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refactor(ai): Implement unified model system with type-safe createLLM
- Add Model interface to types.ts with normalized structure - Create type-safe generic createLLM function with provider-specific model constraints - Generate models from OpenRouter API and models.dev data - Strip provider prefixes for direct providers (google, openai, anthropic, xai) - Keep full model IDs for OpenRouter-proxied models - Clean separation: types.ts (Model interface), models.ts (factory logic), models.generated.ts (data) - Remove old model scripts and unused dependencies - Rename GeminiLLM to GoogleLLM for consistency - Add tests for new providers (xAI, Groq, Cerebras, OpenRouter) - Support 181 tool-capable models across 7 providers with full type safety
This commit is contained in:
Mario Zechner
parent
3f36051bc6
commit
c7618db3f7
8 changed files with 409 additions and 418 deletions
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@ -3,41 +3,30 @@
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export const version = "0.5.8";
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// Export generated models and factory
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// Export generated models data
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export { PROVIDERS } from "./models.generated.js";
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// Export models utilities and types
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export {
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ANTHROPIC_MODELS,
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type AnthropicModel,
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type CreateLLMOptions,
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type CerebrasModel,
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createLLM,
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GEMINI_MODELS,
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type GeminiModel,
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type ModelData,
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OPENAI_COMPATIBLE_PROVIDERS,
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OPENAI_MODELS,
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type OpenAICompatibleProvider,
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type GoogleModel,
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type GroqModel,
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type Model,
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type OpenAIModel,
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type ProviderData,
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} from "./models.generated.js";
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// Export models utilities
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export {
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getAllProviders,
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getModelInfo,
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getProviderInfo,
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getProviderModels,
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loadModels,
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type ModalityInput,
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type ModalityOutput,
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type ModelInfo,
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type ModelsData,
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type ProviderInfo,
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supportsThinking,
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supportsTools,
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type OpenRouterModel,
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PROVIDER_CONFIG,
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type ProviderModels,
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type ProviderToLLM,
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type XAIModel,
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} from "./models.js";
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// Export providers
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export { AnthropicLLM } from "./providers/anthropic.js";
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export { GeminiLLM } from "./providers/gemini.js";
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export { GoogleLLM } from "./providers/gemini.js";
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export { OpenAICompletionsLLM } from "./providers/openai-completions.js";
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export { OpenAIResponsesLLM } from "./providers/openai-responses.js";
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// Export types
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export type * from "./types.js";
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@ -1,133 +1,97 @@
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import { readFileSync } from "fs";
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import { dirname, join } from "path";
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import { fileURLToPath } from "url";
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import { PROVIDERS } from "./models.generated.js";
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import { AnthropicLLM } from "./providers/anthropic.js";
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import { GoogleLLM } from "./providers/gemini.js";
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import { OpenAICompletionsLLM } from "./providers/openai-completions.js";
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import { OpenAIResponsesLLM } from "./providers/openai-responses.js";
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import type { Model } from "./types.js";
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export type ModalityInput = "text" | "image" | "audio" | "video" | "pdf";
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export type ModalityOutput = "text" | "image" | "audio";
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// Provider configuration with factory functions
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export const PROVIDER_CONFIG = {
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google: {
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envKey: "GEMINI_API_KEY",
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create: (model: string, apiKey: string) => new GoogleLLM(model, apiKey),
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},
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openai: {
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envKey: "OPENAI_API_KEY",
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create: (model: string, apiKey: string) => new OpenAIResponsesLLM(model, apiKey),
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},
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anthropic: {
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envKey: "ANTHROPIC_API_KEY",
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create: (model: string, apiKey: string) => new AnthropicLLM(model, apiKey),
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},
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xai: {
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envKey: "XAI_API_KEY",
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create: (model: string, apiKey: string) => new OpenAICompletionsLLM(model, apiKey, "https://api.x.ai/v1"),
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},
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groq: {
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envKey: "GROQ_API_KEY",
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create: (model: string, apiKey: string) =>
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new OpenAICompletionsLLM(model, apiKey, "https://api.groq.com/openai/v1"),
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},
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cerebras: {
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envKey: "CEREBRAS_API_KEY",
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create: (model: string, apiKey: string) => new OpenAICompletionsLLM(model, apiKey, "https://api.cerebras.ai/v1"),
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},
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openrouter: {
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envKey: "OPENROUTER_API_KEY",
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create: (model: string, apiKey: string) =>
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new OpenAICompletionsLLM(model, apiKey, "https://openrouter.ai/api/v1"),
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},
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} as const;
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export interface ModelInfo {
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id: string;
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name: string;
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attachment: boolean;
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reasoning: boolean;
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temperature: boolean;
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tool_call: boolean;
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release_date: string;
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last_updated: string;
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modalities: {
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input: ModalityInput[];
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output: ModalityOutput[];
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};
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open_weights: boolean;
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limit: {
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context: number;
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output: number;
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};
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knowledge?: string; // Optional - knowledge cutoff date
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cost?: {
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input: number;
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output: number;
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cache_read?: number;
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cache_write?: number;
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};
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// Type mapping from provider to LLM implementation
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export type ProviderToLLM = {
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google: GoogleLLM;
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openai: OpenAIResponsesLLM;
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anthropic: AnthropicLLM;
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xai: OpenAICompletionsLLM;
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groq: OpenAICompletionsLLM;
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cerebras: OpenAICompletionsLLM;
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openrouter: OpenAICompletionsLLM;
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};
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// Extract model types for each provider
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export type GoogleModel = keyof typeof PROVIDERS.google.models;
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export type OpenAIModel = keyof typeof PROVIDERS.openai.models;
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export type AnthropicModel = keyof typeof PROVIDERS.anthropic.models;
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export type XAIModel = keyof typeof PROVIDERS.xai.models;
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export type GroqModel = keyof typeof PROVIDERS.groq.models;
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export type CerebrasModel = keyof typeof PROVIDERS.cerebras.models;
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export type OpenRouterModel = keyof typeof PROVIDERS.openrouter.models;
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// Map providers to their model types
