From 5e2fa131263b8fb1ae519f4f8d680b2458ba6007 Mon Sep 17 00:00:00 2001
From: Waffle <52460705+ox01024@users.noreply.github.com>
Date: Thu, 8 Aug 2024 10:54:39 +0800
Subject: [PATCH] feat: support glm-4-long (#7070)

Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
---
 .../zhipuai/llm/glm_4_long.yaml               | 33 +++++++++++++++++++
 1 file changed, 33 insertions(+)
 create mode 100644 api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml

diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml
new file mode 100644
index 0000000000..9d92e58f6c
--- /dev/null
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml
@@ -0,0 +1,33 @@
+model: glm-4-long
+label:
+  en_US: glm-4-long
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 10240
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    default: 0.95
+    min: 0.0
+    max: 1.0
+    help:
+      zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: top_p
+    use_template: top_p
+    default: 0.7
+    min: 0.0
+    max: 1.0
+    help:
+      zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: max_tokens
+    use_template: max_tokens
+    default: 1024
+    min: 1
+    max: 4096