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feat: add Ambient provider with GLM-5.1 and Kimi K2.6
Adds the Ambient inference provider (api.ambient.xyz) with an initial catalog of GLM-5.1 and Kimi K2.6, plus a generator script that pulls from /v1/models so pricing and limits stay in sync with the upstream API. Run `bun run ambient:generate` to refresh model TOMLs.
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‎package.json‎

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"venice:generate": "bun ./packages/core/script/generate-venice.ts",
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"vercel:generate": "bun ./packages/core/script/generate-vercel.ts",
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"wandb:generate": "bun ./packages/core/script/generate-wandb.ts",
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"digitalocean:generate": "bun ./packages/core/script/generate-digitalocean.ts"
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"digitalocean:generate": "bun ./packages/core/script/generate-digitalocean.ts",
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"ambient:generate": "bun ./packages/core/script/generate-ambient.ts"
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},
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"dependencies": {
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"@cloudflare/workers-types": "^4.20260424.1",

‎packages/core/script/generate-ambient.ts‎

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#!/usr/bin/env bun
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/**
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* Generates Ambient model TOML files from https://api.ambient.xyz/v1/models.
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*
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* Emits `[extends]`-format TOMLs that inherit upstream metadata
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* (family, release_date, knowledge, capabilities) from the canonical
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* provider model, and override only the fields Ambient's API reports:
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* cost, limit, modalities.
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*
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* Flags:
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* --dry-run Preview generated TOMLs without writing files.
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*/
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import { z } from "zod";
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import path from "node:path";
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import { mkdir } from "node:fs/promises";
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const API_ENDPOINT = "https://api.ambient.xyz/v1/models";
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// Allowlist for the initial rollout.
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const ALLOWLIST = new Set<string>([
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"zai-org/GLM-5.1-FP8",
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"moonshotai/kimi-k2.6",
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]);
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// Maps Ambient model IDs to canonical <provider>/<model> in this repo.
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// The generated TOML uses this path as `[extends].from` so capabilities
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// and metadata propagate from the upstream provider automatically.
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const EXTENDS_MAP: Record<string, string> = {
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"zai-org/GLM-5.1-FP8": "zai/glm-5.1",
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"moonshotai/kimi-k2.6": "moonshotai/kimi-k2.6",
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};
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const Pricing = z
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.object({
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prompt: z.string(),
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completion: z.string(),
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input_cache_read: z.string().optional(),
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input_cache_write: z.string().optional(),
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})
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.passthrough();
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const AmbientModel = z
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.object({
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id: z.string(),
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name: z.string(),
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context_length: z.number(),
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max_output_length: z.number(),
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input_modalities: z.array(z.string()),
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output_modalities: z.array(z.string()),
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pricing: Pricing,
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})
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.passthrough();
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const AmbientResponse = z
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.object({
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object: z.literal("list"),
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data: z.array(AmbientModel),
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})
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.passthrough();
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const ALLOWED_MODALITIES = new Set(["text", "audio", "image", "video", "pdf"]);
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function modalities(values: string[]): string[] {
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return values
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.map((v) => v.toLowerCase())
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.filter((v) => ALLOWED_MODALITIES.has(v));
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}
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function perMTok(price: string): number {
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const n = parseFloat(price);
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if (!Number.isFinite(n)) {
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throw new Error(`Invalid price: ${price}`);
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}
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// Round to 6 decimals to absorb float noise from per-token strings.
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return Math.round(n * 1_000_000 * 1_000_000) / 1_000_000;
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}
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function formatToml(
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model: z.infer<typeof AmbientModel>,
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extendsFrom: string,
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): string {
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const lines: string[] = [];
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lines.push("[extends]");
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lines.push(`from = "${extendsFrom}"`);
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lines.push("");
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lines.push("[cost]");
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lines.push(`input = ${perMTok(model.pricing.prompt)}`);
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lines.push(`output = ${perMTok(model.pricing.completion)}`);
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if (model.pricing.input_cache_read !== undefined) {
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lines.push(`cache_read = ${perMTok(model.pricing.input_cache_read)}`);
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}
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if (model.pricing.input_cache_write !== undefined) {
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lines.push(`cache_write = ${perMTok(model.pricing.input_cache_write)}`);
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}
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lines.push("");
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lines.push("[limit]");
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lines.push(`context = ${model.context_length}`);
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lines.push(`output = ${model.max_output_length}`);
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lines.push("");
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const input = modalities(model.input_modalities);
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const output = modalities(model.output_modalities);
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lines.push("[modalities]");
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lines.push(`input = [${input.map((m) => `"${m}"`).join(", ")}]`);
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lines.push(`output = [${output.map((m) => `"${m}"`).join(", ")}]`);
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return lines.join("\n") + "\n";
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}
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async function main() {
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const dryRun = process.argv.includes("--dry-run");
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const outDir = path.join(
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import.meta.dirname,
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"..",
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"..",
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"..",
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"providers",
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"ambient",
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"models",
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);
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const res = await fetch(API_ENDPOINT);
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if (!res.ok) {
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console.error(`Fetch failed: ${res.status} ${res.statusText}`);
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process.exit(1);
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}
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const parsed = AmbientResponse.safeParse(await res.json());
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if (!parsed.success) {
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console.error("Invalid Ambient response:", parsed.error.issues);
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process.exit(1);
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}
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const selected = parsed.data.data.filter((m) => ALLOWLIST.has(m.id));
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const missing = [...ALLOWLIST].filter(
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(id) => !selected.some((m) => m.id === id),
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);
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if (missing.length > 0) {
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console.error(`Allowlisted models missing from API: ${missing.join(", ")}`);
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process.exit(1);
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}
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let count = 0;
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for (const model of selected) {
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const extendsFrom = EXTENDS_MAP[model.id];
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if (!extendsFrom) {
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console.error(`No EXTENDS_MAP entry for ${model.id}; skipping`);
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continue;
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}
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const filePath = path.join(outDir, `${model.id}.toml`);
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const toml = formatToml(model, extendsFrom);
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if (dryRun) {
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console.log(`--- ${path.relative(process.cwd(), filePath)} ---`);
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console.log(toml);
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} else {
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await mkdir(path.dirname(filePath), { recursive: true });
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await Bun.write(filePath, toml);
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}
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count++;
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}
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console.log(
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`${dryRun ? "Previewed" : "Wrote"} ${count} model file(s) under providers/ambient/models/`,
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);
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}
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await main();

‎providers/ambient/logo.svg‎

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‎providers/ambient/models/moonshotai/kimi-k2.6.toml‎

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[extends]
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from = "moonshotai/kimi-k2.6"
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[cost]
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input = 0.95
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output = 4
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cache_read = 0.2
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cache_write = 0
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[limit]
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context = 262144
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output = 262144
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[modalities]
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input = ["text", "image"]
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output = ["text"]

‎providers/ambient/models/zai-org/GLM-5.1-FP8.toml‎

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[extends]
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from = "zai/glm-5.1"
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[cost]
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input = 1.4
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output = 4.4
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cache_read = 0
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cache_write = 0
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[limit]
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context = 202752
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output = 131072
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[modalities]
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input = ["text"]
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output = ["text"]

‎providers/ambient/provider.toml‎

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name = "Ambient"
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env = ["AMBIENT_API_KEY"]
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npm = "@ai-sdk/openai-compatible"
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api = "https://api.ambient.xyz/v1"
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doc = "https://ambient.xyz"

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