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@deepseek-ai/dsh-model-catalog-bigmodel

Model Catalog Bigmodel

用于 DeepSeek Harness 的 Zhipu AI BigModel 和 GLM Coding Plan LLM 提供商模型目录插件

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add github:OpenSaozi/dsh-bigmodel-catalog#0a74906a907b412e6a41b835af3cff9e6db83c52
README兼容性版本

兼容性与来源证明

Model Catalog Bigmodel 以 @deepseek-ai/dsh-model-catalog-bigmodel 发布,当前版本为 0.1.0-rc.5。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
any
发布来源
github
Registry 更新时间
2026/8/22

版本

0.1.0-rc.5prerelease
2026/8/22

相关插件

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最新版
0.1.0-rc.5
DSH
*
HMR
重启进程
Tree shaking
未声明可安全裁剪
解包体积
未提供
文件数
未提供
Surface
any
许可证
MIT
发布源
github
GitHub
★ 2
周下载
0
最近提交
2026/9/10
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README

DSH Plugin: LLM Provider - BigModel GLM

中文 | English

Allows connecting to the Zhipu AI BigModel / GLM Coding Plan as an LLM Provider, enabling DeepSeek Harness to utilize the dedicated Coding Plan route and unlocking the verified 1M-token context model glm-5.3 (along with glm-4.5, glm-4.6, and glm-5).

Target Audience and Use Cases

Designed for developers with a Zhipu GLM Coding Plan membership or BigModel account who need to analyze large codebases, process long documents, or perform intensive code generation.

Key Features

  • Unlocks 1M Context Window: Directly select glm-5.3 in the model selector, featuring a 1,000,000-token context limit and 128K max output capacity.
  • Tailored for Coding Plan: Connects to Zhipu AI's developer-focused Coding PaaS endpoint (https://open.bigmodel.cn/api/coding/paas/v4/models).
  • Live Reconciled with Verified Exceptions: Combines live endpoint discovery while maintaining verified support for glm-5.3.
  • Independent Provider Route: The plugin registers its own zai adapter. It reuses the exported PiAiAdapter only for message and stream conversion, without depending on llm-pi-ai provider configuration or catalog seams.
  • Secure Credential Isolation: The plugin resolves BIGMODEL_API_KEY through the Harness credential service for each request and never places the key in Cordis configuration or logs.

Installation and Quick Start

Install a reviewed revision into a DeepSeek Harness profile. The repository includes a dsh.bundle patch and prebuilt runtime artifacts so no local build steps are required:

dsh plugin --profile <profile> add github:OpenSaozi/dsh-bigmodel-catalog#<commit-sha>

The installed bundle contributes the following Cordis configuration:

- id: model-catalog-bigmodel
  name: '@deepseek-ai/dsh-model-catalog-bigmodel'
  config:
    apiKeyEnv: BIGMODEL_API_KEY
    baseURL: https://open.bigmodel.cn/api/coding/paas/v4
    displayName: BigModel

The plugin owns the complete zai route: catalog, live filtering, credential resolution, and adapter registration all live in this package. Deployments may override baseURL for another Coding Plan endpoint and apiKeyEnv for another credential reference.

Contributing

Please attach provider evidence for every catalog change: exact model ID, protocol, context/output capacity, reasoning behavior, and direct request verification where applicable. Update both README languages and run package tests in a matching DeepSeek Harness checkout.

License and Disclaimer

MIT License. This community integration is not affiliated with or endorsed by Zhipu AI, BigModel, DeepSeek, or pi-ai.

Model Experience

Catalog Selection

What the model sees

No package-owned text. The plugin controls which BigModel descriptor, such as glm-5.3, can be selected; the exported PiAiAdapter owns request conversion.

Token effect

No direct token effect. Tokenization and context use remain properties of the selected model and pi-ai's z.ai-compatible request implementation.

KV Cache effect

No direct effect. Selecting a different model may change provider-side cache eligibility, but this plugin adds no request content.

Known Limitations and Deferred Work

  • Refresh runs on mount and when the managed credential named by BIGMODEL_API_KEY changes. Failure keeps the maintained catalog and logs the error.
  • The Coding Plan Models endpoint currently omits a directly callable glm-5.3; that exact id is an explicit verified exception.
  • The endpoint supplies ids, not complete capability metadata. Context and output capacities therefore come from the reviewed descriptor table and remain pinned by package tests.