Merge e597c6d398 into 06289b36da

2026-01-29 18:40:27 +02:00 · 2026-01-29 18:40:27 +02:00 · 76ad4b9679
commit 76ad4b9679
parent 06289b36da e597c6d398
14 changed files with 778 additions and 5 deletions
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@ -8,6 +8,7 @@ Status: beta.
 ### Changes
 - Security: harden SSH tunnel target parsing to prevent option injection/DoS. (#4001) Thanks @YLChen-007.
 - Rebrand: rename the npm package/CLI to `moltbot`, add a `moltbot` compatibility shim, and move extensions to the `@moltbot/*` scope.
+- Models: add ShengSuanYun (胜算云) as a model provider with dynamic model discovery for both LLM and multimodal models (text-to-image, image-to-video, etc.).
 - Commands: group /help and /commands output with Telegram paging. (#2504) Thanks @hougangdev.
 - macOS: limit project-local `node_modules/.bin` PATH preference to debug builds (reduce PATH hijacking risk).
 - macOS: finish Moltbot app rename for macOS sources, bundle identifiers, and shared kit paths. (#2844) Thanks @fal3.
--- a/docs/providers/shengsuanyun.md
+++ b/docs/providers/shengsuanyun.md
@ -0,0 +1,260 @@
+---
+summary: "Use ShengSuanYun (胜算云) models in Moltbot"
+read_when:
+  - You want to use ShengSuanYun model router
+  - You need ShengSuanYun setup guidance
+---
+# ShengSuanYun (胜算云)
+
+ShengSuanYun provides a unified router for accessing multiple AI model providers through a single API endpoint, supporting both LLM models and multimodal generative models (text-to-image, image-to-video, etc.).
+
+## Why ShengSuanYun in Moltbot
+
+- **Unified API** for multiple model providers
+- **LLM Support**: OpenAI, Anthropic, Google, DeepSeek, and many others
+- **Multimodal Support**: Text-to-image, image-to-video, and other generative models
+- **OpenAI-compatible** `/v1` endpoints for LLMs
+- **Anthropic-compatible** `/v1/messages` endpoint
+- **Wide model selection** from different providers
+- **Automatic model discovery** from the provider's API
+
+## Features
+
+### LLM Models
+- **Multi-provider access**: Access models from OpenAI, Anthropic, Google, Ali, ByteDance, DeepSeek, Meta, and more
+- **Multiple API formats**: Supports `/v1/chat/completions`, `/v1/messages`, and `/v1/responses`
+- **Streaming**: ✅ Supported on all compatible models
+- **Function calling**: ✅ Supported on compatible models
+- **Vision**: ✅ Supported on models with vision capability
+- **Dynamic model discovery**: Models are automatically discovered from the API
+
+### Multimodal Models
+- **Text-to-Image**: GPT-Image, Doubao-Seedream, Qwen-Image-Plus, Flux models
+- **Text-to-Video**: Veo3.1, Sora2, 通义万相 (Wanxiang) models
+- **Image-to-Video**: Doubao-Seedance, Wanxiang image-to-video models
+- **Image-to-Image**: Flux-kontext-pro, Wanxiang image editing models
+- **Automatic discovery**: Over 200+ multimodal models available
+
+## Setup
+
+### 1. Get API Key
+
+1. Sign up at [ShengSuanYun](https://shengsuanyun.com)
+2. Navigate to [API settings](https://console.shengsuanyun.com/user/keys)
+3. Generate an API key
+
+### 2. Configure Moltbot
+
+**Option A: Environment Variable**
+
+```bash
+export SHENGSUANYUN_API_KEY="your-api-key"
+```
+
+**Option B: Config File**
+
+Add to your `moltbot.json`:
+
+```json5
+{
+  env: { SHENGSUANYUN_API_KEY: "your-api-key" },
+  agents: {
+    defaults: {
+      model: { primary: "shengsuanyun/anthropic/claude-opus-4.5" }
+    }
+  }
+}
+```
+
+### 3. Verify Setup
+
+```bash
+moltbot models list | grep shengsuanyun
+moltbot chat --model shengsuanyun/anthropic/claude-opus-4.5 "Hello, are you working?"
+```
+
+## Model Selection
+
+ShengSuanYun provides access to hundreds of models from various providers. Models are identified by their provider prefix:
+
+### LLM Providers
+
+- **OpenAI**: `openai/gpt-5.1`, `openai/gpt-5.2`, `openai/o3`
+- **Anthropic**: `anthropic/claude-opus-4.5`, `anthropic/claude-sonnet-4.5`, `anthropic/claude-haiku-4.5`
+- **Google**: `google/gemini-3-pro-preview`, `google/gemini-3-flash`
+- **DeepSeek**: `deepseek/deepseek-chat`, `deepseek/deepseek-reasoner`
+- **Ali**: Various Qwen models
+- **ByteDance**: Various Doubao models
+- **Meta**: Llama models
+- And many more...
