wehub/anomalyco--models.dev
1
0
Fork 0
Code Issues Pull Requests Actions 2 Deployments Models Agent Notes Packages Projects Releases Wiki Activity

docs: make Chinese README the default

Browse Source
This commit is contained in:
wehub-resource-sync
2026-07-13 10:18:45 +00:00
parent 766dabe633
commit 6e60f69e15
1 changed files with 110 additions and 104 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+110 -104
View File
@@ -1,3 +1,9 @@
<!-- WEHUB_ZH_README -->
> [!NOTE]
> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。
> [English](./README.en.md) · [原始项目](https://github.com/anomalyco/models.dev) · [上游 README](https://github.com/anomalyco/models.dev/blob/HEAD/README.md)
> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
<p align="center">
<a href="https://models.dev">
<picture>
@@ -10,27 +16,27 @@
---
[Models.dev](https://models.dev) is a comprehensive open-source database of AI model specifications, pricing, and capabilities.
[Models.dev](https://models.dev) 是一个全面的开源 AI 模型规格、定价与能力数据库。
There's no single database with information about all the available AI models. We started Models.dev as a community-contributed project to address this. We also use it internally in [opencode](https://opencode.ai).
目前没有一个数据库能涵盖所有可用 AI 模型的信息。我们发起 Models.dev，作为一个社区贡献项目来解决这一问题。我们也在 [opencode](https://opencode.ai). 内部使用它。
## API
You can access this data through an API.
你可以通过 API 访问这些数据。
```bash
curl https://models.dev/api.json
```
Use the **Model ID** field to do a lookup on any model; it's the identifier used by [AI SDK](https://ai-sdk.dev/).
使用 **Model ID** 字段查询任意模型；这是 [AI SDK](https://ai-sdk.dev/). 使用的标识符。
Provider-agnostic model metadata is available separately:
与提供商无关（provider-agnostic）的模型元数据可单独获取：
```bash
curl https://models.dev/models.json
```
Use this for facts about the model itself, independent of where it is served. If you need both provider endpoints and model-only metadata in one response:
用于获取模型本身的事实信息，与由何处提供服务无关。若需要在一个响应中同时获取提供商端点与仅含模型的元数据：
```bash
curl https://models.dev/catalog.json
@@ -38,33 +44,33 @@ curl https://models.dev/catalog.json
### Logos
Provider logos are available as SVG files:
提供商标志以 SVG 文件形式提供：
```bash
curl https://models.dev/logos/{provider}.svg
```
Replace `{provider}` with the **Provider ID** (e.g., `anthropic`, `openai`, `google`). If we don't have a provider's logo, a default logo is served instead.
将 `{provider}` 替换为 **Provider ID**（例如 `anthropic`、`openai`、`google`）。若我们没有某提供商的标志，将返回默认标志。
## Contributing
The data is stored in the repo as TOML files; organized by provider and model. The logo is stored as an SVG. This is used to generate this page and power the API.
数据以 TOML 文件形式存储在仓库中，按提供商和模型组织。标志存储为 SVG。这些内容用于生成本页面并驱动 API。
We need your help keeping the data up to date.
我们需要你的帮助来保持数据最新。
### Adding Model Metadata
Model-only facts live in `models/`, using the same path-style IDs as provider models. For example, `models/openai/gpt-5.toml` defines metadata for the underlying GPT-5 model, while `providers/openai/models/gpt-5.toml` defines OpenAI-specific serving details such as pricing.
仅含模型的事实信息存放在 `models/`，使用与提供商模型相同的路径式 ID。例如，`models/openai/gpt-5.toml` 定义底层 GPT-5 模型的元数据，而 `providers/openai/models/gpt-5.toml` 定义 OpenAI 特定的服务详情（如定价）。
Use model metadata for provider-agnostic facts:
将模型元数据用于与提供商无关的事实：
- `name`, `family`, `release_date`, `last_updated`, `knowledge`
- `attachment`, `reasoning`, `tool_call`, `structured_output`, `temperature`
- `[limit]` defaults like context, input, and output token limits
- `[modalities]` defaults
- `open_weights`, `license`, `links`, `weights`, and `benchmarks`
- `name`、`family`、`release_date`、`last_updated`、`knowledge`
- `attachment`、`reasoning`、`tool_call`、`structured_output`、`temperature`
- `[limit]` 默认值，如上下文、输入与输出 token 限制
- `[modalities]` 默认值
- `open_weights`、`license`、`links`、`weights` 以及 `benchmarks`
Example:
示例：
```toml
name = "GPT-5"
@@ -99,7 +105,7 @@ url = "https://huggingface.co/example/model"
format = "safetensors"
```
Provider TOMLs can inherit these facts with `base_model` and then keep only provider-specific fields or overrides:
提供商 TOML 可通过 `base_model` 继承这些事实，然后仅保留提供商特定字段或覆盖项：
```toml
base_model = "openai/gpt-5"
@@ -114,18 +120,18 @@ context = 200_000 # optional provider override
output = 32_000
```
Provider fields win over model metadata during generation. Use this when the underlying model is the same but a provider serves it with different context limits, modalities, features, or pricing.
