feat: support comma-separated AI_MODEL for quick multi-model setup

Users expected setting AI_MODEL to a comma-separated list to expose
multiple models in the picker, but the value was used verbatim as a
single model id, leaving the picker with only the "Server Default"
fallback.

Add a third-priority fallback in loadEnvServerModelsConfig: when
AI_MODELS_CONFIG and ai-models.json are both absent, AI_MODEL contains
a comma, and AI_PROVIDER is set to a known provider, synthesize an
equivalent ServerModelsConfig with the provider's models trimmed,
deduplicated, and the first marked as default.

Also makes getAIModel and getValidationModel pick the first comma-split
value when falling back to AI_MODEL, so requests started before the
client picker hydrates still resolve to a real model id.

Docs (en/cn/ja) and env.example updated; tests cover the new fallback
plus the no-comma / no-AI_PROVIDER negative cases.

README.md

@@ -225,7 +225,7 @@ All providers except AWS Bedrock and OpenRouter support custom endpoints.
 
 ### Server-Side Multi-Model Configuration
 
-Administrators can configure multiple server-side models that are available to all users without requiring personal API keys. Configure via `AI_MODELS_CONFIG` environment variable (JSON string) or `ai-models.json` file.
+Administrators can configure multiple server-side models that are available to all users without requiring personal API keys. Configure via `AI_MODELS_CONFIG` environment variable (JSON string) or `ai-models.json` file. For a single-provider quick setup, list comma-separated model IDs in `AI_MODEL`.
 
 ### Admin Panel
 

docs/cn/README_CN.md

@@ -217,7 +217,7 @@ npm run dev
 
 ### 服务端多模型配置
 
-管理员可以配置多个服务端模型，让所有用户无需提供个人 API Key 即可使用。通过 `AI_MODELS_CONFIG` 环境变量（JSON 字符串）或 `ai-models.json` 文件配置。
+管理员可以配置多个服务端模型，让所有用户无需提供个人 API Key 即可使用。通过 `AI_MODELS_CONFIG` 环境变量（JSON 字符串）或 `ai-models.json` 文件配置。如果只需要单 provider 下的多个模型，也可以直接在 `AI_MODEL` 中用逗号分隔模型 ID。
 
 **模型要求**：此任务需要强大的模型能力，因为它涉及生成具有严格格式约束的长文本（draw.io XML）。推荐使用 Claude Sonnet 4.5、GPT-5.1、Gemini 3 Pro 和 DeepSeek V3.2/R1。
 

docs/cn/ai-providers.md

@@ -336,6 +336,17 @@ AI_MODELS_CONFIG='{"providers":[{"name":"OpenAI","provider":"openai","models":["
 
 在项目根目录创建 `ai-models.json` 文件（或通过 `AI_MODELS_CONFIG_PATH` 指定路径）。
 
+**方式三：`AI_MODEL` 用逗号分隔**（单 provider 的快速配置）
+
+如果只需要暴露同一 provider 下的多个模型，可以直接在 `AI_MODEL` 里用逗号分隔。第一个模型会作为默认值。
+
+```bash
+AI_PROVIDER=doubao
+AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
+```
+
+这是等价 `ai-models.json` 的简写形式。如果需要配置多个 provider，或自定义 `apiKeyEnv` / `baseUrlEnv`，请使用方式一或方式二。
+
 ### 配置示例
 
 ```json

docs/en/ai-providers.md

@@ -351,6 +351,17 @@ AI_MODELS_CONFIG='{"providers":[{"name":"OpenAI","provider":"openai","models":["
 
 Create an `ai-models.json` file in the project root (or set `AI_MODELS_CONFIG_PATH` to a custom location).
 
+**Option 3: Comma-separated `AI_MODEL`** (quick setup, single provider)
+
+If you only need multiple models from one provider, list them in `AI_MODEL` separated by commas. The first model is treated as the default.
+
+```bash
+AI_PROVIDER=doubao
+AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
+```
+
+This is shorthand for the equivalent `ai-models.json`. For multiple providers or custom `apiKeyEnv` / `baseUrlEnv`, use Option 1 or 2 instead.
+
 ### Example Configuration
 