+
+### Multimodal Models
+
+Multimodal models use the prefix `modality/{id}` format:
+
+#### Text-to-Image Models
+- **GPT-Image**: OpenAI's image generation models
+- **Doubao-Seedream**: ByteDance's text-to-image models (4.5 series)
+- **Qwen-Image-Plus**: Ali's advanced image generation
+- **Flux**: BlackForestLabs' high-quality image models
+
+#### Text-to-Video Models
+- **Veo3.1**: Google's video generation model
+- **Sora2**: OpenAI's video generation model
+- **通义万相 (Wanxiang)**: Ali's text-to-video models (2.2-Plus)
+
+#### Image-to-Video Models
+- **Doubao-Seedance**: ByteDance's image-to-video conversion
+- **通义万相 (Wanxiang)**: Ali's image-to-video models (2.5, 2.6)
+
+#### Image-to-Image Models
+- **Flux-kontext-pro**: Advanced image editing
+- **通义万相 (Wanxiang)**: Ali's image editing models (2.5)
+
+List all available models:
+
+```bash
+# List all models
+moltbot models list | grep shengsuanyun
+
+# List only LLM models
+moltbot models list | grep "shengsuanyun" | grep -v "modality"
+
+# List only multimodal models
+moltbot models list | grep "shengsuanyun/modality"
+```
+
+Change your default model:
+
+```bash
+# Set LLM model
+moltbot models set shengsuanyun/anthropic/claude-opus-4.5
+
+# Set multimodal model (if supported by your workflow)
+moltbot models set shengsuanyun/modality/256
+```
+
+## Model Discovery
+
+Moltbot automatically discovers models from two ShengSuanYun APIs when `SHENGSUANYUN_API_KEY` is configured:
+
+1. **LLM Models API**: `https://router.shengsuanyun.com/api/v1/models`
+   - Returns all text-based chat and completion models
+   - Includes models from major AI providers
+   - Supports filtering by API compatibility
+
+2. **Multimodal Models API**: `https://api.shengsuanyun.com/modelrouter/modalities/list`
+   - Returns generative models for images and videos
+   - Includes text-to-image, image-to-video, and image-to-image models
+   - Over 200+ models available
+
+Each model includes:
+- Model ID and name
+- Company/provider information
+- Context window size and max tokens (for LLMs)
+- Maximum output tokens
+- Supported APIs
+- Pricing information
+- Input modality support (text, image, etc.)
+- Model capabilities and classifications
+
+## API Compatibility
+
+ShengSuanYun supports multiple API formats:
+
+| API Format | Endpoint | Compatible With |
+|------------|----------|-----------------|
+| OpenAI Completions | `/v1/chat/completions` | OpenAI SDK |
+| Anthropic Messages | `/v1/messages` | Claude SDK |
+| OpenAI Responses | `/v1/responses` | OpenAI SDK |
+
+Moltbot automatically uses the appropriate API format based on the model's capabilities, preferring the OpenAI completions format when available.
+
+## Usage Examples
+
+### LLM Models
+
+```bash
+# Use Claude via ShengSuanYun
+moltbot chat --model shengsuanyun/anthropic/claude-opus-4.5
+
+# Use GPT-5.2
+moltbot chat --model shengsuanyun/openai/gpt-5.2
+
+# Use Gemini
+moltbot chat --model shengsuanyun/google/gemini-3-pro-preview
+
+# Use DeepSeek
+moltbot chat --model shengsuanyun/deepseek/deepseek-chat
+```
+
+### Multimodal Models
+
+Note: Multimodal model integration depends on your specific workflow and use case. The models are discovered and listed but may require additional configuration or API integration for image/video generation tasks.
+
+```bash
+# List available multimodal models
+moltbot models list | grep "modality"
+
+# Example multimodal model IDs (text-to-image, image-to-video, etc.)
+# - shengsuanyun/modality/256  (Ali Wanxiang 2.6 I2V)
+# - shengsuanyun/modality/XXX  (Other generative models)
+```
+
+## Configuration Example
+
+Full configuration in `moltbot.json`:
+
+```json5
+{
+  env: { SHENGSUANYUN_API_KEY: "your-api-key" },
+  agents: {
+    defaults: {
+      model: { primary: "shengsuanyun/anthropic/claude-opus-4.5" }
+    }
+  },
+  models: {
+    mode: "merge",
+    providers: {
+      shengsuanyun: {
+        baseUrl: "https://router.shengsuanyun.com/api/v1",
+        apiKey: "${SHENGSUANYUN_API_KEY}",
+        api: "openai-completions",
+        models: []  // Models are auto-discovered
+      }
+    }
+  }
+}
+```
+
+## Pricing
+
+ShengSuanYun uses its own pricing model. Check the ShengSuanYun dashboard for current rates per model. Pricing varies by:
+- Model provider
+- Model size and capability
+- Input/output tokens
+- Additional features (vision, etc.)
