feat: add MiniMax as alternative LLM provider (M2.7 default)

README.md

@@ -47,7 +47,8 @@ You can deploy your own version of Novel to Vercel with one click:
 
 To set up Novel locally, you'll need to clone the repository and set up the following environment variables:
 
-- `OPENAI_API_KEY` – your OpenAI API key (you can get one [here](https://platform.openai.com/account/api-keys))
+- `OPENAI_API_KEY` – your OpenAI API key (you can get one [here](https://platform.openai.com/account/api-keys)), **or**
+- `MINIMAX_API_KEY` – your MiniMax API key (you can get one [here](https://platform.minimax.io)). When set, MiniMax takes priority over OpenAI. Supported models: `MiniMax-M2.7` (default), `MiniMax-M2.7-highspeed`, `MiniMax-M2.5`, `MiniMax-M2.5-highspeed`.
 - `BLOB_READ_WRITE_TOKEN` – your Vercel Blob read/write token (currently [still in beta](https://vercel.com/docs/storage/vercel-blob/quickstart#quickstart), but feel free to [sign up on this form](https://vercel.fyi/blob-beta) for access)
 
 If you've deployed this to Vercel, you can also use [`vc env pull`](https://vercel.com/docs/cli/env#exporting-development-environment-variables) to pull the environment variables from your Vercel project.
@@ -78,7 +79,7 @@ Novel is built on the following stack:
 
 - [Next.js](https://nextjs.org/) – framework
 - [Tiptap](https://tiptap.dev/) – text editor
-- [OpenAI](https://openai.com/) - AI completions
+- [OpenAI](https://openai.com/) / [MiniMax](https://www.minimax.io/) - AI completions
 - [Vercel AI SDK](https://sdk.vercel.ai/docs) – AI library
 - [Vercel](https://vercel.com) – deployments
 - [TailwindCSS](https://tailwindcss.com/) – styles

apps/web/.env.example

@@ -2,10 +2,21 @@
 # secrets in it. If you are cloning this repo, create a copy of this file named
 # ".env" and populate it with your secrets.
 
+# --- LLM Provider (pick ONE) ---
+
+# Option 1: OpenAI (default)
 # Get your OpenAI API key here: https://platform.openai.com/account/api-keys
 OPENAI_API_KEY=
-# OPTIONAL: OpenAI Base URL (default to https://api.openai.com/v1)
-OPENAI_BASE_URL=
+# OPTIONAL: Override the default model (default: gpt-4o-mini)
+# OPENAI_MODEL=gpt-4o-mini
+
+# Option 2: MiniMax (OpenAI-compatible)
+# Get your MiniMax API key here: https://platform.minimax.io
+# When MINIMAX_API_KEY is set it takes priority over OpenAI.
+# MINIMAX_API_KEY=
+# OPTIONAL: Override the default model (default: MiniMax-M2.7)
+# Supported models: MiniMax-M2.7, MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed
+# MINIMAX_MODEL=MiniMax-M2.7
 
 # OPTIONAL: Vercel Blob (for uploading images)
 # Get your Vercel Blob credentials here: https://vercel.com/docs/storage/vercel-blob/quickstart#quickstart

apps/web/__tests__/ai-provider.integration.test.ts

@@ -0,0 +1,103 @@
+import { describe, it, expect, beforeAll } from "vitest";
+import { createOpenAI } from "@ai-sdk/openai";
+import { generateText } from "ai";
+
+/**
+ * Integration tests that call the MiniMax API.
+ * Requires MINIMAX_API_KEY to be set in the environment.
+ *
+ * Run with:
+ *   MINIMAX_API_KEY=<key> pnpm vitest run __tests__/ai-provider.integration.test.ts
+ */
+describe("MiniMax integration", () => {
+  const apiKey = process.env.MINIMAX_API_KEY;
+
+  beforeAll(() => {
+    if (!apiKey) {
+      console.warn("Skipping integration tests: MINIMAX_API_KEY not set");
+    }
+  });
+
+  it.skipIf(!apiKey)("generates text with MiniMax-M2.7", async () => {
+    const minimax = createOpenAI({
+      baseURL: "https://api.minimax.io/v1",
+      apiKey: apiKey!,
+    });
+
+    const result = await generateText({
+      model: minimax("MiniMax-M2.7"),
+      prompt: "Say hello in exactly 5 words.",
+      maxTokens: 64,
+      temperature: 0.7,
+    });
+
+    expect(result.text).toBeTruthy();
+    expect(result.text.length).toBeGreaterThan(0);
+    console.log("MiniMax-M2.7 response:", result.text);
+  }, 30000);
+
+  it.skipIf(!apiKey)("generates text with MiniMax-M2.7-highspeed", async () => {
+    const minimax = createOpenAI({
+      baseURL: "https://api.minimax.io/v1",
+      apiKey: apiKey!,
+    });
+
+    const result = await generateText({
+      model: minimax("MiniMax-M2.7-highspeed"),
+      prompt: "What is 2+2? Reply with just the number.",
+      maxTokens: 128,
+      temperature: 0.7,
+    });
+
+    expect(result.text).toBeTruthy();
+    // Strip potential thinking tokens before checking
+    const answer = result.text.replace(/<think>[\s\S]*?<\/think>\s*/g, "").trim();
+    expect(answer).toContain("4");
+    console.log("MiniMax-M2.7-highspeed response:", answer);
+  }, 30000);
+
+  it.skipIf(!apiKey)("generates text with MiniMax-M2.5 (legacy)", async () => {
+    const minimax = createOpenAI({
+      baseURL: "https://api.minimax.io/v1",
+      apiKey: apiKey!,
+    });
+
+    const result = await generateText({
+      model: minimax("MiniMax-M2.5"),
+      prompt: "Say hello in exactly 5 words.",
+      maxTokens: 64,
+      temperature: 0.7,
+    });
+
+    expect(result.text).toBeTruthy();
+    expect(result.text.length).toBeGreaterThan(0);
+    console.log("MiniMax-M2.5 response:", result.text);
+  }, 30000);
+
+  it.skipIf(!apiKey)("streams text with MiniMax-M2.7", async () => {
+    const { streamText } = await import("ai");
+    const minimax = createOpenAI({
+      baseURL: "https://api.minimax.io/v1",
+      apiKey: apiKey!,
+    });
+
+    const result = await streamText({
+      model: minimax("MiniMax-M2.7"),
+      prompt: "Count from 1 to 5, one number per line.",
+      maxTokens: 64,
+      temperature: 0.7,
+    });
+
+    let fullText = "";
+    for await (const chunk of result.textStream) {
+      fullText += chunk;
+    }
+
+    expect(fullText).toBeTruthy();
+    // Strip thinking tokens if present
+    const answer = fullText.replace(/<think>[\s\S]*?<\/think>\s*/g, "").trim();
+    expect(answer).toBeTruthy();
+    expect(answer).toContain("1");
+    console.log("MiniMax streaming response:", answer);
+  }, 60000);
+});