 ```json

docs/ja/README_JA.md

@@ -216,7 +216,7 @@ AWS BedrockとOpenRouter以外のすべてのプロバイダーはカスタム
 
 ### サーバーサイドマルチモデル設定
 
-管理者は、ユーザーが個人のAPIキーを提供することなく利用できる複数のサーバーサイドモデルを設定できます。`AI_MODELS_CONFIG` 環境変数（JSON文字列）または `ai-models.json` ファイルで設定します。
+管理者は、ユーザーが個人のAPIキーを提供することなく利用できる複数のサーバーサイドモデルを設定できます。`AI_MODELS_CONFIG` 環境変数（JSON文字列）または `ai-models.json` ファイルで設定します。同一プロバイダー内の複数モデルだけが必要な場合は、`AI_MODEL` にカンマ区切りでモデルIDを列挙する簡易設定も使えます。
 
 **モデル要件**：このタスクは厳密なフォーマット制約（draw.io XML）を持つ長文テキスト生成を伴うため、強力なモデル機能が必要です。Claude Sonnet 4.5、GPT-5.1、Gemini 3 Pro、DeepSeek V3.2/R1を推奨します。
 

docs/ja/ai-providers.md

@@ -336,6 +336,17 @@ AI_MODELS_CONFIG='{"providers":[{"name":"OpenAI","provider":"openai","models":["
 