+
+## Troubleshooting
+
+### API key not recognized
+
+```bash
+echo $SHENGSUANYUN_API_KEY
+moltbot models list | grep shengsuanyun
+```
+
+Verify your API key is valid and has the correct permissions.
+
+### Model not available
+
+The ShengSuanYun model catalog updates dynamically. Run `moltbot models list` to see currently available models. Some models may be temporarily unavailable.
+
+### Connection issues
+
+ShengSuanYun API is at `https://router.shengsuanyun.com/api/v1`. Ensure your network allows HTTPS connections.
+
+## Links
+
+- [ShengSuanYun Website](https://router.shengsuanyun.com)
+- [Model List API](https://router.shengsuanyun.com/api/v1/models)
--- a/src/agents/model-auth.ts
+++ b/src/agents/model-auth.ts
@ -285,6 +285,7 @@ export function resolveEnvApiKey(provider: string): EnvApiKeyResult | null {
    venice: "VENICE_API_KEY",
    mistral: "MISTRAL_API_KEY",
    opencode: "OPENCODE_API_KEY",
+    shengsuanyun: "SHENGSUANYUN_API_KEY",
  };
  const envVar = envMap[normalized];
  if (!envVar) return null;
--- a/src/agents/models-config.providers.shengsuanyun.test.ts
+++ b/src/agents/models-config.providers.shengsuanyun.test.ts
@ -0,0 +1,15 @@
+import { describe, expect, it } from "vitest";
+import { resolveImplicitProviders } from "./models-config.providers.js";
+import { mkdtempSync } from "node:fs";
+import { join } from "node:path";
+import { tmpdir } from "node:os";
+
+describe("ShengSuanYun provider", () => {
+  it("should not include shengsuanyun when no API key is configured", async () => {
+    const agentDir = mkdtempSync(join(tmpdir(), "clawd-test-"));
+    const providers = await resolveImplicitProviders({ agentDir });
+
+    // ShengSuanYun requires explicit configuration via SHENGSUANYUN_API_KEY env var or profile
+    expect(providers?.shengsuanyun).toBeUndefined();
+  });
+});
--- a/src/agents/models-config.providers.ts
+++ b/src/agents/models-config.providers.ts
@ -13,6 +13,7 @@ import {
  SYNTHETIC_MODEL_CATALOG,
 } from "./synthetic-models.js";
 import { discoverVeniceModels, VENICE_BASE_URL } from "./venice-models.js";
+import { discoverAllShengSuanYunModels, SHENGSUANYUN_BASE_URL } from "./shengsuanyun-models.js";

 type ModelsConfig = NonNullable<MoltbotConfig["models"]>;
 export type ProviderConfig = NonNullable<ModelsConfig["providers"]>[string];
@ -359,6 +360,15 @@ async function buildOllamaProvider(): Promise<ProviderConfig> {
  };
 }

+async function buildShengSuanYunProvider(): Promise<ProviderConfig> {
+  const models = await discoverAllShengSuanYunModels();
+  return {
+    baseUrl: SHENGSUANYUN_BASE_URL,
+    api: "openai-completions",
+    models,
+  };
+}
+
 export async function resolveImplicitProviders(params: {
  agentDir: string;
 }): Promise<ModelsConfig["providers"]> {
@ -418,6 +428,14 @@ export async function resolveImplicitProviders(params: {
    providers.ollama = { ...(await buildOllamaProvider()), apiKey: ollamaKey };
  }

+  // ShengSuanYun provider - only add if explicitly configured
+  const shengsuanyunKey =
+    resolveEnvApiKeyVarName("shengsuanyun") ??
