feat(moonshot): add kimi-k3 and kimi-k2.7-code model support

Author: lin-snow

models/moonshot/manifest.yaml

@@ -1,8 +1,8 @@
 author: langgenius
 created_at: '2024-09-20T00:13:50.29298939-04:00'
 description:
-  en_US: Models provided by Moonshot, such as kimi-k2.6, kimi-k2.5, kimi-k2, moonshot-v1-8k, moonshot-v1-32k, and moonshot-v1-128k.
-  zh_Hans: Moonshot 提供的模型，例如 kimi-k2.6, kimi-k2.5, kimi-k2, moonshot-v1-8k、moonshot-v1-32k 和 moonshot-v1-128k。
+  en_US: Models provided by Moonshot, such as kimi-k3, kimi-k2.7-code, kimi-k2.6, kimi-k2.5, kimi-k2, moonshot-v1-8k, moonshot-v1-32k, and moonshot-v1-128k.
+  zh_Hans: Moonshot 提供的模型，例如 kimi-k3, kimi-k2.7-code, kimi-k2.6, kimi-k2.5, kimi-k2, moonshot-v1-8k、moonshot-v1-32k 和 moonshot-v1-128k。
 icon: icon_s_en.png
 label:
   en_US: Moonshot
@@ -34,4 +34,4 @@ resource:
     tool:
       enabled: true
 type: plugin
-version: 0.1.8
+version: 0.1.9

models/moonshot/models/llm/_position.yaml

@@ -8,3 +8,6 @@
 - kimi-k2-thinking-turbo
 - kimi-k2.5
 - kimi-k2.6
+- kimi-k2.7-code
+- kimi-k2.7-code-highspeed
+- kimi-k3

models/moonshot/models/llm/kimi-k2.7-code-highspeed.yaml

@@ -0,0 +1,37 @@
+model: kimi-k2.7-code-highspeed
+label:
+  zh_Hans: kimi-k2.7-code-highspeed
+  en_US: kimi-k2.7-code-highspeed
+model_type: llm
+features:
+  - vision
+  - agent-thought
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 262144
+parameter_rules:
+  - name: max_tokens
+    use_template: max_tokens
+    default: 32768
+    min: 1
+    max: 262144
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: Response Format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '13'
+  output: '54'
+  unit: '0.000001'
+  currency: RMB

models/moonshot/models/llm/kimi-k2.7-code.yaml

@@ -0,0 +1,37 @@
+model: kimi-k2.7-code
+label:
+  zh_Hans: kimi-k2.7-code
+  en_US: kimi-k2.7-code
+model_type: llm
+features:
+  - vision
+  - agent-thought
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 262144
+parameter_rules:
+  - name: max_tokens
+    use_template: max_tokens
+    default: 32768
+    min: 1
+    max: 262144
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: Response Format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '6.5'
+  output: '27'
+  unit: '0.000001'
+  currency: RMB

models/moonshot/models/llm/kimi-k3.yaml

@@ -0,0 +1,37 @@
+model: kimi-k3
+label:
+  zh_Hans: kimi-k3
+  en_US: kimi-k3
+model_type: llm
+features:
+  - vision
+  - agent-thought
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 1048576
+parameter_rules:
+  - name: max_tokens
+    use_template: max_tokens
+    default: 131072
+    min: 1
+    max: 1048576
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: Response Format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '20'
+  output: '100'
+  unit: '0.000001'
+  currency: RMB

models/moonshot/models/llm/llm.py

@@ -156,8 +156,8 @@ def _convert_prompt_message_to_dict(self, message: PromptMessage, credentials: O
         credentials = credentials or {}
         model_name = credentials.get("_current_model", "").lower()
 
-        # 判断是否为支持深度思考模式的模型（K2.5、K2.6 以及 K2-thinking 系列）
-        is_thinking_model = any(x in model_name for x in ["k2.5", "k2.6", "k2-thinking"])
+        # 判断是否为支持深度思考模式的模型（K2.5、K2.6、K2.7、K3 以及 K2-thinking 系列）
+        is_thinking_model = any(x in model_name for x in ["k2.5", "k2.6", "k2.7", "k3", "k2-thinking"])
 
         # Use base implementation for standard conversion
         message_dict = super()._convert_prompt_message_to_dict(message, credentials)