 プロジェクトルートに `ai-models.json` ファイルを作成します（または `AI_MODELS_CONFIG_PATH` でパスを指定）。
 
+**方法3：`AI_MODEL` をカンマ区切りで指定**（単一プロバイダーの簡易設定）
+
+同一プロバイダー内の複数モデルだけを公開したい場合は、`AI_MODEL` にカンマ区切りで列挙できます。最初のモデルがデフォルトになります。
+
+```bash
+AI_PROVIDER=doubao
+AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
+```
+
+これは等価な `ai-models.json` の簡易表記です。複数のプロバイダーや、カスタム `apiKeyEnv` / `baseUrlEnv` を使う場合は、方法1または方法2を使ってください。
+
 ### 設定例
 
 ```json

env.example

@@ -5,6 +5,10 @@
 AI_PROVIDER=bedrock
 
 # AI_MODEL: The model ID for your chosen provider (REQUIRED)
+# Tip: For a single-provider quick multi-model setup, list comma-separated model IDs.
+# The first one becomes the default and the rest appear in the model picker.
+# For multiple providers or custom apiKeyEnv/baseUrlEnv, use AI_MODELS_CONFIG / ai-models.json instead.
+# Example: AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
 AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
 
 # AWS Bedrock Configuration

lib/ai-providers.ts

@@ -729,8 +729,10 @@ export function getAIModel(overrides?: ClientOverrides): ModelConfig {
             (overrides?.provider === "vertexai" && overrides?.vertexApiKey))
     )
 
-    // Use client override if provided, otherwise fall back to env vars
-    const modelId = overrides?.modelId || process.env.AI_MODEL
+    // Use client override if provided, otherwise fall back to env vars.
+    // AI_MODEL may be comma-separated (multi-model fallback); pick the first.
+    const envModel = process.env.AI_MODEL?.split(",")[0]?.trim() || undefined
+    const modelId = overrides?.modelId || envModel
 
     if (!modelId) {
         if (isClientOverride) {
@@ -1490,7 +1492,9 @@ export function supportsImageInput(modelId: string): boolean {
  * Throws if the model doesn't support image input.
  */
 export function getValidationModel(): ReturnType<typeof getAIModel>["model"] {
-    const modelId = process.env.VALIDATION_MODEL || process.env.AI_MODEL
+    // AI_MODEL may be comma-separated (multi-model fallback); pick the first.
+    const envFallback = process.env.AI_MODEL?.split(",")[0]?.trim() || undefined
+    const modelId = process.env.VALIDATION_MODEL || envFallback
 
     if (!modelId) {
         throw new Error(

lib/server-model-config.ts

@@ -62,6 +62,53 @@ function getConfigPath(): string {
     return path.join(process.cwd(), "ai-models.json")
 }
 
+/**
+ * Synthesize a config from a comma-separated AI_MODEL value (Priority 3 fallback).
+ * Lets users expose multiple models without authoring AI_MODELS_CONFIG / ai-models.json.
+ * Triggers only when AI_MODEL contains a comma AND AI_PROVIDER is set to a known provider.
+ */
+function configFromCommaSeparatedAiModel(): ServerModelsConfig | null {
+    const aiModel = process.env.AI_MODEL
+    if (!aiModel || !aiModel.includes(",")) return null
+
+    const aiProvider = process.env.AI_PROVIDER
+    if (!aiProvider) {
+        console.warn(
+            "[server-model-config] AI_MODEL contains commas but AI_PROVIDER is not set; " +
+                "skipping multi-model fallback. Set AI_PROVIDER, or use AI_MODELS_CONFIG / ai-models.json.",
+        )
+        return null
+    }
+    if (!(aiProvider in PROVIDER_INFO)) {
+        console.warn(
+            `[server-model-config] AI_PROVIDER="${aiProvider}" is not a known provider; skipping multi-model fallback.`,
+        )
+        return null
+    }
+
+    const models = Array.from(
+        new Set(
+            aiModel
+                .split(",")
+                .map((s) => s.trim())
+                .filter((s) => s.length > 0),
+        ),
+    )
+    if (models.length === 0) return null
+
+    const providerName = aiProvider as ProviderName
+    return {
+        providers: [
+            {
+                name: PROVIDER_INFO[providerName]?.label || providerName,
+                provider: providerName,
+                models,
+                default: true,
+            },
+        ],
+    }
+}
+
 export async function loadEnvServerModelsConfig(): Promise<ServerModelsConfig | null> {
     // Priority 1: AI_MODELS_CONFIG env var (JSON string) - for cloud deployments
     const envConfig = process.env.AI_MODELS_CONFIG
@@ -85,15 +132,17 @@ export async function loadEnvServerModelsConfig(): Promise<ServerModelsConfig |
         const json = JSON.parse(jsonStr)
         return ServerModelsConfigSchema.parse(json)
     } catch (err: any) {
-        if (err?.code === "ENOENT") {
+        if (err?.code !== "ENOENT") {
+            console.error(
+                "[server-model-config] Failed to load ai-models.json:",
+                err,
+            )
             return null
         }
-        console.error(
-            "[server-model-config] Failed to load ai-models.json:",
-            err,
-        )
-        return null
     }
+
+    // Priority 3: AI_MODEL with comma-separated values + AI_PROVIDER
+    return configFromCommaSeparatedAiModel()
 }
 
 export async function loadRawServerModelsConfig(): Promise<ServerModelsConfig | null> {

tests/unit/server-model-config.test.ts

@@ -159,6 +159,44 @@ describe("loadFlattenedServerModels", () => {
         expect(defaultModel.modelId).toBe("gpt-4o") // First model of default provider
     })
 
+    it("falls back to comma-separated AI_MODEL when no other config is set", async () => {
+        process.env.AI_MODELS_CONFIG = ""
+        process.env.AI_MODELS_CONFIG_PATH = `non-existent-config-${Date.now()}.json`
+        process.env.AI_PROVIDER = "openai"
+        process.env.AI_MODEL = "gpt-4o, gpt-4o-mini, gpt-4o"
+
+        const models = await loadFlattenedServerModels()
+
+        // Trims, deduplicates, and preserves order
+        expect(models.map((m) => m.modelId)).toEqual(["gpt-4o", "gpt-4o-mini"])
+        expect(models.every((m) => m.provider === "openai")).toBe(true)
+
+        // First model is marked default (provider has default: true)
+        const defaults = models.filter((m) => m.isDefault)
+        expect(defaults.length).toBe(1)
+        expect(defaults[0].modelId).toBe("gpt-4o")
+    })
+
+    it("does not synthesize when AI_MODEL has no comma", async () => {
+        process.env.AI_MODELS_CONFIG = ""
+        process.env.AI_MODELS_CONFIG_PATH = `non-existent-config-${Date.now()}.json`
+        process.env.AI_PROVIDER = "openai"
+        process.env.AI_MODEL = "gpt-4o"
+
+        const models = await loadFlattenedServerModels()
+        expect(models).toEqual([])
+    })
+
+    it("does not synthesize when AI_PROVIDER is unset", async () => {
+        process.env.AI_MODELS_CONFIG = ""
+        process.env.AI_MODELS_CONFIG_PATH = `non-existent-config-${Date.now()}.json`
+        delete process.env.AI_PROVIDER
+        process.env.AI_MODEL = "gpt-4o, gpt-4o-mini"
+
+        const models = await loadFlattenedServerModels()
+        expect(models).toEqual([])
+    })
+
     it("preserves apiKeyEnv array in flattened models for load balancing", async () => {
         const config: ServerModelsConfig = {
             providers: [