apps/web/__tests__/ai-provider.test.ts

@@ -0,0 +1,97 @@
+import { describe, it, expect, vi, beforeEach, afterEach } from "vitest";
+import { getModel, getTemperature, hasApiKey } from "@/lib/ai-provider";
+
+// Save original env
+const originalEnv = { ...process.env };
+
+beforeEach(() => {
+  // Clear provider env vars before each test
+  delete process.env.OPENAI_API_KEY;
+  delete process.env.MINIMAX_API_KEY;
+  delete process.env.OPENAI_MODEL;
+  delete process.env.MINIMAX_MODEL;
+});
+
+afterEach(() => {
+  process.env = { ...originalEnv };
+});
+
+describe("hasApiKey", () => {
+  it("returns false when no API key is set", () => {
+    expect(hasApiKey()).toBe(false);
+  });
+
+  it("returns true when OPENAI_API_KEY is set", () => {
+    process.env.OPENAI_API_KEY = "sk-test-openai-key";
+    expect(hasApiKey()).toBe(true);
+  });
+
+  it("returns true when MINIMAX_API_KEY is set", () => {
+    process.env.MINIMAX_API_KEY = "sk-test-minimax-key";
+    expect(hasApiKey()).toBe(true);
+  });
+
+  it("returns true when both keys are set", () => {
+    process.env.OPENAI_API_KEY = "sk-test-openai-key";
+    process.env.MINIMAX_API_KEY = "sk-test-minimax-key";
+    expect(hasApiKey()).toBe(true);
+  });
+});
+
+describe("getTemperature", () => {
+  it("returns the base temperature when using OpenAI", () => {
+    process.env.OPENAI_API_KEY = "sk-test";
+    expect(getTemperature(0.7)).toBe(0.7);
+    expect(getTemperature(0)).toBe(0);
+    expect(getTemperature(1.5)).toBe(1.5);
+  });
+
+  it("clamps temperature to (0.0, 1.0] for MiniMax", () => {
+    process.env.MINIMAX_API_KEY = "sk-test";
+    // Normal value in range
+    expect(getTemperature(0.7)).toBe(0.7);
+    // Zero should be clamped to 0.01
+    expect(getTemperature(0)).toBe(0.01);
+    // Negative should be clamped to 0.01
+    expect(getTemperature(-0.5)).toBe(0.01);
+    // Values above 1.0 should be clamped to 1.0
+    expect(getTemperature(1.5)).toBe(1.0);
+    // Exactly 1.0 is valid
+    expect(getTemperature(1.0)).toBe(1.0);
+  });
+});
+
+describe("getModel", () => {
+  it("returns an OpenAI model when OPENAI_API_KEY is set", () => {
+    process.env.OPENAI_API_KEY = "sk-test-openai";
+    const model = getModel();
+    expect(model.modelId).toBe("gpt-4o-mini");
+  });
+
+  it("allows overriding OpenAI model via OPENAI_MODEL", () => {
+    process.env.OPENAI_API_KEY = "sk-test-openai";
+    process.env.OPENAI_MODEL = "gpt-4o";
+    const model = getModel();
+    expect(model.modelId).toBe("gpt-4o");
+  });
+
+  it("returns a MiniMax model when MINIMAX_API_KEY is set", () => {
+    process.env.MINIMAX_API_KEY = "sk-test-minimax";
+    const model = getModel();
+    expect(model.modelId).toBe("MiniMax-M2.7");
+  });
+
+  it("allows overriding MiniMax model via MINIMAX_MODEL", () => {
+    process.env.MINIMAX_API_KEY = "sk-test-minimax";
+    process.env.MINIMAX_MODEL = "MiniMax-M2.5-highspeed";
+    const model = getModel();
+    expect(model.modelId).toBe("MiniMax-M2.5-highspeed");
+  });
+
+  it("prioritizes MiniMax over OpenAI when both keys are set", () => {
+    process.env.OPENAI_API_KEY = "sk-test-openai";
+    process.env.MINIMAX_API_KEY = "sk-test-minimax";
+    const model = getModel();
+    expect(model.modelId).toBe("MiniMax-M2.7");
+  });
+});

