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https://github.com/badlogic/pi-mono.git
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8d95fd138b
Replace the single 3300-line generate-models.ts with declarative provider definitions and ordered rule packs under scripts/model-generation/. Each provider is a defineProvider() call: an upstream source (usually the generic modelsDev() mapper), static models upstream lacks, and rules scoped to that provider. Cross-provider facts live in rule packs applied in a fixed order. Every rule() carries a why, matches models with plain data, and patches them with typed set/replace/apply semantics. Generated model data is unchanged: 1443 models across 41 providers compare equal against a snapshot of the same upstream responses, apart from a now stable key order. Committed models.generated.ts and provider shards are byte-identical. Also: - Bring packages/ai/scripts under tsgo and biome; the old generator had 20+ type errors that nothing checked. - Add --upstream-snapshot <dir> to record and replay upstream catalogs and --explain <provider>:<model> to list the rules applied to a model. - Report rules that matched no model so stale corrections get removed. - Export parseRadiusGatewayConfig so the generator can replay Radius too. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_018ExCU9zaZnN8vB5fKpTAjP
64 lines
1.8 KiB
TypeScript
64 lines
1.8 KiB
TypeScript
import type { OpenAICompletionsCompat } from "../../../src/types.ts";
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import { type DefinedRule, defineProvider, rule } from "../dsl.ts";
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import { modelsDev } from "../models-dev.ts";
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import { KIMI_K3_COST } from "../shared.ts";
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const MOONSHOT_COMPAT: OpenAICompletionsCompat = {
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supportsStore: false,
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supportsDeveloperRole: false,
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supportsReasoningEffort: false,
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maxTokensField: "max_tokens",
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supportsStrictMode: false,
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thinkingFormat: "deepseek",
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};
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const kimiK3Rules: DefinedRule[] = [
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rule({
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why: "Kimi K3 always reasons, takes OpenAI reasoning_effort, and needs reasoning_content replayed on assistant messages.",
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match: { id: "kimi-k3" },
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set: {
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reasoning: true,
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compat: {
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requiresReasoningContentOnAssistantMessages: true,
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thinkingFormat: "openai",
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supportsReasoningEffort: true,
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},
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},
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}),
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rule({
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why: "models.dev has no Kimi K3 prices yet; fill in the published Moonshot rates per missing field.",
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match: { id: "kimi-k3" },
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apply: (model) => {
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model.cost = {
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input: model.cost.input || KIMI_K3_COST.input,
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output: model.cost.output || KIMI_K3_COST.output,
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cacheRead: model.cost.cacheRead || KIMI_K3_COST.cacheRead,
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cacheWrite: model.cost.cacheWrite || KIMI_K3_COST.cacheWrite,
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};
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},
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}),
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];
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export const moonshotai = defineProvider({
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id: "moonshotai",
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source: modelsDev({
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provider: "moonshotai",
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key: "moonshotai",
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api: "openai-completions",
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baseUrl: "https://api.moonshot.ai/v1",
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compat: MOONSHOT_COMPAT,
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}),
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rules: kimiK3Rules,
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});
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export const moonshotaiCn = defineProvider({
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id: "moonshotai-cn",
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source: modelsDev({
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provider: "moonshotai-cn",
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key: "moonshotai-cn",
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api: "openai-completions",
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baseUrl: "https://api.moonshot.cn/v1",
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compat: MOONSHOT_COMPAT,
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}),
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rules: kimiK3Rules,
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});
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