Add lm studio as model provider

README.md

@@ -288,7 +288,7 @@ Then open **http://127.0.0.1:8088/** for the Console. Config, memory, and skills
 >   --add-host=host.docker.internal:host-gateway \
 >   -v copaw-data:/app/working agentscope/copaw:latest
 > ```
-> Then in CoPaw **Settings → Models → Ollama**, change the Base URL to `http://host.docker.internal:11434` or your corresponding port.
+> Then in CoPaw **Settings → Models**, change the Base URL to `http://host.docker.internal:<port>` — for example, `http://host.docker.internal:11434` for Ollama, or `http://host.docker.internal:1234/v1` for LM Studio.
 >
 > **Option B** — Host networking (Linux only):
 > ```bash

README_zh.md

@@ -290,7 +290,7 @@ docker run -p 127.0.0.1:8088:8088 -v copaw-data:/app/working agentscope/copaw:la
 >   --add-host=host.docker.internal:host-gateway \
 >   -v copaw-data:/app/working agentscope/copaw:latest
 > ```
-> 然后在 CoPaw **设置 → 模型 → Ollama** 中，将 Base URL 改为 `http://host.docker.internal:11434` 或对应端口。
+> 然后在 CoPaw **设置 → 模型** 中，将 Base URL 改为 `http://host.docker.internal:<端口>` — 例如 Ollama 填 `http://host.docker.internal:11434`，LM Studio 填 `http://host.docker.internal:1234/v1`。
 >
 > **方式 B** — 使用宿主机网络（仅限 Linux）：
 > ```bash

console/src/api/types/provider.ts

@@ -18,6 +18,7 @@ export interface ProviderInfo {
   freeze_url: boolean;
   api_key: string;
   base_url: string;
+  require_api_key: boolean;
 }
 
 export interface ProviderConfigRequest {

console/src/locales/en.json

@@ -346,6 +346,7 @@
     "azureEndpointHint": "Azure OpenAI endpoint, e.g. https://<resource>.openai.azure.com/openai/v1",
     "anthropicEndpointHint": "Anthropic endpoint, e.g. https://api.anthropic.com",
     "ollamaEndpointHint": "Ollama endpoint, e.g. http://localhost:11434",
+    "lmstudioEndpointHint": "LM Studio endpoint, e.g. http://localhost:1234/v1",
     "apiEndpointHint": "API endpoint, e.g. https://api.example.com",
     "pleaseEnterBaseURL": "Please enter the API base URL",
     "pleaseEnterValidURL": "Please enter a valid URL",

console/src/locales/ja.json

@@ -343,6 +343,7 @@
     "azureEndpointHint": "Azure OpenAIエンドポイント、例: https://<resource>.openai.azure.com/openai/v1",
     "anthropicEndpointHint": "Anthropicエンドポイント、例: https://api.anthropic.com",
     "ollamaEndpointHint": "Ollamaエンドポイント、例: http://localhost:11434",
+    "lmstudioEndpointHint": "LM Studioエンドポイント、例: http://localhost:1234/v1",
     "apiEndpointHint": "APIエンドポイント、例: https://api.example.com",
     "pleaseEnterBaseURL": "APIベースURLを入力してください",
     "pleaseEnterValidURL": "有効なURLを入力してください",

console/src/locales/ru.json

@@ -346,6 +346,7 @@
     "azureEndpointHint": "Azure OpenAI endpoint, например https://<resource>.openai.azure.com/openai/v1",
     "anthropicEndpointHint": "Anthropic endpoint, например https://api.anthropic.com",
     "ollamaEndpointHint": "Ollama endpoint, например http://localhost:11434",
+    "lmstudioEndpointHint": "LM Studio endpoint, например http://localhost:1234/v1",
     "apiEndpointHint": "API endpoint, например https://api.example.com",
     "pleaseEnterBaseURL": "Пожалуйста, введите базовый URL API",
     "pleaseEnterValidURL": "Пожалуйста, введите корректный URL",

