feat: add MiniMax as first-class LLM provider

.env.example

@@ -1,7 +1,7 @@
 # InkOS Environment Configuration
 # Copy to .env and fill in your values
 
-# LLM Provider (openai, anthropic, custom)
+# LLM Provider (openai, anthropic, minimax, custom)
 INKOS_LLM_PROVIDER=openai
 
 # API Base URL (OpenAI-compatible endpoint)
@@ -13,6 +13,12 @@ INKOS_LLM_API_KEY=sk-your-key-here
 # Model name
 INKOS_LLM_MODEL=gpt-4o
 
+# --- MiniMax example ---
+# INKOS_LLM_PROVIDER=minimax
+# INKOS_LLM_BASE_URL=https://api.minimax.io/v1
+# INKOS_LLM_API_KEY=your-minimax-api-key
+# INKOS_LLM_MODEL=MiniMax-M2.7
+
 # Notifications (optional)
 INKOS_TELEGRAM_BOT_TOKEN=
 INKOS_TELEGRAM_CHAT_ID=

README.en.md

@@ -49,19 +49,22 @@ Once installed, Claw can invoke InkOS atomic commands and control-surface operat
 ```bash
 inkos config set-global \
   --lang en \
-  --provider <openai|anthropic|custom> \
+  --provider <openai|anthropic|minimax|custom> \
   --base-url <API endpoint> \
   --api-key <your API key> \
   --model <model name>
 
-# provider: openai / anthropic / custom (use custom for OpenAI-compatible proxies)
+# provider: openai / anthropic / minimax / custom (use custom for OpenAI-compatible proxies)
 # base-url: your API provider URL
 # api-key: your API key
 # model: your model name
 ```
 
 `--lang en` sets English as the default writing language for all projects. Saved to `~/.inkos/.env`. New projects just work without extra config.
 
+> **MiniMax quick setup:** `inkos config set-global --lang en --provider minimax --base-url https://api.minimax.io/v1 --api-key <key> --model MiniMax-M2.7`
+> Supported models: `MiniMax-M2.7` (latest, 204K context), `MiniMax-M2.7-highspeed` (204K context). Temperature is auto-clamped to (0, 1].
+
 **Option 2: Per-project `.env`**
 
 ```bash
@@ -71,8 +74,8 @@ inkos init my-novel     # Initialize project
 
 ```bash
 # Required
-INKOS_LLM_PROVIDER=                               # openai / anthropic / custom (use custom for any OpenAI-compatible API)
-INKOS_LLM_BASE_URL=                               # API endpoint
+INKOS_LLM_PROVIDER=                               # openai / anthropic / minimax / custom (use custom for any OpenAI-compatible API)
+INKOS_LLM_BASE_URL=                               # API endpoint (supports MiniMax, proxies, etc.)
 INKOS_LLM_API_KEY=                                 # API Key
 INKOS_LLM_MODEL=                                   # Model name
 

README.ja.md

@@ -49,19 +49,22 @@ npm でインストール済み、またはリポジトリをクローン済み
 ```bash
 inkos config set-global \
   --lang en \
-  --provider <openai|anthropic|custom> \
+  --provider <openai|anthropic|minimax|custom> \
   --base-url <APIエンドポイント> \
   --api-key <APIキー> \
   --model <モデル名>
 
-# provider: openai / anthropic / custom（OpenAI互換プロキシにはcustomを使用）
+# provider: openai / anthropic / minimax / custom（OpenAI互換プロキシにはcustomを使用）
 # base-url: APIプロバイダーURL
 # api-key: APIキー
 # model: モデル名
 ```
 
 `--lang en` で英語をすべてのプロジェクトのデフォルト執筆言語に設定。`~/.inkos/.env` に保存されます。新規プロジェクトは追加設定なしですぐに使えます。
 
+> **MiniMax クイック設定：** `inkos config set-global --provider minimax --base-url https://api.minimax.io/v1 --api-key <key> --model MiniMax-M2.7`
+> 対応モデル：`MiniMax-M2.7`（最新、204Kコンテキスト）、`MiniMax-M2.7-highspeed`（204Kコンテキスト）。温度は自動的に (0, 1] に制限されます。
+
 **方法2：プロジェクトごとの `.env`**
 
 ```bash
@@ -71,8 +74,8 @@ inkos init my-novel     # プロジェクトを初期化
 
 ```bash
 # 必須
-INKOS_LLM_PROVIDER=                               # openai / anthropic / custom（OpenAI互換APIにはcustomを使用）
-INKOS_LLM_BASE_URL=                               # APIエンドポイント
+INKOS_LLM_PROVIDER=                               # openai / anthropic / minimax / custom（OpenAI互換APIにはcustomを使用）
+INKOS_LLM_BASE_URL=                               # APIエンドポイント（MiniMax、プロキシ等対応）
 INKOS_LLM_API_KEY=                                 # APIキー
 INKOS_LLM_MODEL=                                   # モデル名
 

README.md

@@ -48,19 +48,22 @@ clawhub install inkos          # 从 ClawHub 安装 InkOS Skill
 
 ```bash
 inkos config set-global \
-  --provider <openai|anthropic|custom> \
+  --provider <openai|anthropic|minimax|custom> \
   --base-url <API 地址> \
   --api-key <你的 API Key> \
   --model <模型名>
 
-# provider: openai / anthropic / custom（兼容 OpenAI 格式的中转站选 custom）
+# provider: openai / anthropic / minimax / custom（兼容 OpenAI 格式的中转站选 custom）
 # base-url: 你的 API 提供商地址
 # api-key: 你的 API Key
 # model: 你的模型名称
 ```
 