apps/web/app/api/generate/route.ts

@@ -1,18 +1,19 @@
-import { openai } from "@ai-sdk/openai";
 import { Ratelimit } from "@upstash/ratelimit";
 import { kv } from "@vercel/kv";
 import { streamText } from "ai";
 import { match } from "ts-pattern";
+import { getModel, getTemperature, hasApiKey } from "@/lib/ai-provider";
 
 // IMPORTANT! Set the runtime to edge: https://vercel.com/docs/functions/edge-functions/edge-runtime
 export const runtime = "edge";
 
 export async function POST(req: Request): Promise<Response> {
-  // Check if the OPENAI_API_KEY is set, if not return 400
-  if (!process.env.OPENAI_API_KEY || process.env.OPENAI_API_KEY === "") {
-    return new Response("Missing OPENAI_API_KEY - make sure to add it to your .env file.", {
-      status: 400,
-    });
+  // Check if an API key is set (supports OpenAI or MiniMax)
+  if (!hasApiKey()) {
+    return new Response(
+      "Missing API key – set OPENAI_API_KEY or MINIMAX_API_KEY in your .env file.",
+      { status: 400 },
+    );
   }
   if (process.env.KV_REST_API_URL && process.env.KV_REST_API_TOKEN) {
     const ip = req.headers.get("x-forwarded-for");
@@ -118,11 +119,11 @@ export async function POST(req: Request): Promise<Response> {
   const result = await streamText({
     prompt: messages[messages.length - 1].content,
     maxTokens: 4096,
-    temperature: 0.7,
+    temperature: getTemperature(0.7),
     topP: 1,
     frequencyPenalty: 0,
     presencePenalty: 0,
-    model: openai("gpt-4o-mini"),
+    model: getModel(),
   });
 
   return result.toDataStreamResponse();

apps/web/lib/ai-provider.ts

@@ -0,0 +1,44 @@
+import { createOpenAI } from "@ai-sdk/openai";
+
+/**
+ * Returns the configured LLM model for AI completions.
+ *
+ * Provider priority:
+ *   1. If MINIMAX_API_KEY is set → MiniMax (MiniMax-M2.7)
+ *   2. If OPENAI_API_KEY is set  → OpenAI  (gpt-4o-mini)
+ *
+ * MiniMax uses an OpenAI-compatible API, so we reuse @ai-sdk/openai
+ * with a custom baseURL and apiKey.
+ */
+export function getModel() {
+  if (process.env.MINIMAX_API_KEY) {
+    const minimax = createOpenAI({
+      baseURL: "https://api.minimax.io/v1",
+      apiKey: process.env.MINIMAX_API_KEY,
+    });
+    return minimax(process.env.MINIMAX_MODEL ?? "MiniMax-M2.7");
+  }
+
+  const openai = createOpenAI({
+    apiKey: process.env.OPENAI_API_KEY,
+  });
+  return openai(process.env.OPENAI_MODEL ?? "gpt-4o-mini");
+}
+
+/**
+ * Clamp temperature for MiniMax: must be in (0.0, 1.0].
+ * OpenAI accepts 0–2, so no clamping needed for OpenAI.
+ */
+export function getTemperature(base: number): number {
+  if (process.env.MINIMAX_API_KEY) {
+    return Math.max(0.01, Math.min(base, 1.0));
+  }
+  return base;
+}
+
+/**
+ * Returns true when an LLM API key is configured (either provider).
+ */
+export function hasApiKey(): boolean {
+  return !!(process.env.MINIMAX_API_KEY || process.env.OPENAI_API_KEY);
+}

apps/web/package.json

@@ -53,6 +53,7 @@
     "@types/react": "^18.2.61",
     "@types/react-dom": "18.2.19",
     "tailwindcss": "^3.4.1",
-    "tsconfig": "workspace:*"
+    "tsconfig": "workspace:*",
+    "vitest": "^4.1.0"
   }
 }

apps/web/vitest.config.ts

@@ -0,0 +1,13 @@
+import { defineConfig } from "vitest/config";
+import path from "path";
+
+export default defineConfig({
+  test: {
+    globals: true,
+  },
+  resolve: {
+    alias: {
+      "@": path.resolve(__dirname, "."),
+    },
+  },
+});