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@loadline/providers

v0.1.1

Published

Model access for loadline gates. Anthropic and OpenRouter, behind one interface.

Readme

@loadline/providers

Model access for loadline gates. Anthropic and OpenRouter behind one interface.

import { createSelector, resolveProvider } from '@loadline/providers';

const { provider } = resolveProvider();          // reads the environment
const selector = createSelector(provider, model);
const calls = await selector.select({ question, tools, instructions });

Why two providers

A gate that only runs against one vendor's model tests that vendor, not your system. Running the same suite across providers is how the interesting findings surface — a rule that holds on one model and is ignored by two others is a different problem from a rule that holds everywhere.

It is also about cost. A gate that runs on every pull request has to be cheap enough that nobody argues for removing it, which usually means OpenRouter and a capable non-frontier model rather than the largest thing available.

Resolution

OPENROUTER_API_KEY is preferred when both are set; ANTHROPIC_API_KEY is used otherwise. Pass { provider } to force one. When neither key is present, resolveProvider returns { provider: undefined, problem } rather than throwing — the caller decides how to report a missing key, and a gate should say which variable to set rather than print a stack trace.

Defaults: claude-opus-5 on Anthropic, z-ai/glm-5.2 on OpenRouter. Any model with tool-calling support works via --model.

Shape

interface ToolCall { name: string; input: Record<string, unknown>; }

interface ToolSelector {
  label: string;                                   // shown in reports and stored in baselines
  select(request: SelectRequest): Promise<ToolCall[]>;
}

OpenAI-shaped tool calls arrive as JSON strings and are parsed defensively: a model that emits malformed arguments should produce a case that fails, not a crash that takes the run down. toOpenAiTools and parseOpenAiToolCalls are exported for anyone wiring up a third provider.

label includes the model id and is recorded in the baseline, so a comparison across two different models is visible rather than silent.