> ## Documentation Index
> Fetch the complete documentation index at: https://docs.rixapi.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# 语言模型

> 语言模型（LLM）使用说明手册

支持通过 OpenAI、Anthropic 和 Gemini AI Studio 兼容接口进行文本生成调用。

## OpenAI 兼容接口 (推荐)

如部分功能本文档未提及，请参考 [OpenAI官方文档](https://platform.openai.com/docs/api-reference/chat/create)

### 消息体结构说明

| **消息类型** | **功能描述**          | **示例内容**                              |
| :- | :- | :- |
| system | 模型指令，设定AI角色，描述模型应一般如何行为和响应 | 例如：“你是有10年经验的儿科医生” |
| user | 用户输入，将最终用户的消息传递给模型 | 例如：“幼儿持续低烧应如何处理？“ |
| assistant | 模型生成的历史回复，为模型提供示例，说明它应该如何回应当前请求 | 例如：“建议先测量体温…” |

若希望模型按照分层指令进行响应，可以利用消息角色来提升输出的质量。不过，消息角色并不总是有确定性的表现，因此建议尝试多种用法，比较不同方法带来的效果，找出最适合你的方案。

### 基础对话

```python Python theme={null} theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
)

response = client.chat.completions.create(
    model="deepseek-r1",
    messages=[
        {
            "role": "user",
            "content": "say 1"
        }
    ]
)

print(response.choices[0].message.content)
```

```javascript Node.js theme={null} theme={null}
import OpenAI from "openai";

const client = new OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
);

const response = await client.chat.completions.create({
  model: "deepseek-r1",
  messages: [
    {
      role: "user",
      content: "say 1",
    },
  ],
});

console.log(response.choices[0].message.content);
```

### 流式响应

```python Python theme={null} theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
)

stream = client.chat.completions.create(
    model="deepseek-r1",
    messages=[
        {
            "role": "user",
            "content": "写一首关于春天的诗"
        }
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
```

```javascript Node.js theme={null} theme={null}
import OpenAI from "openai";

const client = new OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
);

const stream = await client.chat.completions.create({
  model: "deepseek-r1",
  messages: [
    {
      role: "user",
      content: "写一首关于春天的诗",
    },
  ],
  stream: true,
});

for await (const chunk of stream) {
  if (chunk.choices[0].delta.content) {
    process.stdout.write(chunk.choices[0].delta.content);
  }
}
```

### 工具调用（Function Calling）

更多详情参考 [OpenAI 函数调用指南](https://platform.openai.com/docs/guides/tools)

```python Python theme={null} theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取指定城市的天气信息",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "城市名称"
                    }
                },
                "required": ["city"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="deepseek-r1",
    messages=[
        {
            "role": "user",
            "content": "北京今天天气怎么样？"
        }
    ],
    tools=tools
)

print(response.choices[0].message)
```

```javascript Node.js theme={null} theme={null}
import OpenAI from "openai";

const client = new OpenAI(
    base_url="https://api.ephone.ai/v1",
    api_key="", # 替换为你在本站点的 API Key
);

const tools = [
  {
    type: "function",
    function: {
      name: "get_weather",
      description: "获取指定城市的天气信息",
      parameters: {
        type: "object",
        properties: {
          city: {
            type: "string",
            description: "城市名称",
          },
        },
        required: ["city"],
      },
    },
  },
];

const response = await client.chat.completions.create({
  model: "deepseek-r1",
  messages: [
    {
      role: "user",
      content: "北京今天天气怎么样？",
    },
  ],
  tools: tools,
});

console.log(response.choices[0].message);
```

### Response 接口

* 目前该接口仅支持OpenAI模型
* 具体使用方案请参考 [OpenAI官方文档](https://platform.openai.com/docs/api-reference/responses/create)

