mirror of
https://github.com/getcompanion-ai/co-mono.git
synced 2026-04-17 03:03:44 +00:00
Massive refactor of API
- Switch to function based API - Anthropic SDK style async generator - Fully typed with escape hatches for custom models
This commit is contained in:
Mario Zechner
parent
004de3c9d0
commit
66cefb236e
29 changed files with 5835 additions and 6225 deletions
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@ -3,6 +3,7 @@
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import { writeFileSync } from "fs";
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import { join, dirname } from "path";
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import { fileURLToPath } from "url";
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import { Api, KnownProvider, Model } from "../src/types.js";
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const __filename = fileURLToPath(import.meta.url);
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const __dirname = dirname(__filename);
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@ -28,30 +29,13 @@ interface ModelsDevModel {
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};
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}
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interface NormalizedModel {
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id: string;
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name: string;
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provider: string;
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baseUrl?: 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;
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output: number;
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cacheRead: number;
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cacheWrite: number;
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};
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contextWindow: number;
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maxTokens: number;
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}
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async function fetchOpenRouterModels(): Promise<NormalizedModel[]> {
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async function fetchOpenRouterModels(): Promise<Model<any>[]> {
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try {
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console.log("Fetching models from OpenRouter API...");
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const response = await fetch("https://openrouter.ai/api/v1/models");
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const data = await response.json();
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const models: NormalizedModel[] = [];
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const models: Model<any>[] = [];
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for (const model of data.data) {
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// Only include models that support tools
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@ -59,27 +43,17 @@ async function fetchOpenRouterModels(): Promise<NormalizedModel[]> {
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// Parse provider from model ID
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const [providerPrefix] = model.id.split("/");
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let provider = "";
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let provider: KnownProvider = "openrouter";
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let modelKey = model.id;
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// Skip models that we get from models.dev (Anthropic, Google, OpenAI)
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if (model.id.startsWith("google/") ||
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model.id.startsWith("openai/") ||
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model.id.startsWith("anthropic/")) {
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continue;
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} else if (model.id.startsWith("x-ai/")) {
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provider = "xai";
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modelKey = model.id.replace("x-ai/", "");
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} else {
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// All other models go through OpenRouter
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provider = "openrouter";
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modelKey = model.id; // Keep full ID for OpenRouter
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}
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// Skip if not one of our supported providers from OpenRouter
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if (!["xai", "openrouter"].includes(provider)) {
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model.id.startsWith("anthropic/") ||
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model.id.startsWith("x-ai/")) {
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continue;
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}
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modelKey = model.id; // Keep full ID for OpenRouter
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// Parse input modalities
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const input: ("text" | "image")[] = ["text"];
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@ -93,9 +67,11 @@ async function fetchOpenRouterModels(): Promise<NormalizedModel[]> {
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const cacheReadCost = parseFloat(model.pricing?.input_cache_read || "0") * 1_000_000;
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const cacheWriteCost = parseFloat(model.pricing?.input_cache_write || "0") * 1_000_000;
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const normalizedModel: NormalizedModel = {
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const normalizedModel: Model<any> = {
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id: modelKey,
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name: model.name,
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api: "openai-completions",
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baseUrl: "https://openrouter.ai/api/v1",
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provider,
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reasoning: model.supported_parameters?.includes("reasoning") || false,
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input,
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@ -108,14 +84,6 @@ async function fetchOpenRouterModels(): Promise<NormalizedModel[]> {
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contextWindow: model.context_length || 4096,
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maxTokens: model.top_provider?.max_completion_tokens || 4096,
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};
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// Add baseUrl for providers that need it
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if (provider === "xai") {
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normalizedModel.baseUrl = "https://api.x.ai/v1";
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} else if (provider === "openrouter") {
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normalizedModel.baseUrl = "https://openrouter.ai/api/v1";
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}
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models.push(normalizedModel);
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}
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@ -127,13 +95,13 @@ async function fetchOpenRouterModels(): Promise<NormalizedModel[]> {
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}
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}
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async function loadModelsDevData(): Promise<NormalizedModel[]> {
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async function loadModelsDevData(): Promise<Model<any>[]> {
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try {
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console.log("Fetching models from models.dev API...");
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const response = await fetch("https://models.dev/api.json");
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const data = await response.json();
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const models: NormalizedModel[] = [];
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const models: Model<any>[] = [];
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// Process Anthropic models
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if (data.anthropic?.models) {
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@ -144,7 +112,9 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "anthropic-messages",
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provider: "anthropic",
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baseUrl: "https://api.anthropic.com",
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reasoning: m.reasoning === true,
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input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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@ -168,7 +138,9 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "google-generative-ai",
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provider: "google",
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baseUrl: "https://generativelanguage.googleapis.com/v1beta",
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reasoning: m.reasoning === true,
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input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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@ -192,7 +164,9 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "openai-responses",
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provider: "openai",
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baseUrl: "https://api.openai.com/v1",
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reasoning: m.reasoning === true,
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input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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@ -216,6 +190,7 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "openai-completions",