console/src/locales/zh.json

@@ -346,6 +346,7 @@
     "azureEndpointHint": "Azure OpenAI 端点，例如 https://<resource>.openai.azure.com/openai/v1",
     "anthropicEndpointHint": "Anthropic 端点，例如 https://api.anthropic.com",
     "ollamaEndpointHint": "Ollama 端点，例如 http://localhost:11434",
+    "lmstudioEndpointHint": "LM Studio 端点，例如 http://localhost:1234/v1",
     "apiEndpointHint": "API 端点，例如 https://api.example.com",
     "pleaseEnterBaseURL": "请输入 API 基础 URL",
     "pleaseEnterValidURL": "请输入有效的 URL",

console/src/pages/Settings/Models/components/cards/RemoteProviderCard.tsx

@@ -62,6 +62,7 @@ export function RemoteProviderCard({
   const isConfigured =
     provider.is_local ||
     (provider.is_custom && provider.base_url) ||
+    (!provider.require_api_key && !!provider.base_url) ||
     provider.api_key;
   const hasModels = totalCount > 0;
   const isAvailable = isConfigured && hasModels;

console/src/pages/Settings/Models/components/modals/ProviderConfigModal.tsx

@@ -78,6 +78,9 @@ export function ProviderConfigModal({
     if (provider.id === "ollama") {
       return t("models.ollamaEndpointHint");
     }
+    if (provider.id === "lmstudio") {
+      return t("models.lmstudioEndpointHint");
+    }
     if (provider.is_custom) {
       return effectiveChatModel === "AnthropicChatModel"
         ? t("models.anthropicEndpointHint")
@@ -102,6 +105,9 @@ export function ProviderConfigModal({
     if (provider.id === "ollama") {
       return "http://localhost:11434";
     }
+    if (provider.id === "lmstudio") {
+      return "http://localhost:1234/v1";
+    }
     if (provider.is_custom && effectiveChatModel === "AnthropicChatModel") {
       return "https://api.anthropic.com";
     }

console/src/pages/Settings/Models/components/sections/ModelsSection.tsx

@@ -16,6 +16,7 @@ interface ModelsSectionProps {
     api_key?: string;
     is_custom: boolean;
     is_local?: boolean;
+    require_api_key?: boolean;
   }>;
   activeModels: {
     active_llm?: {
@@ -50,7 +51,7 @@ export function ModelsSection({
           (p.models?.length ?? 0) + (p.extra_models?.length ?? 0) > 0;
         if (!hasModels) return false;
         if (p.is_local) return true;
-        if (p.id === "ollama") return !!p.base_url;
+        if (!p.require_api_key) return !!p.base_url;
         if (p.is_custom) return !!p.base_url;
         return !!p.api_key;
       }),

src/copaw/providers/lm_studio_provider.py

@@ -0,0 +1,44 @@
+# -*- coding: utf-8 -*-
+"""An LM Studio provider implementation.
+
+LM Studio exposes an OpenAI-compatible local server (default
+http://localhost:1234/v1). This provider auto-discovers loaded models
+on each get_info() call, similar to OllamaProvider."""
+
+from __future__ import annotations
+
+import logging
+from typing import List
+
+from copaw.providers.openai_provider import OpenAIProvider
+from copaw.providers.provider import ModelInfo, ProviderInfo
+
+logger = logging.getLogger(__name__)
+
+
+class LMStudioProvider(OpenAIProvider):
+    """Provider for LM Studio's OpenAI-compatible local server."""
+
+    async def get_info(self, mock_secret: bool = True) -> ProviderInfo:
+        models: List[ModelInfo] = []
+        try:
+            models = await self.fetch_models(timeout=1)
+            self.models = models
+        except Exception:
+            pass
+        return ProviderInfo(
+            id=self.id,
+            name=self.name,
+            base_url=self.base_url,
+            api_key=self.api_key_prefix + "*" * 6
+            if mock_secret and self.api_key
+            else self.api_key,
+            chat_model=self.chat_model,
+            models=models,
+            extra_models=self.extra_models,
+            api_key_prefix=self.api_key_prefix,
+            is_local=self.is_local,
+            is_custom=self.is_custom,
+            freeze_url=self.freeze_url,
+            require_api_key=self.require_api_key,
+        )

src/copaw/providers/provider_manager.py

@@ -19,6 +19,7 @@
     ProviderInfo,
 )
 from copaw.providers.openai_provider import OpenAIProvider
+from copaw.providers.lm_studio_provider import LMStudioProvider
 from copaw.providers.anthropic_provider import AnthropicProvider
 from copaw.providers.ollama_provider import OllamaProvider
 from copaw.constant import SECRET_DIR
@@ -159,6 +160,15 @@
     require_api_key=False,
 )
 