### 注意事项

如果在使用过程中遇到任何问题：

* 联系我们的技术支持团队
* 在我们的 [工单中心](#) 提交工单反馈

> [!WARNING]
>
> 1. 使用时需要将 `OPENAI_BASE_URL` 设置为 `https://api.ephone.ai/v1`
> 2. `OPENAI_API_KEY` 应设置为您的 API Key
> 3. 部分模型不支持 `presence_penalty`、`frequency_penalty`、`logit_bias` 等参数，传入会被忽略
> 4. 旧版的 `function_call` 参数已废弃，请使用 `tools`

## Anthropic 兼容接口

如部分功能本文档未提及，请参考 [Anthropic官方文档](https://docs.claude.com/en/api/messages)

### 基础对话

```python Python theme={null} theme={null}
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
)

message = client.messages.create(
    model="deepseek-r1",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": "请用简单的语言解释什么是机器学习"
        }
    ]
)

print(message.content[0].text)
```

```javascript Node.js theme={null} theme={null}
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
);

const message = await client.messages.create({
  model: "deepseek-r1",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: "请用简单的语言解释什么是机器学习",
    },
  ],
});

console.log(message.content[0].text);
```

### 流式响应

```python Python theme={null} theme={null}
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
)

with client.messages.stream(
    model="deepseek-r1",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": "写一首关于春天的诗"
        }
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```

```javascript Node.js theme={null} theme={null}
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
);

const stream = await client.messages.stream({
  model: "deepseek-r1",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: "写一首关于春天的诗",
    },
  ],
});

for await (const chunk of stream) {
  if (
    chunk.type === "content_block_delta" &&
    chunk.delta.type === "text_delta"
  ) {
    process.stdout.write(chunk.delta.text);
  }
}
```

### 工具调用（Function Calling）

更多详情参考 [Anthropic 函数调用指南](https://docs.claude.com/en/docs/agents-and-tools/tool-use/overview)

```python Python theme={null} theme={null}
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
)

tools = [
    {
        "name": "get_weather",
        "description": "获取指定城市的天气信息",
        "input_schema": {
            "type": "object",
            "properties": {
                "city": {
                    "type": "string",
                    "description": "城市名称"
                }
            },
            "required": ["city"]
        }
    }
]

message = client.messages.create(
    model="deepseek-r1",
    max_tokens=1024,
    tools=tools,
    messages=[
        {
            "role": "user",
            "content": "北京今天天气怎么样？"
        }
    ]
)

print(message.content)
```

```javascript Node.js theme={null} theme={null}
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic(
    base_url="https://api.ephone.ai/anthropic",
    api_key=""  # 替换为你在本站点的 API Key
);

const tools = [
  {
    name: "get_weather",
    description: "获取指定城市的天气信息",
    input_schema: {
      type: "object",
      properties: {
        city: {
          type: "string",
          description: "城市名称",
        },
      },
      required: ["city"],
    },
  },
];

const message = await client.messages.create({
  model: "deepseek-r1",
  max_tokens: 1024,
  tools: tools,
  messages: [
    {
      role: "user",
      content: "北京今天天气怎么样？",
    },
  ],
});

console.log(message.content);
```

> [!WARNING]
>
> 1. 使用时需要将 `ANTHROPIC_BASE_URL` 设置为 `https://api.ephone.ai/anthropic`
> 2. `ANTHROPIC_API_KEY` 应设置为您的 API Key

***

## Gemini AI Studio 兼容接口

Gemini 模型支持通过 Google AI Studio 官方 API 格式直接调用，无需转换为 OpenAI 格式。适用于已使用 Google `genai` SDK 的项目。

如部分功能本文档未提及，请参考 [Google AI Studio 官方文档](https://ai.google.dev/gemini-api/docs)

### 基础对话

