explicit provider credentials are available.

Package Facts

• Language: Java.
• Package: dev.axllm:ax.
• 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 dev.axllm.ax.*;

var llm = Ax.ai("openai", java.util.Map.of("apiKey", System.getenv("OPENAI_API_KEY")));

Routing And Balancing

• Use the multi-service router when a logical model key selects a configured service or concrete model. It combines model lists; it does not learn from outcomes.
• Use the default AxBalancer for deterministic ordered/metric failover with its existing retry policy.
• Opt into AxBalancerAdaptiveStrategy only for operational routing among application-approved equivalent aliases. It learns transient reliability and successful latency, combines them with estimated cost and a deadline, and explores with Thompson sampling.
• Put centralized decision state in an AxBalancerStatsStore. The routing-event callback is best-effort analytics and observability, not a state replication mechanism.
• Shared stores require non-empty, unique, stable route keys. Use slices to isolate workflows, tenants, or traffic classes without putting prompts, responses, raw errors, or sensitive identifiers in keys or events.
• Adaptive balancing does not measure answer quality or semantically choose a model. Only group routes that the application already accepts as substitutes.
• Generated streaming APIs are buffered: a provider error can fail over before the completed result is returned, and success latency is recorded after completion.
• Start with examples/adaptive_balancer_no_key for store/reducer syntax, then use the cataloged provider-backed adaptive-balancer example for a complete two-route setup.

Relevant API Surface

• AxAI: Ax.ai, OpenAICompatibleClient, OpenAIResponsesClient, GoogleGeminiClient, AnthropicClient, Map<String, Object>, AxUsageEvent, AxUsageObserver, AxGlobals.setUsageObserver, AxBalancer, AxBalancerAdaptiveStrategy, AxBalancerStatsStore, AxInMemoryBalancerStatsStore, AxBalancerAdaptive.createRouteStats, AxBalancerAdaptive.updateRouteStats, AxBalancerAdaptive.sampleRouteHealth, MultiServiceRouter, ProviderRouter

Guardrails

• Start from package examples for exact native syntax before inventing a new call shape.
• Use provider-api examples only when the user explicitly has provider credentials available.
• Use no-key examples for deterministic local checks and provider request mapping.
• Treat AxIR as the source of generated package truth: if package docs disagree with source code, update the compiler and regenerate packages.
• Do not copy repo-maintainer skills from tools/*/skills/ into user packages.