+    resolveApiKeyFromProfiles({ provider: "shengsuanyun", store: authStore });
+  if (shengsuanyunKey) {
+    providers.shengsuanyun = { ...(await buildShengSuanYunProvider()), apiKey: shengsuanyunKey };
+  }
+
  return providers;
 }

--- a/src/agents/shengsuanyun-models.test.ts
+++ b/src/agents/shengsuanyun-models.test.ts
@ -0,0 +1,30 @@
+import { describe, it, expect } from "vitest";
+import {
+  discoverShengSuanYunModels,
+  discoverShengSuanYunModalityModels,
+  discoverAllShengSuanYunModels,
+  SHENGSUANYUN_BASE_URL,
+  SHENGSUANYUN_MODALITIES_BASE_URL,
+} from "./shengsuanyun-models.js";
+
+describe("ShengSuanYun provider", () => {
+  it("should have the correct base URLs", () => {
+    expect(SHENGSUANYUN_BASE_URL).toBe("https://router.shengsuanyun.com/api/v1");
+    expect(SHENGSUANYUN_MODALITIES_BASE_URL).toBe("https://api.shengsuanyun.com/modelrouter");
+  });
+
+  it("should skip LLM discovery in test environment", async () => {
+    const models = await discoverShengSuanYunModels();
+    expect(models).toEqual([]);
+  });
+
+  it("should skip multimodal discovery in test environment", async () => {
+    const models = await discoverShengSuanYunModalityModels();
+    expect(models).toEqual([]);
+  });
+
+  it("should skip all model discovery in test environment", async () => {
+    const models = await discoverAllShengSuanYunModels();
+    expect(models).toEqual([]);
+  });
+});
--- a/src/agents/shengsuanyun-models.ts
+++ b/src/agents/shengsuanyun-models.ts
@ -0,0 +1,270 @@
+import type { ModelDefinitionConfig } from "../config/types.js";
+
+export const SHENGSUANYUN_BASE_URL = "https://router.shengsuanyun.com/api/v1";
+export const SHENGSUANYUN_MODALITIES_BASE_URL = "https://api.shengsuanyun.com/modelrouter";
+
+// ShengSuanYun uses credit-based pricing. Set to 0 as costs vary by model.
+export const SHENGSUANYUN_DEFAULT_COST = {
+  input: 0,
+  output: 0,
+  cacheRead: 0,
+  cacheWrite: 0,
+};
+
+// ShengSuanYun API response types for LLM models
+interface ShengSuanYunModel {
+  id: string;
+  company: string;
+  name: string;
+  api_name: string;
+  description: string;
+  max_tokens: number;
+  context_window: number;
+  supports_prompt_cache: boolean;
+  architecture: {
+    modality: string;
+    tokenizer: string;
+    instruct_type: string | null;
+  };
+  pricing: {
+    prompt: string;
+    completion: string;
+    request: string;
+    image?: string;
+    tts?: string;
+  };
+  support_apis: string[];
+}
+
+interface ShengSuanYunModelsResponse {
+  data: ShengSuanYunModel[];
+  object: string;
+  success: boolean;
+}
+
+// ShengSuanYun multimodal API response types
+interface ShengSuanYunModalityModel {
+  id: number;
+  model_name: string;
+  company_name: string;
+  class_name: string;
+  class_names: string[];
+  desc: string;
+  preview_img: string;
+  preview_video?: string;
+  usage: number;
+  pricing: {
+    input_price: number;
+    output_price: number;
+    currency: string;
+  };
+}
+
+interface ShengSuanYunModalitiesResponse {
+  code: number;
+  data: {
+    infos: ShengSuanYunModalityModel[];
+  };
+}
+
+/**
+ * Determine if a model supports reasoning based on its name and description.
+ */
+function isReasoningModel(model: ShengSuanYunModel): boolean {
+  const lowerName = (model.name ?? "").toLowerCase();
+  const lowerId = (model.id ?? "").toLowerCase();
+  const lowerDesc = (model.description ?? "").toLowerCase();
+
+  return (
+    lowerName.includes("thinking") ||
+    lowerName.includes("reasoning") ||
+    lowerName.includes("reason") ||
+    lowerName.includes("r1") ||
+    lowerId.includes("thinking") ||
+    lowerId.includes("reasoning") ||
+    lowerId.includes("r1") ||
+    lowerDesc.includes("reasoning") ||
+    lowerDesc.includes("thinking")
+  );
+}
+
+/**
+ * Determine if a model supports vision/image inputs.
+ */
+function supportsVision(model: ShengSuanYunModel): boolean {
+  const modality = (model.architecture?.modality ?? "").toLowerCase();
+  return (
+    modality.includes("image") || modality.includes("vision") || modality === "text+image->text"
+  );
+}
+
+/**
+ * Build a ModelDefinitionConfig from a ShengSuanYun API model.
+ */
+function buildShengSuanYunModelDefinition(model: ShengSuanYunModel): ModelDefinitionConfig {
+  const hasVision = supportsVision(model);
+  const reasoning = isReasoningModel(model);
+
+  return {
+    id: model.id,
+    name: model.name,
+    reasoning,
+    input: hasVision ? ["text", "image"] : ["text"],
+    cost: SHENGSUANYUN_DEFAULT_COST,
+    contextWindow: model.context_window || 128000,
+    maxTokens: model.max_tokens || 8192,
+  };
+}
+
+/**
+ * Discover models from ShengSuanYun API.