生成时，提供商字段优先于模型元数据。当底层模型相同，但提供商以不同的上下文限制、模态、功能或定价提供服务时，请使用此方式。
### Adding a New Provider Model
To add a new model, start by checking if the provider already exists in the `providers/` directory. If not, then:
要添加新模型，请先检查该提供商是否已存在于 `providers/` 目录中。若不存在，则：
#### 1. Create a Provider
If the provider isn't already in `providers/`:
若提供商尚未在 `providers/` 中：
1. Create a new folder in `providers/` with the provider's ID. For example, `providers/newprovider/`.
2. Add a `provider.toml` with the provider details:
1. 在 `providers/` 中创建一个以提供商 ID 命名的新文件夹。例如 `providers/newprovider/`。
2. 添加包含提供商详情的 `provider.toml`：
```toml
name = "Provider Name"
@@ -134,7 +140,7 @@ If the provider isn't already in `providers/`:
doc = "https://example.com/docs/models" # Link to provider's documentation
```
If the provider doesn’t publish an npm package but exposes an OpenAI-compatible endpoint, set the npm field accordingly and include the base URL:
若提供商未发布 npm 包，但暴露了 OpenAI 兼容端点，请相应设置 npm 字段并包含 base URL：
```toml
npm = "@ai-sdk/openai-compatible" # Use OpenAI-compatible SDK
@@ -143,12 +149,12 @@ If the provider isn't already in `providers/`:
#### 2. Add a Logo (optional)
To add a logo for the provider:
要为提供商添加标志：
1. Add a `logo.svg` file to the provider's directory (e.g., `providers/newprovider/logo.svg`)
2. Use SVG format with no fixed size or colors - use `currentColor` for fills/strokes
1. 在提供商目录中添加 `logo.svg` 文件（例如 `providers/newprovider/logo.svg`）
2. 使用 SVG 格式，不固定尺寸或颜色——填充/描边使用 `currentColor`
Example SVG structure:
SVG 结构示例：
```svg
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="currentColor">
@@ -158,9 +164,9 @@ Example SVG structure:
#### 3. Add a Model Definition
Create a new TOML file in the provider's `models/` directory where the filename is the model ID.
在提供商的 `models/` 目录中创建新的 TOML 文件，文件名为模型 ID。
If the model ID contains `/`, use subfolders. For example, for the model ID `openai/gpt-5`, create a folder `openai/` and place a file named `gpt-5.toml` inside it.
若模型 ID 包含 `/`，请使用子文件夹。例如，对于模型 ID `openai/gpt-5`，创建文件夹 `openai/`，并在其中放置名为 `gpt-5.toml` 的文件。
```toml
name = "Model Display Name"
@@ -198,9 +204,9 @@ field = "reasoning_content" # Name of the interleaved field "reasoning_content"
#### 3a. Reuse Model Metadata with `base_model`
For wrapper providers that mirror an existing model, prefer referencing the model-only metadata instead of duplicating provider-agnostic fields.
对于镜像现有模型的封装提供商（wrapper provider），优先引用仅含模型的元数据，而不是重复与提供商无关的字段。
Use `base_model` when the provider serves the same underlying model and only provider-specific fields differ.
当提供商提供相同的底层模型，且仅提供商特定字段不同时，使用 `base_model`。
```toml
base_model = "anthropic/claude-opus-4-6"
@@ -210,96 +216,96 @@ input = 5.00
output = 25.00
```
Rules:
规则：
- `base_model` must point to a TOML file in `models/` using `<provider>/<model-id>`.
- You can override any top-level model field locally.
- If you override a nested table like `[cost]`, `[limit]`, or `[modalities]`, include the full values needed for that table.
- `base_model_omit` is optional and removes inherited model metadata fields after local overrides are merged. Use dot-path strings, for example `base_model_omit = ["limit.input"]`.
- `id` still comes from the filename; do not add it to the TOML.
