coze-dev · JianyangZhang · Aug 4, 2025
@@ -0,0 +1,170 @@
+id: 10002
+name: GLM-4.5
+icon_uri: default_icon/z_ai.png
+icon_url: ""
+description:
+    zh: GLM-4.5 系列模型是专为智能体设计的基座模型。GLM-4.5 拥有 3550 亿总参数与 320 亿激活参数，而 GLM-4.5-Air 采用更紧凑的设计，总参数达 1060 亿，激活参数为 120 亿。该系列模型统一了推理、编程与智能体能力，可满足智能体应用的复杂需求。
+    en: The GLM-4.5 series models are foundation models designed for intelligent agents. GLM-4.5 has 355 billion total parameters with 32 billion active parameters, while GLM-4.5-Air adopts a more compact design with 106 billion total parameters and 12 billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications.
+default_parameters:
+    - name: temperature
+      label:
+        zh: 生成随机性
+        en: Temperature
+      desc:
+        zh: '- **temperature**: 调高温度会使得模型的输出更多样性和创新性，反之，降低温度会使输出内容更加遵循指令要求但减少多样性。建议不要与“Top p”同时调整。'
+        en: '**Temperature**:\n\n- When you increase this value, the model outputs more diverse and innovative content; when you decrease it, the model outputs less diverse content that strictly follows the given instructions.\n- It is recommended not to adjust this value with \"Top p\" at the same time.'
+      type: float
+      min: "0"
+      max: "1"
+      default_val:
+        balance: "0.8"
+        creative: "1"
+        default_val: "1.0"
+        precise: "0.3"
+      precision: 1
+      options: []
+      style:
+        widget: slider
+        label:
+            zh: 生成多样性
+            en: Generation diversity
+    - name: max_tokens
+      label:
+        zh: 最大回复长度
+        en: Response max length
+      desc:
+        zh: 控制模型输出的Tokens 长度上限。通常 100 Tokens 约等于 150 个中文汉字。
+        en: You can specify the maximum length of the tokens output through this value. Typically, 100 tokens are approximately equal to 150 Chinese characters.
+      type: int
+      min: "1"
+      max: "4096"
+      default_val:
+        default_val: "4096"
+      options: []
+      style:
+        widget: slider
+        label:
+            zh: 输入及输出设置
+            en: Input and output settings
+    - name: top_p
+      label:
+        zh: Top P
+        en: Top P
+      desc:
+        zh: '- **Top p 为累计概率**: 模型在生成输出时会从概率最高的词汇开始选择，直到这些词汇的总概率累积达到Top p 值。这样可以限制模型只选择这些高概率的词汇，从而控制输出内容的多样性。建议不要与“生成随机性”同时调整。'
+        en: '**Top P**:\n\n- An alternative to sampling with temperature, where only tokens within the top p probability mass are considered. For example, 0.1 means only the top 10% probability mass tokens are considered.\n- We recommend altering this or temperature, but not both.'
+      type: float
+      min: "0"
+      max: "1"
+      default_val:
+        default_val: "0.7"
+      precision: 2
+      options: []
+      style:
+        widget: slider
+        label:
+            zh: 生成多样性
+            en: Generation diversity
+    - name: frequency_penalty
+      label:
+        zh: 重复语句惩罚
+        en: Frequency penalty
+      desc:
+        zh: '- **frequency penalty**: 当该值为正时，会阻止模型频繁使用相同的词汇和短语，从而增加输出内容的多样性。'
+        en: '**Frequency Penalty**: When positive, it discourages the model from repeating the same words and phrases, thereby increasing the diversity of the output.'
+      type: float
+      min: "-2"
+      max: "2"
+      default_val:
+        default_val: "0"
+      precision: 2
+      options: []
+      style:
+        widget: slider
+        label:
+            zh: 生成多样性
+            en: Generation diversity
+    - name: presence_penalty
+      label:
+        zh: 重复主题惩罚
+        en: Presence penalty
+      desc:
+        zh: '- **presence penalty**: 当该值为正时，会阻止模型频繁讨论相同的主题，从而增加输出内容的多样性'
+        en: '**Presence Penalty**: When positive, it prevents the model from discussing the same topics repeatedly, thereby increasing the diversity of the output.'
+      type: float
+      min: "-2"
+      max: "2"
+      default_val:
+        default_val: "0"
+      precision: 2
+      options: []
+      style:
+        widget: slider
+        label:
+            zh: 生成多样性
+            en: Generation diversity
+    - name: response_format
+      label:
+        zh: 输出格式
+        en: Response format
+      desc:
+        zh: '- **文本**: 使用普通文本格式回复\n- **Markdown**: 将引导模型使用Markdown格式输出回复\n- **JSON**: 将引导模型使用JSON格式输出'
+        en: '**Response Format**:\n\n- **Text**: Replies in plain text format\n- **Markdown**: Uses Markdown format for replies\n- **JSON**: Uses JSON format for replies'
+      type: int
+      min: ""
+      max: ""
+      default_val:
+        default_val: "0"
+      options:
+        - label: Text
+          value: "0"
+        - label: Markdown
+          value: "1"
+        - label: JSON
+          value: "2"
+      style:
+        widget: radio_buttons
+        label:
+            zh: 输入及输出设置
+            en: Input and output settings
+meta:
+    name: glm-4.5
+    protocol: openai
+    capability:
+        function_call: true
+        input_modal:
+            - text
+        input_tokens: 128000
+        json_mode: false
+        max_tokens: 128000
+        output_modal:
+            - text
+        output_tokens: 16384
+        prefix_caching: true
+        reasoning: true
+        prefill_response: false
+    conn_config:
+        base_url: "https://open.bigmodel.cn/api/paas/v4"
+        api_key: ""
+        timeout: 0s
+        model: "glm-4.5"
+        temperature: 0.7
+        frequency_penalty: 0
+        presence_penalty: 0
+        max_tokens: 4096
+        top_p: 1
+        top_k: 0
+        stop: []
+        openai:
+            by_azure: false
+            api_version: ""
+            response_format:
+                type: text
+                jsonschema: null
+        claude: null
+        ark: null
+        deepseek: null
+        qwen: null
+        gemini: null
+        custom: {}
+    status: 0