+ * The /models endpoint is public and doesn't require authentication.
+ */
+export async function discoverShengSuanYunModels(): Promise<ModelDefinitionConfig[]> {
+  // Skip API discovery in test environment
+  if (process.env.NODE_ENV === "test" || process.env.VITEST) {
+    return [];
+  }
+
+  try {
+    const response = await fetch(`${SHENGSUANYUN_BASE_URL}/models`, {
+      signal: AbortSignal.timeout(10000), // 10s timeout for large model list
+    });
+
+    if (!response.ok) {
+      // console.warn(
+      //   `[shengsuanyun-models] Failed to discover models: HTTP ${response.status}`,
+      // );
+      return [];
+    }
+
+    const data = (await response.json()) as ShengSuanYunModelsResponse;
+
+    if (!data.success || !Array.isArray(data.data) || data.data.length === 0) {
+      // console.warn("[shengsuanyun-models] No models found from API");
+      return [];
+    }
+
+    const models: ModelDefinitionConfig[] = [];
+    for (const apiModel of data.data) {
+      // Only include models that support at least one compatible API
+      const supportApis = apiModel.support_apis;
+      if (!Array.isArray(supportApis)) {
+        continue;
+      }
+
+      const hasCompatibleApi = supportApis.some(
+        (api) =>
+          api === "/v1/chat/completions" || api === "/v1/messages" || api === "/v1/responses",
+      );
+
+      if (!hasCompatibleApi) {
+        continue;
+      }
+
+      models.push(buildShengSuanYunModelDefinition(apiModel));
+    }
+
+    // console.log(`[shengsuanyun-models] Discovered ${models.length} LLM models`);
+    return models;
+  } catch {
+    // console.warn(`[shengsuanyun-models] Discovery failed: ${String(error)}`);
+    return [];
+  }
+}
+
+/**
+ * Determine modality input types from class names.
+ */
+function getModalityInputTypes(classNames: string[]): Array<"text" | "image"> {
+  if (!Array.isArray(classNames)) return ["text"];
+
+  const hasText = classNames.some((name) => name && (name.includes("text") || name.includes("文")));
+  const hasImage = classNames.some(
+    (name) =>
+      name &&
+      (name.includes("image") ||
+        name.includes("图") ||
+        name.includes("video") ||
+        name.includes("视频")),
+  );
+
+  const inputs: Array<"text" | "image"> = [];
+  if (hasText) inputs.push("text");
+  if (hasImage) inputs.push("image");
+
+  // Default to text if no clear input type
+  return inputs.length > 0 ? inputs : ["text"];
+}
+
+function buildShengSuanYunModalityModelDefinition(
+  model: ShengSuanYunModalityModel,
+): ModelDefinitionConfig {
+  const inputs = getModalityInputTypes(model.class_names);
+
+  return {
+    id: `modality/${model.id}`,
+    name: `${model.model_name} (${model.company_name})`,
+    reasoning: false, // Multimodal models typically don't do reasoning
+    input: inputs,
+    cost: SHENGSUANYUN_DEFAULT_COST,
+    contextWindow: 128000, // Default context window for multimodal models
+    maxTokens: 8192,
+  };
+}
+
+export async function discoverShengSuanYunModalityModels(): Promise<ModelDefinitionConfig[]> {
+  // Skip API discovery in test environment
+  if (process.env.NODE_ENV === "test" || process.env.VITEST) {
+    return [];
+  }
+
+  try {
+    const response = await fetch(
+      `${SHENGSUANYUN_MODALITIES_BASE_URL}/modalities/list?page=1&page_size=200`,
+      {
+        signal: AbortSignal.timeout(10000), // 10s timeout
+      },
+    );
+
+    if (!response.ok) {
+      // console.warn(
+      //   `[shengsuanyun-modalities] Failed to discover modality models: HTTP ${response.status}`,
+      // );
+      return [];
+    }
+
+    const data = (await response.json()) as ShengSuanYunModalitiesResponse;
+
+    if (data.code !== 0 || !Array.isArray(data.data.infos) || data.data.infos.length === 0) {
+      // console.warn("[shengsuanyun-modalities] No modality models found from API");
+      return [];
+    }
+
+    const models: ModelDefinitionConfig[] = data.data.infos.map(
+      buildShengSuanYunModalityModelDefinition,
+    );
+
+    // console.log(`[shengsuanyun-modalities] Discovered ${models.length} modality models`);
+    return models;
+  } catch {
+    // console.warn(`[shengsuanyun-modalities] Discovery failed: ${String(error)}`);
+    return [];
+  }
+}
+
+/**
+ * Discover all ShengSuanYun models (LLM + multimodal).
