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doc/docs/en/user-guide/model-configuration.md

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## ⚙️ Configure System Models
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After adding models, you also need to properly configure system main/secondary models, embedding models, and multimodal models. These system models will be used in subsequent agents.
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### Large Language Models
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The system supports configuring main and secondary models for handling tasks of different complexity. The main model should be powerful, responsive, and capable to ensure core business performance. The secondary model can be cost-effective for less critical tasks.
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- Click the main model dropdown to select a model from the added LLMs.
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- Click the secondary model dropdown to select a model from the added LLMs.
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### Embedding Models
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Embedding models are mainly used for vectorizing text, images, and other data in the knowledge base, enabling efficient search and semantic understanding. Properly configuring embedding models can significantly improve search accuracy and multimodal data processing.
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- Click the embedding model dropdown to select a model from the added embedding models.
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### Multimodal Models
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Multimodal models combine vision and language capabilities, enabling complex scenarios involving text, images, etc. For example, when uploading images in the chat page, the system will automatically use a multimodal model for content analysis and intelligent conversation.
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- Click the vision-language model dropdown to select a model from the added multimodal models.
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<div style="display: flex; gap: 8px;">
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<img src="./assets/model/select-model-1.png" style="width: 30%; height: 100%;" />
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<img src="./assets/model/select-model-2.png" style="width: 30%; height: 100%;" />
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<img src="./assets/model/select-model-3.png" style="width: 30%; height: 100%;" />
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</div>
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After adding models, you need to configure the system base model, which will be used for basic functions such as title generation and real-time file reading. When agents are running, you can specify specific models for each agent.
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### Base Model Configuration
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The system base model is used for core platform functions, including:
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- Title generation
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- Real-time file reading
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- Basic text processing
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**Configuration Steps:**
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- Click the base model dropdown to select a model from the added large language models as the system base model.
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### Agent Model Configuration
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When creating and configuring agents, you can specify specific models for each agent:
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- Each agent can independently select the large language model to use
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- Support configuring different models for different agents to meet various business needs
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- Agent model configuration will be set in the agent configuration page
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## ✅ Check Model Connectivity
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doc/docs/zh/user-guide/model-configuration.md

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## ⚙️ 配置系统模型
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添加模型后,您还需要合理配置系统主/副模型、向量化模型和多模态模型,这些系统模型会在后续的智能体中被使用。
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### 大语言模型
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系统支持配置主模型和副模型,分别用于处理不同复杂度的任务。主模型建议选择性能最强、响应速度快、理解能力优秀的大语言模型,以保证系统在核心业务场景下的表现。副模型则可选择资源消耗较低、成本更优的模型,用于处理次要任务。
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- 点击主模型下拉框,从已添加的大语言模型中选择一个。
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- 点击副模型下拉框,从已添加的大语言模型中选择一个。
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添加模型后,您需要配置系统基础模型,该模型将用于标题生成、实时文件读取等基础功能。在智能体运行时,您可以为每个智能体指定特定的运行模型。
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### 基础模型配置
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系统基础模型用于处理平台的核心功能,包括:
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- 标题生成
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- 实时文件读取
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- 基础文本处理
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**配置步骤**
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- 点击基础模型下拉框,从已添加的大语言模型中选择一个作为系统基础模型。
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### 智能体模型配置
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在创建和配置智能体时,您可以为每个智能体指定特定的运行模型:
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- 每个智能体可以独立选择使用的大语言模型
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- 支持为不同智能体配置不同的模型,以满足不同的业务需求
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- 智能体模型配置将在智能体配置页面进行设置
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### 向量化模型
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向量化模型主要用于知识库的文本、图片等数据的向量化处理,是实现高效检索和语义理解的基础。配置合适的向量化模型,可以显著提升知识库的搜索准确率和多模态数据的处理能力。