- `base_model` 必须指向 `models/` 中的 TOML 文件，使用 `<provider>/<model-id>`。
- 你可以在本地覆盖任何顶层模型字段。
- 若覆盖嵌套表（如 `[cost]`、`[limit]` 或 `[modalities]`），请包含该表所需的完整值。
- `base_model_omit` 为可选项，在合并本地覆盖后会移除继承的模型元数据字段。使用点路径字符串，例如 `base_model_omit = ["limit.input"]`。
- `id` 仍来自文件名；请勿将其添加到 TOML 中。
Use `base_model` when the wrapper model is materially the same as the source model and only differs by provider-specific pricing, limits, modalities, provider request shape, or lifecycle flags.
当封装模型在实质上与源模型相同，仅因提供商特定的定价、限制、模态、提供商请求结构或生命周期标志而有所不同时，使用 `base_model`。
Sync and generator scripts should preserve existing `base_model` / `base_model_omit` fields when updating provider TOMLs. Do not use legacy `[extends]` tables.
同步与生成脚本在更新提供商 TOML 时应保留现有的 `base_model` / `base_model_omit` 字段。请勿使用旧版 `[extends]` 表。
#### 4. Submit a Pull Request
1. Fork this repo
2. Create a new branch with your changes
3. Add your provider and/or model files
4. Open a PR with a clear description
1. Fork 本仓库
2. 创建包含你更改的新分支
3. 添加你的提供商和/或模型文件
4. 提交 PR，并附上清晰的描述
### Validation
### 验证
There's a GitHub Action that will automatically validate your submission against our schema to ensure:
有一个 GitHub Action 会根据我们的 schema 自动验证你的提交，以确保：
- All required fields are present
- Data types are correct
- Values are within acceptable ranges
- TOML syntax is valid
- 所有必填字段都已存在
- 数据类型正确
- 值在可接受范围内
- TOML 语法有效
When moving existing provider fields into model metadata, compare generated output before and after the change:
将现有 provider 字段迁移到 model metadata 时，请在修改前后对比生成的输出：
```bash
bun run compare:migrations
```
This prints a diff for each changed model TOML so you can confirm the generated JSON only changed where you intended.
这会为每个变更的 model TOML 打印 diff，以便你确认生成的 JSON 仅在你预期的位置发生变化。
### Schema Reference
### Schema 参考
Models must conform to the following schema, as defined in `packages/core/src/schema.ts`.
模型必须符合以下 schema，定义见 `packages/core/src/schema.ts`。
**Provider Schema:**
**Provider Schema：**
- `name`: String - Display name of the provider
- `npm`: String - AI SDK Package name
- `env`: String[] - Environment variable keys used for auth
- `doc`: String - Link to the provider's documentation
- `api` _(optional)_: String - OpenAI-compatible API endpoint. Required only when using `@ai-sdk/openai-compatible` as the npm package
- `name`: String - 提供商的显示名称
- `npm`: String - AI SDK 包名
- `env`: String[] - 用于身份验证的环境变量键名
- `doc`: String - 提供商文档链接
- `api` _(optional)_: String - 兼容 OpenAI 的 API 端点。仅在使用 `@ai-sdk/openai-compatible` 作为 npm 包时才需要
**Model Schema:**
**Model Schema：**
- `name`: String — Display name of the model
- `attachment`: Boolean — Supports file attachments
- `reasoning`: Boolean — Supports reasoning / chain-of-thought
- `tool_call`: Boolean - Supports tool calling
- `structured_output` _(optional)_: Boolean — Supports structured output feature
- `temperature` _(optional)_: Boolean — Supports temperature control
- `knowledge` _(optional)_: String — Knowledge-cutoff date in `YYYY-MM` or `YYYY-MM-DD` format
- `release_date`: String — First public release date in `YYYY-MM` or `YYYY-MM-DD`
- `last_updated`: String — Most recent update date in `YYYY-MM` or `YYYY-MM-DD`
- `open_weights`: Boolean - Indicate the model's trained weights are publicly available
- `interleaved` _(optional)_: Boolean or Object — Supports interleaved reasoning. Use `true` for general support or an object with `field` to specify the format
- `interleaved.field`: String — Name of the interleaved field (`"reasoning_content"` or `"reasoning_details"`)
- `cost.input`: Number — Cost per million input tokens (USD)
- `cost.output`: Number — Cost per million output tokens (USD)
- `cost.reasoning` _(optional)_: Number — Cost per million reasoning tokens (USD)
- `cost.cache_read` _(optional)_: Number — Cost per million cached read tokens (USD)
- `cost.cache_write` _(optional)_: Number — Cost per million cached write tokens (USD)