+ */
+export async function discoverAllShengSuanYunModels(): Promise<ModelDefinitionConfig[]> {
+  const [llmModels, modalityModels] = await Promise.all([
+    discoverShengSuanYunModels(),
+    discoverShengSuanYunModalityModels(),
+  ]);
+
+  const allModels = [...llmModels, ...modalityModels];
+  // console.log(
+  //   `[shengsuanyun] Discovered ${allModels.length} total models (${llmModels.length} LLM, ${modalityModels.length} multimodal)`
+  // );
+  return allModels;
+}
--- a/src/commands/auth-choice-options.ts
+++ b/src/commands/auth-choice-options.ts
@ -20,7 +20,8 @@ export type AuthChoiceGroupId =
  | "minimax"
  | "synthetic"
  | "venice"
-  | "qwen";
+  | "qwen"
+  | "shengsuanyun";

 export type AuthChoiceGroup = {
  value: AuthChoiceGroupId;
@ -113,6 +114,12 @@ const AUTH_CHOICE_GROUP_DEFS: {
    hint: "API key",
    choices: ["opencode-zen"],
  },
+  {
+    value: "shengsuanyun",
+    label: "ShengSuanYun",
+    hint: "API key",
+    choices: ["shengsuanyun-api-key"],
+  },
 ];

 export function buildAuthChoiceOptions(params: {
@ -142,6 +149,7 @@ export function buildAuthChoiceOptions(params: {
  options.push({ value: "moonshot-api-key", label: "Moonshot AI API key" });
  options.push({ value: "kimi-code-api-key", label: "Kimi Code API key" });
  options.push({ value: "synthetic-api-key", label: "Synthetic API key" });
+  options.push({ value: "shengsuanyun-api-key", label: "ShengSuanYun API key" });
  options.push({
    value: "venice-api-key",
    label: "Venice AI API key",
--- a/src/commands/auth-choice.apply.api-providers.ts
+++ b/src/commands/auth-choice.apply.api-providers.ts
@ -11,6 +11,10 @@ import {
  applyGoogleGeminiModelDefault,
  GOOGLE_GEMINI_DEFAULT_MODEL,
 } from "./google-gemini-model-default.js";
+import {
+  setShengSuanYunApiKey,
+  SHENGSUANYUN_DEFAULT_MODEL_REF,
+} from "./onboard-auth.credentials.js";
 import {
  applyAuthProfileConfig,
  applyKimiCodeConfig,
@ -21,6 +25,8 @@ import {
  applyOpencodeZenProviderConfig,
  applyOpenrouterConfig,
  applyOpenrouterProviderConfig,
+  applyShengSuanYunConfig,
+  applyShengSuanYunProviderConfig,
  applySyntheticConfig,
  applySyntheticProviderConfig,
  applyVeniceConfig,
@ -579,5 +585,73 @@ export async function applyAuthChoiceApiProviders(
    return { config: nextConfig, agentModelOverride };
  }

+  if (authChoice === "shengsuanyun-api-key") {
+    const store = ensureAuthProfileStore(params.agentDir, { allowKeychainPrompt: false });
+    const profileOrder = resolveAuthProfileOrder({
+      cfg: nextConfig,
+      store,
+      provider: "shengsuanyun",
+    });
+    const existingProfileId = profileOrder.find((profileId) => Boolean(store.profiles[profileId]));
+    const existingCred = existingProfileId ? store.profiles[existingProfileId] : undefined;
+    let profileId = "shengsuanyun:default";
+    let mode: "api_key" | "token" = "api_key";
+    let hasCredential = false;
+
+    if (existingProfileId && existingCred?.type) {
+      profileId = existingProfileId;
+      mode = existingCred.type === "token" ? "token" : "api_key";
+      hasCredential = true;
+    }
+
+    if (!hasCredential && params.opts?.token && params.opts?.tokenProvider === "shengsuanyun") {
+      await setShengSuanYunApiKey(normalizeApiKeyInput(params.opts.token), params.agentDir);
+      hasCredential = true;
+    }
+
+    if (!hasCredential) {
+      const envKey = resolveEnvApiKey("shengsuanyun");
+      if (envKey) {
+        const useExisting = await params.prompter.confirm({
+          message: `Use existing SHENGSUANYUN_API_KEY (${envKey.source}, ${formatApiKeyPreview(envKey.apiKey)})?`,
+          initialValue: true,
+        });
+        if (useExisting) {
+          await setShengSuanYunApiKey(envKey.apiKey, params.agentDir);
+          hasCredential = true;
+        }
+      }
+    }