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provider: "groq",
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baseUrl: "https://api.groq.com/openai/v1",
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reasoning: m.reasoning === true,
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@ -241,6 +216,7 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "openai-completions",
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provider: "cerebras",
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baseUrl: "https://api.cerebras.ai/v1",
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reasoning: m.reasoning === true,
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@ -257,6 +233,32 @@ async function loadModelsDevData(): Promise<NormalizedModel[]> {
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}
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}
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// Process xAi models
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if (data.xai?.models) {
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for (const [modelId, model] of Object.entries(data.xai.models)) {
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const m = model as ModelsDevModel;
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if (m.tool_call !== true) continue;
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "openai-completions",
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provider: "xai",
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baseUrl: "https://api.x.ai/v1",
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reasoning: m.reasoning === true,
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input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: m.cost?.input || 0,
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output: m.cost?.output || 0,
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cacheRead: m.cost?.cache_read || 0,
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cacheWrite: m.cost?.cache_write || 0,
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},
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contextWindow: m.limit?.context || 4096,
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maxTokens: m.limit?.output || 4096,
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});
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}
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}
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console.log(`Loaded ${models.length} tool-capable models from models.dev`);
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return models;
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} catch (error) {
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@ -280,6 +282,8 @@ async function generateModels() {
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allModels.push({
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id: "gpt-5-chat-latest",
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name: "GPT-5 Chat Latest",
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api: "openai-responses",
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baseUrl: "https://api.openai.com/v1",
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provider: "openai",
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reasoning: false,
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input: ["text", "image"],
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@ -294,8 +298,29 @@ async function generateModels() {
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});
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}
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// Add missing Grok models
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if (!allModels.some(m => m.provider === "xai" && m.id === "grok-code-fast-1")) {
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allModels.push({
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id: "grok-code-fast-1",
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name: "Grok Code Fast 1",
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api: "openai-completions",
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baseUrl: "https://api.x.ai/v1",
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provider: "xai",
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reasoning: false,
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input: ["text"],
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cost: {
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input: 0.2,
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output: 1.5,
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cacheRead: 0.02,
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cacheWrite: 0,
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},
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contextWindow: 32768,
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maxTokens: 8192,
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});
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}
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// Group by provider and deduplicate by model ID
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const providers: Record<string, Record<string, NormalizedModel>> = {};
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const providers: Record<string, Record<string, Model<any>>> = {};
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for (const model of allModels) {
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if (!providers[model.provider]) {
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providers[model.provider] = {};
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@ -319,39 +344,33 @@ export const PROVIDERS = {
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// Generate provider sections
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for (const [providerId, models] of Object.entries(providers)) {
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output += `\t${providerId}: {\n`;
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output += `\t\tmodels: {\n`;
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for (const model of Object.values(models)) {
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output += `\t\t\t"${model.id}": {\n`;
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output += `\t\t\t\tid: "${model.id}",\n`;
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output += `\t\t\t\tname: "${model.name}",\n`;
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output += `\t\t\t\tprovider: "${model.provider}",\n`;
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output += `\t\t"${model.id}": {\n`;
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output += `\t\t\tid: "${model.id}",\n`;
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output += `\t\t\tname: "${model.name}",\n`;
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output += `\t\t\tapi: "${model.api}",\n`;
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output += `\t\t\tprovider: "${model.provider}",\n`;
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if (model.baseUrl) {
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output += `\t\t\t\tbaseUrl: "${model.baseUrl}",\n`;
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output += `\t\t\tbaseUrl: "${model.baseUrl}",\n`;
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}
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output += `\t\t\t\treasoning: ${model.reasoning},\n`;
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output += `\t\t\t\tinput: ${JSON.stringify(model.input)},\n`;
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output += `\t\t\t\tcost: {\n`;
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output += `\t\t\t\t\tinput: ${model.cost.input},\n`;
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output += `\t\t\t\t\toutput: ${model.cost.output},\n`;
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output += `\t\t\t\t\tcacheRead: ${model.cost.cacheRead},\n`;
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output += `\t\t\t\t\tcacheWrite: ${model.cost.cacheWrite},\n`;
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output += `\t\t\t\t},\n`;
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output += `\t\t\t\tcontextWindow: ${model.contextWindow},\n`;
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output += `\t\t\t\tmaxTokens: ${model.maxTokens},\n`;
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output += `\t\t\t} satisfies Model,\n`;
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output += `\t\t\treasoning: ${model.reasoning},\n`;
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output += `\t\t\tinput: [${model.input.map(i => `"${i}"`).join(", ")}],\n`;
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output += `\t\t\tcost: {\n`;
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output += `\t\t\t\tinput: ${model.cost.input},\n`;
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output += `\t\t\t\toutput: ${model.cost.output},\n`;
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output += `\t\t\t\tcacheRead: ${model.cost.cacheRead},\n`;
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output += `\t\t\t\tcacheWrite: ${model.cost.cacheWrite},\n`;
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output += `\t\t\t},\n`;
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output += `\t\t\tcontextWindow: ${model.contextWindow},\n`;
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output += `\t\t\tmaxTokens: ${model.maxTokens},\n`;
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output += `\t\t} satisfies Model<"${model.api}">,\n`;
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}
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output += `\t\t}\n`;
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output += `\t},\n`;
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}
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output += `} as const;
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// Helper type to extract models for each provider
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export type ProviderModels = {
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[K in keyof typeof PROVIDERS]: typeof PROVIDERS[K]["models"]
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};
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`;
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// Write file
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