+PROVIDER_LMSTUDIO = LMStudioProvider(
+    id="lmstudio",
+    name="LM Studio",
+    base_url="http://localhost:1234/v1",
+    require_api_key=False,
+    api_key_prefix="",
+    models=[],
+)
+
 
 class ModelSlotConfig(BaseModel):
     provider_id: str = Field(
@@ -216,6 +226,7 @@ def _init_builtins(self):
         self._add_builtin(PROVIDER_AZURE_OPENAI)
         self._add_builtin(PROVIDER_ANTHROPIC)
         self._add_builtin(PROVIDER_OLLAMA)
+        self._add_builtin(PROVIDER_LMSTUDIO)
         self._add_builtin(PROVIDER_LLAMACPP)
         self._add_builtin(PROVIDER_MLX)
 
@@ -419,6 +430,8 @@ def _provider_from_data(self, data: Dict) -> Provider:
             return AnthropicProvider.model_validate(data)
         if provider_id == "ollama" or chat_model == "OllamaChatModel":
             return OllamaProvider.model_validate(data)
+        if provider_id == "lmstudio":
+            return LMStudioProvider.model_validate(data)
         if data.get("is_local", False):
             return DefaultProvider.model_validate(data)
         return OpenAIProvider.model_validate(data)

website/public/docs/config.en.md

@@ -287,11 +287,16 @@ CoPaw needs an LLM provider to work. You can set it up in three ways:
 
 ### Built-in providers
 
-| Provider   | ID           | Default Base URL                                    | API Key Prefix |
-| ---------- | ------------ | --------------------------------------------------- | -------------- |
-| ModelScope | `modelscope` | `https://api-inference.modelscope.cn/v1`            | `ms`           |
-| DashScope  | `dashscope`  | `https://dashscope.aliyuncs.com/compatible-mode/v1` | `sk`           |
-| Custom     | `custom`     | _(you set it)_                                      | _(any)_        |
+| Provider     | ID             | Default Base URL                                    | API Key Prefix |
+| ------------ | -------------- | --------------------------------------------------- | -------------- |
+| ModelScope   | `modelscope`   | `https://api-inference.modelscope.cn/v1`            | `ms`           |
+| DashScope    | `dashscope`    | `https://dashscope.aliyuncs.com/compatible-mode/v1` | `sk`           |
+| OpenAI       | `openai`       | `https://api.openai.com/v1`                         | _(any)_        |
+| Azure OpenAI | `azure-openai` | _(you set it)_                                      | _(any)_        |
+| Anthropic    | `anthropic`    | `https://api.anthropic.com`                         | _(any)_        |
+| Ollama       | `ollama`       | `http://localhost:11434`                            | _(none)_       |
+| LM Studio    | `lmstudio`     | `http://localhost:1234/v1`                          | _(none)_       |
+| Custom       | `custom`       | _(you set it)_                                      | _(any)_        |
 
 For each provider you need to set:
 