+
+    if (!hasCredential) {
+      const key = await params.prompter.text({
+        message: "Enter ShengSuanYun API key",
+        validate: validateApiKeyInput,
+      });
+      await setShengSuanYunApiKey(normalizeApiKeyInput(String(key)), params.agentDir);
+      hasCredential = true;
+    }
+
+    if (hasCredential) {
+      nextConfig = applyAuthProfileConfig(nextConfig, {
+        profileId,
+        provider: "shengsuanyun",
+        mode,
+      });
+    }
+    const applied = await applyDefaultModelChoice({
+      config: nextConfig,
+      setDefaultModel: params.setDefaultModel,
+      defaultModel: SHENGSUANYUN_DEFAULT_MODEL_REF,
+      applyDefaultConfig: applyShengSuanYunConfig,
+      applyProviderConfig: applyShengSuanYunProviderConfig,
+      noteDefault: SHENGSUANYUN_DEFAULT_MODEL_REF,
+      noteAgentModel,
+      prompter: params.prompter,
+    });
+    agentModelOverride = applied.agentModelOverride ?? agentModelOverride;
+    return { config: applied.config, agentModelOverride };
+  }
+
  return null;
 }
--- a/src/commands/model-picker.ts
+++ b/src/commands/model-picker.ts
@ -211,7 +211,10 @@ export async function promptDefaultModel(
    // Skip internal router models that can't be directly called via API.
    if (HIDDEN_ROUTER_MODELS.has(key)) return;
    const hints: string[] = [];
-    if (entry.name && entry.name !== entry.id) hints.push(entry.name);
+    // For models with a distinct name, show the name as label and key as hint
+    const hasDistinctName = entry.name && entry.name !== entry.id;
+    const label = hasDistinctName ? (entry.name ?? key) : key;
+    if (hasDistinctName) hints.push(key);
    if (entry.contextWindow) hints.push(`ctx ${formatTokenK(entry.contextWindow)}`);
    if (entry.reasoning) hints.push("reasoning");
    const aliases = aliasIndex.byKey.get(key);
@ -219,7 +222,7 @@ export async function promptDefaultModel(
    if (!hasAuth(entry.provider)) hints.push("auth missing");
    options.push({
      value: key,
-      label: key,
+      label,
      hint: hints.length > 0 ? hints.join(" · ") : undefined,
    });
    seen.add(key);
@ -338,7 +341,10 @@ export async function promptModelAllowlist(params: {
    if (seen.has(key)) return;
    if (HIDDEN_ROUTER_MODELS.has(key)) return;
    const hints: string[] = [];
-    if (entry.name && entry.name !== entry.id) hints.push(entry.name);
+    // For models with a distinct name, show the name as label and key as hint
+    const hasDistinctName = entry.name && entry.name !== entry.id;
+    const label = hasDistinctName ? (entry.name ?? key) : key;
+    if (hasDistinctName) hints.push(key);
    if (entry.contextWindow) hints.push(`ctx ${formatTokenK(entry.contextWindow)}`);
    if (entry.reasoning) hints.push("reasoning");
    const aliases = aliasIndex.byKey.get(key);
@ -346,7 +352,7 @@ export async function promptModelAllowlist(params: {
    if (!hasAuth(entry.provider)) hints.push("auth missing");
    options.push({
      value: key,
-      label: key,
+      label,
      hint: hints.length > 0 ? hints.join(" · ") : undefined,
    });
    seen.add(key);
--- a/src/commands/onboard-auth.config-core.ts
+++ b/src/commands/onboard-auth.config-core.ts
@ -10,9 +10,11 @@ import {
  VENICE_DEFAULT_MODEL_REF,
  VENICE_MODEL_CATALOG,
 } from "../agents/venice-models.js";
+import { SHENGSUANYUN_BASE_URL } from "../agents/shengsuanyun-models.js";
 import type { MoltbotConfig } from "../config/config.js";
 import {
  OPENROUTER_DEFAULT_MODEL_REF,
+  SHENGSUANYUN_DEFAULT_MODEL_REF,
  VERCEL_AI_GATEWAY_DEFAULT_MODEL_REF,
  ZAI_DEFAULT_MODEL_REF,
 } from "./onboard-auth.credentials.js";
@ -411,6 +413,76 @@ export function applyVeniceConfig(cfg: MoltbotConfig): MoltbotConfig {
  };
 }

+/**
+ * Apply ShengSuanYun provider configuration only (adds to models.providers).