 配置保存在 `~/.inkos/.env`，所有项目共享。之后新建项目不用再配。
 
+> **MiniMax 快速配置：** `inkos config set-global --provider minimax --base-url https://api.minimax.io/v1 --api-key <key> --model MiniMax-M2.7`
+> 支持模型：`MiniMax-M2.7`（最新，204K 上下文）、`MiniMax-M2.7-highspeed`（204K 上下文）。温度自动限制在 (0, 1] 范围。
+
 **方式二：项目级 `.env`**
 
 ```bash
@@ -70,8 +73,8 @@ inkos init my-novel     # 初始化项目
 
 ```bash
 # 必填
-INKOS_LLM_PROVIDER=                               # openai / anthropic / custom（兼容 OpenAI 接口的都选 custom）
-INKOS_LLM_BASE_URL=                               # API 地址（支持中转站、智谱、Gemini 等）
+INKOS_LLM_PROVIDER=                               # openai / anthropic / minimax / custom（兼容 OpenAI 接口的都选 custom）
+INKOS_LLM_BASE_URL=                               # API 地址（支持中转站、MiniMax、智谱、Gemini 等）
 INKOS_LLM_API_KEY=                                 # API Key
 INKOS_LLM_MODEL=                                   # 模型名
 

packages/cli/src/commands/config.ts

@@ -87,7 +87,7 @@ configCommand
 configCommand
   .command("set-global")
   .description("Set global LLM config (~/.inkos/.env), shared by all projects")
-  .requiredOption("--provider <provider>", "LLM provider (openai / anthropic)")
+  .requiredOption("--provider <provider>", "LLM provider (openai / anthropic / minimax)")
   .requiredOption("--base-url <url>", "API base URL")
   .requiredOption("--api-key <key>", "API key")
   .requiredOption("--model <model>", "Model name")

packages/cli/src/commands/init.ts

@@ -90,7 +90,7 @@ export const initCommand = new Command("init")
           [
             "# LLM Configuration",
             "# Tip: Run 'inkos config set-global' to set once for all projects.",
-            "# Provider: openai (OpenAI / compatible proxy), anthropic (Anthropic native)",
+            "# Provider: openai (OpenAI / compatible proxy), anthropic (Anthropic native), minimax (MiniMax)",
             "INKOS_LLM_PROVIDER=openai",
             "INKOS_LLM_BASE_URL=",
             "INKOS_LLM_API_KEY=",
@@ -110,6 +110,11 @@ export const initCommand = new Command("init")
             "# INKOS_LLM_PROVIDER=anthropic",
             "# INKOS_LLM_BASE_URL=",
             "# INKOS_LLM_MODEL=",
+            "",
+            "# MiniMax example:",
+            "# INKOS_LLM_PROVIDER=minimax",
+            "# INKOS_LLM_BASE_URL=https://api.minimax.io/v1",
+            "# INKOS_LLM_MODEL=MiniMax-M2.7",
           ].join("\n"),
           "utf-8",
         );

packages/core/src/__tests__/minimax-integration.test.ts

@@ -0,0 +1,57 @@
+/**
+ * Integration tests for MiniMax LLM provider.
+ *
+ * These tests verify the MiniMax integration end-to-end against the real API.
+ * They require the MINIMAX_API_KEY environment variable to be set.
+ *
+ * Run with:
+ *   MINIMAX_API_KEY=<your-key> npx vitest run src/__tests__/minimax-integration.test.ts
+ */
+import { describe, expect, it } from "vitest";
+import { createLLMClient, chatCompletion } from "../llm/provider.js";
+import { LLMConfigSchema } from "../models/project.js";
+
+const MINIMAX_API_KEY = process.env.MINIMAX_API_KEY;
+
+const describeIf = MINIMAX_API_KEY ? describe : describe.skip;
+
+describeIf("MiniMax integration (real API)", () => {
+  const config = LLMConfigSchema.parse({
+    provider: "minimax",
+    baseUrl: "https://api.minimax.io/v1",
+    apiKey: MINIMAX_API_KEY ?? "",
+    model: "MiniMax-M2.7-highspeed",
+    temperature: 0.7,
+    maxTokens: 64,
+  });
+  const client = createLLMClient(config);
+
+  it("completes a simple chat request (sync)", async () => {
+    const syncClient = createLLMClient({ ...config, stream: false });
+    const result = await chatCompletion(syncClient, config.model, [
+      { role: "user", content: "Say OK and nothing else." },
+    ], { maxTokens: 16 });
+
+    expect(result.content).toBeTruthy();
+    expect(result.content.length).toBeGreaterThan(0);
+    expect(result.usage.totalTokens).toBeGreaterThan(0);
+  }, 30000);
+
+  it("completes a simple chat request (streaming)", async () => {
+    const result = await chatCompletion(client, config.model, [
+      { role: "user", content: "Say OK and nothing else." },
+    ], { maxTokens: 16 });
+
+    expect(result.content).toBeTruthy();
+    expect(result.content.length).toBeGreaterThan(0);
+  }, 30000);
+
+  it("handles system messages correctly", async () => {
+    const result = await chatCompletion(client, config.model, [
+      { role: "system", content: "You are a helpful assistant. Always reply with exactly one word." },
+      { role: "user", content: "What color is the sky?" },
+    ], { maxTokens: 16 });
+
+    expect(result.content).toBeTruthy();
+  }, 30000);
+});