website/public/docs/config.zh.md

@@ -277,11 +277,16 @@ CoPaw 需要 LLM 提供商才能运行。有三种设置方式：
 
 ### 内置提供商
 
-| 提供商             | ID           | 默认 Base URL                                       | API Key 前缀 |
-| ------------------ | ------------ | --------------------------------------------------- | ------------ |
-| ModelScope（魔搭） | `modelscope` | `https://api-inference.modelscope.cn/v1`            | `ms`         |
-| DashScope（灵积）  | `dashscope`  | `https://dashscope.aliyuncs.com/compatible-mode/v1` | `sk`         |
-| 自定义             | `custom`     | _（你自己填）_                                      | _（任意）_   |
+| 提供商             | ID             | 默认 Base URL                                       | API Key 前缀 |
+| ------------------ | -------------- | --------------------------------------------------- | ------------ |
+| ModelScope（魔搭） | `modelscope`   | `https://api-inference.modelscope.cn/v1`            | `ms`         |
+| DashScope（灵积）  | `dashscope`    | `https://dashscope.aliyuncs.com/compatible-mode/v1` | `sk`         |
+| OpenAI             | `openai`       | `https://api.openai.com/v1`                         | _（任意）_   |
+| Azure OpenAI       | `azure-openai` | _（你自己填）_                                      | _（任意）_   |
+| Anthropic          | `anthropic`    | `https://api.anthropic.com`                         | _（任意）_   |
+| Ollama             | `ollama`       | `http://localhost:11434`                            | _（无需）_   |
+| LM Studio          | `lmstudio`     | `http://localhost:1234/v1`                          | _（无需）_   |
+| 自定义             | `custom`       | _（你自己填）_                                      | _（任意）_   |
 
 每个提供商需要设置：
 

website/public/docs/console.en.md

@@ -327,6 +327,28 @@ automatically when models are added/removed via Ollama CLI or Console.
 > `copaw models ollama-list`, `copaw models ollama-remove`. See
 > [CLI](./cli#ollama-models).
 
+### LM Studio provider
+
+The LM Studio provider connects to the LM Studio desktop application's
+OpenAI-compatible local server to discover and use loaded models.
+
+**Prerequisites:**
+
+- Install LM Studio from [lmstudio.ai](https://lmstudio.ai)
+- Load a model and start the local server in LM Studio (default: `http://localhost:1234`)
+
+**Configure:**
+
+1. Click **Settings** on the LM Studio provider card.
+2. The default Base URL is `http://localhost:1234/v1`. Adjust if needed, then
+   click **Save**.
+3. Click **Manage Models** to see models loaded in LM Studio. You can also
+   manually add model IDs.
+4. Select **LM Studio** in the **Provider** dropdown and pick a model.
+
+> LM Studio does not require an API key by default. Models must be loaded
+> in LM Studio before they appear in CoPaw.
+
 ### Choose the active model
 
 1. In the **LLM Config** section, select a **Provider** from the dropdown
@@ -375,18 +397,18 @@ Select rows → click **Delete** in the toolbar → confirm.
 
 ## Quick Reference
 
-| Page                  | Sidebar path                     | What you can do                                      |
-| --------------------- | -------------------------------- | ---------------------------------------------------- |
-| Chat                  | Chat → Chat                      | Talk with CoPaw, manage sessions                     |
-| Channels              | Control → Channels               | Enable/disable channels, configure credentials       |
-| Sessions              | Control → Sessions               | Filter, rename, delete sessions                      |
-| Cron Jobs             | Control → Cron Jobs              | Create/edit/delete jobs, run immediately             |
-| Workspace             | Agent → Workspace                | Edit persona files, view memory, upload/download     |
-| Skills                | Agent → Skills                   | Enable/disable/create/delete skills                  |
-| MCP                   | Agent → MCP                      | Enable/disable/create/delete MCP clients             |
-| Runtime Config        | Agent → Runtime Config           | Modify runtime configuration                         |
-| Models                | Settings → Models                | Configure providers, manage local/Ollama, pick model |
-| Environment Variables | Settings → Environment Variables | Add/edit/delete environment variables                |
+| Page                  | Sidebar path                     | What you can do                                                |
+| --------------------- | -------------------------------- | -------------------------------------------------------------- |
+| Chat                  | Chat → Chat                      | Talk with CoPaw, manage sessions                               |
+| Channels              | Control → Channels               | Enable/disable channels, configure credentials                 |
+| Sessions              | Control → Sessions               | Filter, rename, delete sessions                                |
+| Cron Jobs             | Control → Cron Jobs              | Create/edit/delete jobs, run immediately                       |
+| Workspace             | Agent → Workspace                | Edit persona files, view memory, upload/download               |
+| Skills                | Agent → Skills                   | Enable/disable/create/delete skills                            |
+| MCP                   | Agent → MCP                      | Enable/disable/create/delete MCP clients                       |
+| Runtime Config        | Agent → Runtime Config           | Modify runtime configuration                                   |
+| Models                | Settings → Models                | Configure providers, manage local/Ollama/LM Studio, pick model |
+| Environment Variables | Settings → Environment Variables | Add/edit/delete environment variables                          |
 
