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learnharness/src/agent/models.ts
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import {
createModels,
type Api,
type Model,
type Models,
type StreamFunction,
} from "@earendil-works/pi-ai";
import { openrouterProvider } from "@earendil-works/pi-ai/providers/openrouter";
import type { ThinkingLevel } from "@earendil-works/pi-agent-core";
import { MODELS, type ModelRole } from "../../config.ts";
/**
* The one engine factory every agent's model comes from (the pi-ai swap,
* docs/pi-engine-swap.md). Model choice and thinking budget live in
* config.ts (MODELS) — the single tuning table; this module only wires them
* to pi-ai's OpenRouter provider.
*
* An "engine" is the model + the stream function the agent loop runs on —
* the two things a test fake replaces. Production engines resolve the model
* from pi-ai's static catalog (glm-5.3-flash and qwen3.8-max are both in
* 0.85.1's built-ins — no overlay fetch) and stream through the same Models
* collection.
*/
export interface PiEngine {
model: Model<Api>;
streamFn: StreamFunction;
}
export type { ThinkingLevel };
/** config's effort scale maps 1:1 onto pi's thinking levels (none→off). */
export function thinkingLevelFor(role: ModelRole): ThinkingLevel {
const effort = MODELS[role].effort as string;
return effort === "none" ? "off" : (effort as ThinkingLevel);
}
let collection: ReturnType<typeof createModels> | undefined;
/** The process-wide pi-ai Models collection (OpenRouter catalog). */
export function piModels() {
if (!collection) {
collection = createModels();
collection.setProvider(openrouterProvider());
}
return collection;
}
/** OpenRouter API key (BYOK); tests never read this — they inject engines. */
export function openRouterApiKey(): string | undefined {
return process.env.OPENROUTER_API_KEY || undefined;
}
/** The production engine for one agent role (config.ts MODELS). */
export function piEngineFor(role: ModelRole): PiEngine {
const models: Models = piModels();
const spec = MODELS[role];
const model = models.getModel("openrouter", spec.model);
if (!model) throw new Error(`OpenRouter catalog has no model ${spec.model} (role ${role})`);
const level = thinkingLevelFor(role);
return {
model,
// bound streamSimple: the agent loop forwards state.thinkingLevel as
// `reasoning` (undefined = off on pi-ai's scale); pin the role's level
// so a bare engine can never drift.
streamFn: (requestModel, context, options) =>
models.streamSimple(requestModel, context, {
...options,
reasoning: level === "off" ? undefined : level,
apiKey: options?.apiKey ?? openRouterApiKey(),
}),
};
}