feat: add support for Zhipu GLM 4.5 series models #659

yyhhyyyyyy · 2025-07-30T07:05:14Z

close #652
add support for Zhipu GLM 4.5 series models

Summary by CodeRabbit

New Features
- Added support for five new "GLM 4.5" series models under the Zhipu provider, including GLM-4.5, GLM-4.5-Air, GLM-4.5-X, GLM-4.5-AirX, and GLM-4.5-Flash.
- These models feature enhanced context length, token limits, and advanced reasoning capabilities.

coderabbitai · 2025-07-30T07:05:20Z

Walkthrough

The changes introduce five new "GLM-4.5" series models to the Zhipu (BigModel.cn) provider across three files. These models are added to the default model settings, the provider-specific configuration, and the list of models returned by the Zhipu provider, enabling their selection and use within the application.

Changes

Cohort / File(s)	Change Summary
Default Model Settings `src/main/presenter/configPresenter/modelDefaultSettings.ts`	Added five new "GLM-4.5" series model entries to the `defaultModelsSettings` array, specifying their properties and capabilities.
Provider Model Settings `src/main/presenter/configPresenter/providerModelSettings.ts`	Populated the "zhipu" provider's `models` array with the five new "GLM-4.5" series models and their configurations.
Zhipu Provider Models `src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts`	Extended the array returned by `fetchOpenAIModels` to include the five new "GLM-4.5" series models with appropriate metadata.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant App
    participant ZhipuProvider

    User->>App: Open provider model selection
    App->>ZhipuProvider: fetchOpenAIModels()
    ZhipuProvider-->>App: Return models (incl. GLM-4.5 series)
    App-->>User: Display GLM-4.5 series models for selection

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~7 minutes

Assessment against linked issues

Objective	Addressed	Explanation
Add support for GLM-4.5 model in BigModel.cn provider configuration and selection (#652)	✅

Assessment against linked issues: Out-of-scope changes

No out-of-scope changes found.

Possibly related PRs

feat: 添加 Kimi K2 Preview 模型默认设置 #592: Adds a Kimi K2 Preview model to the same default model settings array, related by extending the list of available models.

Poem

Five new models hop into view,
GLM-4.5—now ready for you!
Zhipu’s menu grows so wide,
With Air, X, and Flash inside.
Rabbits cheer and models gleam—
BigModel.cn fulfills your dream!
🐇✨

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Reviewing files that changed from the base of the PR and between a26907c and ae6ca29.

📒 Files selected for processing (3)

src/main/presenter/configPresenter/modelDefaultSettings.ts (1 hunks)
src/main/presenter/configPresenter/providerModelSettings.ts (1 hunks)
src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts (1 hunks)

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**/*.{ts,tsx,js,jsx,vue}

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Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

**/*.{ts,tsx}

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Strict type checking enabled for TypeScript

**/*.{ts,tsx}: 始终使用 try-catch 处理可能的错误
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日志应包含时间戳、日志级别、错误代码、错误描述、堆栈跟踪（如适用）、相关上下文信息
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Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/main/**/*.ts

📄 CodeRabbit Inference Engine (CLAUDE.md)

Main to Renderer: Use EventBus to broadcast events via mainWindow.webContents.send()

Use Electron's built-in APIs for file system and native dialogs

Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/main/presenter/**/*.ts

📄 CodeRabbit Inference Engine (CLAUDE.md)

One presenter per functional domain

Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/main/presenter/llmProviderPresenter/providers/*.ts

📄 CodeRabbit Inference Engine (CLAUDE.md)

src/main/presenter/llmProviderPresenter/providers/*.ts: Create provider file in src/main/presenter/llmProviderPresenter/providers/ when adding a new LLM provider
Implement coreStream method following standardized event interface in LLM provider files

src/main/presenter/llmProviderPresenter/providers/*.ts: Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.
Provider implementations must use a coreStream method that yields standardized stream events to decouple the main loop from provider-specific details.
The coreStream method in each Provider must perform a single streaming API request per conversation round and must not contain multi-round tool call loop logic.
Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.
All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.
When a provider does not support native function calling, it must prepare messages using prompt wrapping (e.g., prepareFunctionCallPrompt) before making the API call.
When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.
Provider implementations should aggregate and yield usage events as part of the standardized stream.
Provider implementations should yield image data events in the standardized format when applicable.
Provider implementations should yield reasoning events in the standardized format when applicable.
Provider implementations should yield tool call events (`tool_call_star...

Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts

**/*.{js,jsx,ts,tsx}

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Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/{main,renderer}/**/*.ts

📄 CodeRabbit Inference Engine (.cursor/rules/electron-best-practices.mdc)

src/{main,renderer}/**/*.ts: Use context isolation for improved security
Implement proper inter-process communication (IPC) patterns
Optimize application startup time with lazy loading
Implement proper error handling and logging for debugging

Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/main/**/*.{ts,js,tsx,jsx}

📄 CodeRabbit Inference Engine (.cursor/rules/project-structure.mdc)

主进程代码放在 src/main

Files:

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts
src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

src/main/presenter/configPresenter/**/*.ts

📄 CodeRabbit Inference Engine (CLAUDE.md)

Centralize configuration in configPresenter/

Files:

src/main/presenter/configPresenter/providerModelSettings.ts
src/main/presenter/configPresenter/modelDefaultSettings.ts

🧠 Learnings (3)

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts (10)

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/providers.ts : Add provider configuration in configPresenter/providers.ts when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Create provider file in src/main/presenter/llmProviderPresenter/providers/ when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield text events in the standardized format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield tool call events (tool_call_start, tool_call_chunk, tool_call_end) in the standardized format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield events asynchronously using the async generator pattern.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Implement coreStream method following standardized event interface in LLM provider files

src/main/presenter/configPresenter/providerModelSettings.ts (10)

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/providers.ts : Add provider configuration in configPresenter/providers.ts when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider files should implement helper methods such as formatMessages, convertToProviderTools, parseFunctionCalls, and prepareFunctionCallPrompt as needed for provider-specific logic.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Create provider file in src/main/presenter/llmProviderPresenter/providers/ when adding a new LLM provider

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : All provider implementations must parse provider-specific data chunks and yield standardized events for text, reasoning, tool calls, usage, errors, stop reasons, and image data.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/**/*.ts : Centralize configuration in configPresenter/

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Each file in src/main/presenter/llmProviderPresenter/providers/*.ts should handle interaction with a specific LLM API, including request/response formatting, tool definition conversion, native/non-native tool call management, and standardizing output streams to a common event format.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield image data events in the standardized format when applicable.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : When a provider supports native function calling, MCP tools must be converted to the provider's format (e.g., using convertToProviderTools) and included in the API request.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield reasoning events in the standardized format when applicable.

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: .cursor/rules/llm-agent-loop.mdc:0-0
Timestamp: 2025-07-21T01:46:52.880Z
Learning: Applies to src/main/presenter/llmProviderPresenter/providers/*.ts : Provider implementations should yield text events in the standardized format.

src/main/presenter/configPresenter/modelDefaultSettings.ts (2)

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/**/*.ts : Centralize configuration in configPresenter/

Learnt from: CR
PR: ThinkInAIXYZ/deepchat#0
File: CLAUDE.md:0-0
Timestamp: 2025-07-21T01:45:33.790Z
Learning: Applies to src/main/presenter/configPresenter/providers.ts : Add provider configuration in configPresenter/providers.ts when adding a new LLM provider

🔇 Additional comments (3)

src/main/presenter/configPresenter/providerModelSettings.ts (1)

240-297: LGTM! Well-structured GLM 4.5 model configurations.

The addition of the five GLM 4.5 series models is consistent and well-organized. All models follow the established configuration pattern with appropriate parameters for the GLM 4.5 series (8192 maxTokens, 128000 contextLength, function calling and reasoning enabled).

src/main/presenter/llmProviderPresenter/providers/zhipuProvider.ts (1)

14-58: LGTM! Proper integration of GLM 4.5 models into the provider.

The new GLM 4.5 models are correctly added to the fetchOpenAIModels method with consistent metadata. The placement at the beginning of the array is appropriate for newer models, and all parameters align with the configurations in other files.

src/main/presenter/configPresenter/modelDefaultSettings.ts (1)

1370-1426: LGTM! Consistent default settings for GLM 4.5 models.

The default model settings for the GLM 4.5 series are properly configured with consistent parameters across all models. The settings align perfectly with the provider-specific configurations and follow the established pattern in the codebase.

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yyhhyyyyyy added 2 commits July 30, 2025 14:59

feat: add support for Zhipu GLM 4.5 series models

c39a1fc

style: code fmt

ae6ca29

zerob13 merged commit ee85bdf into ThinkInAIXYZ:dev Jul 30, 2025
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coderabbitai bot mentioned this pull request Aug 6, 2025

feat: add support for new models #700

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coderabbitai bot mentioned this pull request Aug 15, 2025

feat: add GLM-4.5V model support #739

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coderabbitai bot mentioned this pull request Dec 26, 2025

chore: bump up deps and update new providers #1221

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