frontend/public/locales/en/common.json

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"setup.page.error.saveConfig": "Failed to save configuration, please try again",
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"setup.page.error.missingModelConfig": "Model configuration not found, please contact the administrator",
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"setup.page.error.systemError": "System error, please try again later",
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"setup.page.error.selectMainModel": "Please select the main model",
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"setup.page.error.selectMainModel": "Please select model",
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"setup.page.error.highlightField.llmMain": "llm.main",
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"setup.page.error.adminOnly": "Only administrators can access the model configuration page",
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"toolConfig.input.string.placeholder": "Please enter {{name}}",
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"toolConfig.input.array.placeholder": "Please enter JSON array",
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"toolConfig.input.object.placeholder": "Please enter JSON object",
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"toolConfig.model.main": "Main Model",
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"toolConfig.model.sub": "Sub Model",
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"toolPool.title": "Select tools",
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"toolPool.loading": "Loading...",
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"document.summary.saveError": "Failed to save summary",
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"document.summary.saveFailed": "Save failed",
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"document.summary.title": "Knowledge Base Summary",
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"document.summary.modelLabel": "Main Model",
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"document.summary.modelLabel": "Model",
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"document.summary.modelPlaceholder": "Select Model",
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"document.status.creating": "Creating...",
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"document.status.loadingList": "Loading document list...",
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"model.source.silicon": "Silicon Flow",
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"model.source.unknown": "Unknown Source",
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"model.warning.updateNotFound": "Model not found for update: {{displayName}}, type: {{type}}",
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"model.type.main": "Main Model",
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"model.type.main": "LLM Model",
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"model.select.placeholder": "Select Model",
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"model.group.modelEngine": "ModelEngine Models",
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"model.group.custom": "Custom Models",
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"model.status.tooltip": "Click to verify connectivity",
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"model.option.main": "Main Model",
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"model.option.sub": "Sub Model",
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"appConfig.appName.label": "Application Name",
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"appConfig.appName.placeholder": "Please enter your application name",
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"modelConfig.category.reranker": "Reranker Models",
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"modelConfig.category.multimodal": "Multimodal Models",
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"modelConfig.category.voice": "Voice Models",
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"modelConfig.option.mainModel": "Main Model",
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"modelConfig.option.mainModel": "LLM Model",
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"modelConfig.option.embeddingModel": "Embedding Model",
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"modelConfig.option.multiEmbeddingModel": "Multimodal Embedding Model",
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"modelConfig.option.rerankerModel": "Reranker Model",

frontend/public/locales/zh/common.json

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"setup.page.error.saveConfig": "保存配置失败,请重试",
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"setup.page.error.missingModelConfig": "未找到模型配置,请联系管理员先完成模型配置",
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"setup.page.error.systemError": "系统异常,请稍后重试",
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"setup.page.error.selectMainModel": "请选择主模型",
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"setup.page.error.selectMainModel": "请选择模型",
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"setup.page.error.highlightField.llmMain": "llm.main",
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"setup.page.error.adminOnly": "只有管理员可以访问模型配置页面",
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"toolConfig.input.string.placeholder": "请输入{{name}}",
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"toolConfig.input.array.placeholder": "请输入JSON数组",
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"toolConfig.input.object.placeholder": "请输入JSON对象",
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"toolConfig.model.main": "主模型",
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"toolPool.title": "选择 Agent 的工具",
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"toolPool.loading": "加载中...",
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"document.summary.saveError": "保存总结失败",
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"document.summary.saveFailed": "保存失败",
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"document.summary.title": "知识库总结",
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"document.summary.modelLabel": "主模型",
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"document.summary.modelLabel": "模型",
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"document.summary.modelPlaceholder": "选择模型",
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"document.status.creating": "创建中...",
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"document.status.loadingList": "正在加载文档列表...",
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"model.source.openai": "OpenAI",
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"model.source.silicon": "硅基流动",
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"model.warning.updateNotFound": "未找到要更新的模型: {{displayName}}, 类型: {{type}}",
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"model.type.main": "主模型",
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"model.type.main": "模型",
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"model.select.placeholder": "选择模型",
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"model.group.modelEngine": "ModelEngine模型",
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"model.group.custom": "自定义模型",
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"model.status.tooltip": "点击可验证连通性",
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"model.option.main": "主模型",
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"model.dialog.success.updateSuccess": "更新成功",
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"appConfig.appName.label": "应用名称",
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"modelConfig.category.reranker": "重排模型",
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"modelConfig.category.multimodal": "多模态模型",
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"modelConfig.category.voice": "语音模型",
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"modelConfig.option.mainModel": "主模型",
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"modelConfig.option.mainModel": "模型",
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"modelConfig.option.embeddingModel": "向量模型",
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"modelConfig.option.multiEmbeddingModel": "多模态向量模型",
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"modelConfig.option.rerankerModel": "重排模型",

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