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export type ProviderModels = {
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google: GoogleModel;
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openai: OpenAIModel;
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anthropic: AnthropicModel;
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xai: XAIModel;
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groq: GroqModel;
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cerebras: CerebrasModel;
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openrouter: OpenRouterModel;
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};
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// Single generic factory function
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export function createLLM<P extends keyof typeof PROVIDERS, M extends keyof (typeof PROVIDERS)[P]["models"]>(
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provider: P,
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model: M,
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apiKey?: string,
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): ProviderToLLM[P] {
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const config = PROVIDER_CONFIG[provider as keyof typeof PROVIDER_CONFIG];
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if (!config) throw new Error(`Unknown provider: ${provider}`);
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const providerData = PROVIDERS[provider];
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if (!providerData) throw new Error(`Unknown provider: ${provider}`);
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// Type-safe model lookup
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const models = providerData.models as Record<string, Model>;
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const modelData = models[model as string];
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if (!modelData) throw new Error(`Unknown model: ${String(model)} for provider ${provider}`);
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const key = apiKey || process.env[config.envKey];
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if (!key) throw new Error(`No API key provided for ${provider}. Set ${config.envKey} or pass apiKey.`);
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return config.create(model as string, key) as ProviderToLLM[P];
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}
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export interface ProviderInfo {
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id: string;
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env?: string[];
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npm?: string;
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api?: string;
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name: string;
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doc?: string;
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models: Record<string, ModelInfo>;
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}
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export type ModelsData = Record<string, ProviderInfo>;
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let cachedModels: ModelsData | null = null;
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/**
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* Load models data from models.json
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* The file is loaded relative to this module's location
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*/
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export function loadModels(): ModelsData {
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if (cachedModels) {
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return cachedModels;
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}
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try {
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// Get the directory of this module
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const currentDir = dirname(fileURLToPath(import.meta.url));
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const modelsPath = join(currentDir, "models.json");
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const data = readFileSync(modelsPath, "utf-8");
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cachedModels = JSON.parse(data);
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return cachedModels!;
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} catch (error) {
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console.error("Failed to load models.json:", error);
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// Return empty providers object as fallback
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return {};
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}
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}
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/**
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* Get information about a specific model
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*/
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export function getModelInfo(modelId: string): ModelInfo | undefined {
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const data = loadModels();
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// Search through all providers
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for (const provider of Object.values(data)) {
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if (provider.models && provider.models[modelId]) {
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return provider.models[modelId];
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}
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}
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return undefined;
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}
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/**
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* Get all models for a specific provider
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*/
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export function getProviderModels(providerId: string): ModelInfo[] {
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const data = loadModels();
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const provider = data[providerId];
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if (!provider || !provider.models) {
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return [];
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}
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return Object.values(provider.models);
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}
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/**
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* Get provider information
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*/
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export function getProviderInfo(providerId: string): ProviderInfo | undefined {
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const data = loadModels();
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return data[providerId];
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}
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/**
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* Check if a model supports thinking/reasoning
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*/
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export function supportsThinking(modelId: string): boolean {
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const model = getModelInfo(modelId);
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return model?.reasoning === true;
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}
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/**
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* Check if a model supports tool calling
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*/
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export function supportsTools(modelId: string): boolean {
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const model = getModelInfo(modelId);
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return model?.tool_call === true;
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}
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/**
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* Get all available providers
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*/
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export function getAllProviders(): ProviderInfo[] {
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const data = loadModels();
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return Object.values(data);
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}
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// Re-export Model type for convenience
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export type { Model };
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@ -17,7 +17,7 @@ import type {
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ToolCall,
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} from "../types.js";
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export interface GeminiLLMOptions extends LLMOptions {
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export interface GoogleLLMOptions extends LLMOptions {
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toolChoice?: "auto" | "none" | "any";
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thinking?: {
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enabled: boolean;
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@ -25,7 +25,7 @@ export interface GeminiLLMOptions extends LLMOptions {
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};
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}
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export class GeminiLLM implements LLM<GeminiLLMOptions> {
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export class GoogleLLM implements LLM<GoogleLLMOptions> {
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private client: GoogleGenAI;
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private model: string;
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this.model = model;
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}
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async complete(context: Context, options?: GeminiLLMOptions): Promise<AssistantMessage> {
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async complete(context: Context, options?: GoogleLLMOptions): Promise<AssistantMessage> {
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try {
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const contents = this.convertMessages(context.messages);
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@ -106,3 +106,20 @@ export interface TokenUsage {
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}
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export type StopReason = "stop" | "length" | "toolUse" | "safety" | "error";
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// Model interface for the unified model system
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export interface Model {
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id: string;
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name: string;
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provider: string;
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reasoning: boolean;
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input: ("text" | "image")[];
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cost: {
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input: number; // $/million tokens
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output: number; // $/million tokens
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cacheRead: number; // $/million tokens
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cacheWrite: number; // $/million tokens
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};
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contextWindow: number;
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maxTokens: number;
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}
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