- `cost.input_audio` _(optional)_: Number — Cost per million audio input tokens, if billed separately (USD)
- `cost.output_audio` _(optional)_: Number — Cost per million audio output tokens, if billed separately (USD)
- `limit.context`: Number — Maximum context window (tokens)
- `limit.input`: Number — Maximum input tokens
- `limit.output`: Number — Maximum output tokens
- `modalities.input`: Array of strings — Supported input modalities (e.g., ["text", "image", "audio", "video", "pdf"])
- `modalities.output`: Array of strings — Supported output modalities (e.g., ["text"])
- `status` _(optional)_: String — Supported status:
- `alpha` - Indicate the model is in alpha testing
- `beta` - Indicate the model is in beta testing
- `deprecated` - Indicate the model is no longer served by the provider's public API
- `name`: String — 模型的显示名称
- `attachment`: Boolean — 是否支持文件附件
- `reasoning`: Boolean — 是否支持推理 / chain-of-thought
- `tool_call`: Boolean - 是否支持工具调用
- `structured_output` _(optional)_: Boolean — 是否支持结构化输出
- `temperature` _(optional)_: Boolean — 是否支持 temperature 控制
- `knowledge` _(optional)_: String — 知识截止日期，格式为 `YYYY-MM` 或 `YYYY-MM-DD`
- `release_date`: String — 首次公开发布日期，格式为 `YYYY-MM` 或 `YYYY-MM-DD`
- `last_updated`: String — 最近更新日期，格式为 `YYYY-MM` 或 `YYYY-MM-DD`
- `open_weights`: Boolean - 表示模型的训练权重是否公开可用
- `interleaved` _(optional)_: Boolean or Object — 是否支持交错推理（interleaved reasoning）。使用 `true` 表示通用支持，或使用包含 `field` 的对象来指定格式
- `interleaved.field`: String — 交错字段名称（`"reasoning_content"` 或 `"reasoning_details"`）
- `cost.input`: Number — 每百万输入 token 的费用（USD）
- `cost.output`: Number — 每百万输出 token 的费用（USD）
- `cost.reasoning` _(optional)_: Number — 每百万推理 token 的费用（USD）
- `cost.cache_read` _(optional)_: Number — 每百万缓存读取 token 的费用（USD）
- `cost.cache_write` _(optional)_: Number — 每百万缓存写入 token 的费用（USD）
- `cost.input_audio` _(optional)_: Number — 每百万音频输入 token 的费用（如单独计费）（USD）
- `cost.output_audio` _(optional)_: Number — 每百万音频输出 token 的费用（如单独计费）（USD）
- `limit.context`: Number — 最大上下文窗口（token 数）
- `limit.input`: Number — 最大输入 token 数
- `limit.output`: Number — 最大输出 token 数
- `modalities.input`: Array of strings — 支持的输入模态（例如 ["text", "image", "audio", "video", "pdf"]）
- `modalities.output`: Array of strings — 支持的输出模态（例如 ["text"]）
- `status` _(optional)_: String — 支持状态：
- `alpha` - 表示模型处于 alpha 测试阶段
- `beta` - 表示模型处于 beta 测试阶段
- `deprecated` - 表示模型已不再通过提供商的公开 API 提供服务
### Examples
### 示例
See existing providers in the `providers/` directory for reference:
请参阅 `providers/` 目录中的现有提供商作为参考：
- `providers/anthropic/` - Anthropic Claude models
- `providers/openai/` - OpenAI GPT models
- `providers/google/` - Google Gemini models
- `providers/anthropic/` - Anthropic Claude 模型
- `providers/openai/` - OpenAI GPT 模型
- `providers/google/` - Google Gemini 模型
### Working on frontend
### 前端开发
Make sure you have [Bun](https://bun.sh/) installed.
请确保已安装 [Bun](https://bun.sh/)。
```bash
$ bun install
@@ -307,11 +313,11 @@ $ cd packages/web
$ bun run dev
```
And it'll open the frontend at http://localhost:3000
前端将在 http://localhost:3000 打开。
### Manual testing with opencode
### 使用 opencode 进行手动测试
You can manually check provider changes with opencode by:
你可以通过 opencode 手动检查 provider 变更：
```bash
$ bun install
@@ -320,12 +326,12 @@ $ bun run build
$ OPENCODE_MODELS_PATH="dist/_api.json" opencode
```
### Questions?
### 有问题？
Open an issue if you need help or have questions about contributing.
如需帮助或对贡献有疑问，请提交 issue。
---
Models.dev is created by the maintainers of [SST](https://sst.dev).
Models.dev 由 [SST](https://sst.dev). 维护者创建。
**Join our community** [Discord](https://sst.dev/discord) | [YouTube](https://www.youtube.com/c/sst-dev) | [X.com](https://x.com/SST_dev)
**加入我们的社区** [Discord](https://sst.dev/discord) | [YouTube](https://www.youtube.com/c/sst-dev) | [X.com](https://x.com/SST_dev)