+ */
+export function applyShengSuanYunProviderConfig(cfg: MoltbotConfig): MoltbotConfig {
+  const models = { ...cfg.agents?.defaults?.models };
+  models[SHENGSUANYUN_DEFAULT_MODEL_REF] = {
+    ...models[SHENGSUANYUN_DEFAULT_MODEL_REF],
+    alias: models[SHENGSUANYUN_DEFAULT_MODEL_REF]?.alias ?? "ShengSuanYun",
+  };
+
+  const providers = { ...cfg.models?.providers };
+  const existingProvider = providers.shengsuanyun;
+  const { apiKey: existingApiKey, ...existingProviderRest } = (existingProvider ?? {}) as Record<
+    string,
+    unknown
+  > as { apiKey?: string };
+  const resolvedApiKey = typeof existingApiKey === "string" ? existingApiKey : undefined;
+  const normalizedApiKey = resolvedApiKey?.trim();
+
+  providers.shengsuanyun = {
+    ...existingProviderRest,
+    baseUrl: SHENGSUANYUN_BASE_URL,
+    api: "openai-completions",
+    ...(normalizedApiKey ? { apiKey: normalizedApiKey } : {}),
+    // Models will be discovered automatically by resolveImplicitProviders
+    models: [],
+  };
+
+  return {
+    ...cfg,
+    agents: {
+      ...cfg.agents,
+      defaults: {
+        ...cfg.agents?.defaults,
+        models,
+      },
+    },
+    models: {
+      mode: cfg.models?.mode ?? "merge",
+      providers,
+    },
+  };
+}
+
+/**
+ * Apply ShengSuanYun provider configuration AND set ShengSuanYun as the default model.
+ * Use this when ShengSuanYun is the primary provider choice during onboarding.
+ */
+export function applyShengSuanYunConfig(cfg: MoltbotConfig): MoltbotConfig {
+  const next = applyShengSuanYunProviderConfig(cfg);
+  const existingModel = next.agents?.defaults?.model;
+  return {
+    ...next,
+    agents: {
+      ...next.agents,
+      defaults: {
+        ...next.agents?.defaults,
+        model: {
+          ...(existingModel && "fallbacks" in (existingModel as Record<string, unknown>)
+            ? {
+                fallbacks: (existingModel as { fallbacks?: string[] }).fallbacks,
+              }
+            : undefined),
+          primary: SHENGSUANYUN_DEFAULT_MODEL_REF,
+        },
+      },
+    },
+  };
+}
+
 export function applyAuthProfileConfig(
  cfg: MoltbotConfig,
  params: {
--- a/src/commands/onboard-auth.credentials.ts
+++ b/src/commands/onboard-auth.credentials.ts
@ -164,3 +164,17 @@ export async function setOpencodeZenApiKey(key: string, agentDir?: string) {
    agentDir: resolveAuthAgentDir(agentDir),
  });
 }
+
+export const SHENGSUANYUN_DEFAULT_MODEL_REF = "shengsuanyun/openai/gpt-5-nano";
+export async function setShengSuanYunApiKey(key: string, agentDir?: string) {
+  // Write to resolved agent dir so gateway finds credentials on startup.
+  upsertAuthProfile({
+    profileId: "shengsuanyun:default",
+    credential: {
+      type: "api_key",
+      provider: "shengsuanyun",
+      key,
+    },
+    agentDir: resolveAuthAgentDir(agentDir),
+  });
+}
--- a/src/commands/onboard-auth.ts
+++ b/src/commands/onboard-auth.ts
@ -11,6 +11,8 @@ export {
  applyMoonshotProviderConfig,
  applyOpenrouterConfig,
  applyOpenrouterProviderConfig,
+  applyShengSuanYunConfig,
+  applyShengSuanYunProviderConfig,
  applySyntheticConfig,
  applySyntheticProviderConfig,
  applyVeniceConfig,
--- a/src/commands/onboard-types.ts
+++ b/src/commands/onboard-types.ts
@ -31,6 +31,7 @@ export type AuthChoice =
  | "github-copilot"
  | "copilot-proxy"
  | "qwen-portal"
+  | "shengsuanyun-api-key"
  | "skip";
 export type GatewayAuthChoice = "token" | "password";
 export type ResetScope = "config" | "config+creds+sessions" | "full";
@ -71,6 +72,7 @@ export type OnboardOptions = {
  syntheticApiKey?: string;
  veniceApiKey?: string;
  opencodeZenApiKey?: string;
+  shengSuanYunApiKey?: string;
  gatewayPort?: number;
  gatewayBind?: GatewayBind;
  gatewayAuth?: GatewayAuthChoice;