```python Python theme={null} theme={null}
from google import genai
from google.genai import types

client = genai.Client(
    api_key="",  # 替换为你在本站点的 API Key
    http_options=types.HttpOptions(
        api_version="v1beta",
        base_url="https://api.ephone.ai",
    ),
)

response = client.models.generate_content(
    model="gemini-2.5-pro",
    contents="你好，请做一下自我介绍",
)

print(response.text)
```

```javascript Node.js theme={null} theme={null}
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({
  apiKey: "",  // 替换为你在本站点的 API Key
  httpOptions: {
    apiVersion: "v1beta",
    baseUrl: "https://api.ephone.ai",
  },
});

const response = await ai.models.generateContent({
  model: "gemini-2.5-pro",
  contents: "你好，请做一下自我介绍",
});

console.log(response.text);
```

### 流式响应

```python Python theme={null} theme={null}
from google import genai
from google.genai import types

client = genai.Client(
    api_key="",  # 替换为你在本站点的 API Key
    http_options=types.HttpOptions(
        api_version="v1beta",
        base_url="https://api.ephone.ai",
    ),
)

for chunk in client.models.generate_content_stream(
    model="gemini-2.5-pro",
    contents="写一首关于春天的诗",
):
    print(chunk.text, end="", flush=True)
```

```javascript Node.js theme={null} theme={null}
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({
  apiKey: "",  // 替换为你在本站点的 API Key
  httpOptions: {
    apiVersion: "v1beta",
    baseUrl: "https://api.ephone.ai",
  },
});

const response = await ai.models.generateContentStream({
  model: "gemini-2.5-pro",
  contents: "写一首关于春天的诗",
});

for await (const chunk of response) {
  process.stdout.write(chunk.text());
}
```

### 工具调用（Function Calling）

更多详情参考 [Google AI Studio 函数调用指南](https://ai.google.dev/gemini-api/docs/function-calling)

```python Python theme={null} theme={null}
from google import genai
from google.genai import types

client = genai.Client(
    api_key="",  # 替换为你在本站点的 API Key
    http_options=types.HttpOptions(
        api_version="v1beta",
        base_url="https://api.ephone.ai",
    ),
)

get_weather = types.FunctionDeclaration(
    name="get_weather",
    description="获取指定城市的天气信息",
    parameters=types.Schema(
        type="OBJECT",
        properties={
            "city": types.Schema(type="STRING", description="城市名称"),
        },
        required=["city"],
    ),
)

response = client.models.generate_content(
    model="gemini-2.5-pro",
    contents="北京今天天气怎么样？",
    config=types.GenerateContentConfig(
        tools=[types.Tool(function_declarations=[get_weather])]
    ),
)

print(response.candidates[0].content.parts)
```

```javascript Node.js theme={null} theme={null}
import { GoogleGenAI, Type } from "@google/genai";

const ai = new GoogleGenAI({
  apiKey: "",  // 替换为你在本站点的 API Key
  httpOptions: {
    apiVersion: "v1beta",
    baseUrl: "https://api.ephone.ai",
  },
});

const response = await ai.models.generateContent({
  model: "gemini-2.5-pro",
  contents: "北京今天天气怎么样？",
  config: {
    tools: [
      {
        functionDeclarations: [
          {
            name: "get_weather",
            description: "获取指定城市的天气信息",
            parameters: {
              type: Type.OBJECT,
              properties: {
                city: { type: Type.STRING, description: "城市名称" },
              },
              required: ["city"],
            },
          },
        ],
      },
    ],
  },
});

console.log(response.candidates[0].content.parts);
```

> [!WARNING]
>
> 1. `base_url` / `baseUrl` 设置为 `https://api.ephone.ai`（不含 `/v1beta` 后缀，SDK 会自动拼接）
> 2. `api_version` / `apiVersion` 建议设为 `v1beta`
> 3. `api_key` / `apiKey` 应设置为您在本站点的 API Key
> 4. 依赖安装：Python 使用 `pip install google-genai`，Node.js 使用 `npm install @google/genai`

## 相关链接

> [card] [OpenAI 官方文档](https://platform.openai.com/docs/guides/text)
>
> OpenAI Chat Completions API

> [card] [Anthropic 官方文档](https://docs.claude.com/en/api/messages)
>
> Anthropic Messages API

> [card] [Google AI Studio 官方文档](https://ai.google.dev/gemini-api/docs)
>
> Gemini GenerateContent API


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