 ---
 

website/public/docs/console.zh.md

@@ -309,6 +309,24 @@ Ollama 提供商集成本地 Ollama 守护进程，动态加载其中的模型
 
 > 也可以通过 CLI 管理 Ollama 模型：`copaw models ollama-pull`、`copaw models ollama-list`、`copaw models ollama-remove`。详见 [CLI](./cli#ollama-模型)。
 
+### LM Studio 提供商
+
+LM Studio 提供商连接 LM Studio 桌面应用内置的 OpenAI 兼容本地服务器，自动发现并使用已加载的模型。
+
+**前置条件：**
+
+- 从 [lmstudio.ai](https://lmstudio.ai) 安装 LM Studio
+- 在 LM Studio 中加载模型并启动本地服务器（默认地址：`http://localhost:1234`）
+
+**配置步骤：**
+
+1. 点击 LM Studio 提供商卡片的 **设置** 按钮。
+2. 默认 Base URL 为 `http://localhost:1234/v1`，如有需要可修改，点击 **保存**。
+3. 点击 **模型** 查看 LM Studio 中当前已加载的模型，也可手动添加模型 ID。
+4. 在 **提供商** 下拉菜单中选择 LM Studio，选择模型后点击 **保存**。
+
+> LM Studio 默认不需要 API Key。模型必须在 LM Studio 中加载后才会在 CoPaw 中显示。
+
 ### 选择活跃模型
 
 1. 在顶部**LLM配置**的**提供商**下拉菜单中选择一个提供商（只显示已授权或
@@ -354,18 +372,18 @@ Ollama 提供商集成本地 Ollama 守护进程，动态加载其中的模型
 
 ## 快速索引
 
-| 页面     | 侧边栏路径        | 你能做什么                                         |
-| -------- | ----------------- | -------------------------------------------------- |
-| 聊天     | 聊天 → 聊天       | 和 CoPaw 对话、管理会话                            |
-| 频道     | 控制 → 频道       | 启用/禁用频道、填入凭据                            |
-| 会话     | 控制 → 会话       | 筛选、重命名、删除会话                             |
-| 定时任务 | 控制 → 定时任务   | 创建/编辑/删除任务、立即执行                       |
-| 工作区   | 智能体 → 工作区   | 编辑人设文件、查看记忆、上传/下载                  |
-| 技能     | 智能体 → 技能     | 启用/禁用/创建/删除技能                            |
-| MCP      | 智能体 → MCP      | 启用/禁用/创建/删除MCP                             |
-| 运行配置 | 智能体 → 运行配置 | 修改运行配置                                       |
-| 模型     | 设置 → 模型       | 配置提供商 API Key、管理本地/Ollama 模型、选择模型 |
-| 环境变量 | 设置 → 环境变量   | 添加/编辑/删除环境变量                             |
+| 页面     | 侧边栏路径        | 你能做什么                                                   |
+| -------- | ----------------- | ------------------------------------------------------------ |
+| 聊天     | 聊天 → 聊天       | 和 CoPaw 对话、管理会话                                      |
+| 频道     | 控制 → 频道       | 启用/禁用频道、填入凭据                                      |
+| 会话     | 控制 → 会话       | 筛选、重命名、删除会话                                       |
+| 定时任务 | 控制 → 定时任务   | 创建/编辑/删除任务、立即执行                                 |
+| 工作区   | 智能体 → 工作区   | 编辑人设文件、查看记忆、上传/下载                            |
+| 技能     | 智能体 → 技能     | 启用/禁用/创建/删除技能                                      |
+| MCP      | 智能体 → MCP      | 启用/禁用/创建/删除MCP                                       |
+| 运行配置 | 智能体 → 运行配置 | 修改运行配置                                                 |
+| 模型     | 设置 → 模型       | 配置提供商 API Key、管理本地/Ollama/LM Studio 模型、选择模型 |
+| 环境变量 | 设置 → 环境变量   | 添加/编辑/删除环境变量                                       |
 
 ---