jhqxxx
475 lines
9.3 KiB
Markdown
475 lines
9.3 KiB
Markdown
# API 参考
|
||
|
||
AHA REST API 的完整参考。
|
||
|
||
## 概述
|
||
|
||
AHA 提供了 OpenAI 兼容的 REST API 用于运行 AI 模型推理。所有端点遵循标准 HTTP 约定并返回 JSON 响应。
|
||
|
||
### 基础 URL
|
||
|
||
默认情况下，API 服务器运行在：
|
||
```
|
||
http://127.0.0.1:10100
|
||
```
|
||
|
||
您可以在启动服务时自定义：
|
||
```bash
|
||
aha cli -m qwen3-0.6b -a 0.0.0.0 -p 8080
|
||
```
|
||
|
||
### 身份验证
|
||
|
||
目前，AHA 不需要身份验证。所有端点在配置的地址/端口上公开访问。
|
||
|
||
**安全提示**：如果您将 API 暴露到外部网络，请考虑通过反向代理（如 nginx、traefik）实现身份验证。
|
||
|
||
### 内容类型
|
||
|
||
所有请求应使用：
|
||
```
|
||
Content-Type: application/json
|
||
```
|
||
|
||
### 响应格式
|
||
|
||
成功响应遵循此结构：
|
||
```json
|
||
{
|
||
"data": { ... },
|
||
"model": "model-name",
|
||
"usage": {
|
||
"total_tokens": 30
|
||
}
|
||
}
|
||
```
|
||
|
||
错误响应：
|
||
```json
|
||
{
|
||
"error": {
|
||
"message": "错误描述",
|
||
"type": "error_type",
|
||
"code": "error_code"
|
||
}
|
||
}
|
||
```
|
||
|
||
## 端点
|
||
|
||
### 对话补全
|
||
|
||
生成对话补全或文本响应。
|
||
|
||
#### 端点
|
||
```
|
||
POST /chat/completions
|
||
```
|
||
|
||
#### 请求体
|
||
|
||
| 参数 | 类型 | 必需 | 描述 |
|
||
|------|------|------|------|
|
||
| `model` | string | 是 | 模型标识符（如 "qwen3-0.6b"） |
|
||
| `messages` | array | 是 | 消息对象数组 |
|
||
| `temperature` | number | 否 | 采样温度（0-2，默认：1） |
|
||
| `top_p` | number | 否 | 核采样（0-1，默认：1） |
|
||
| `max_tokens` | integer | 否 | 要生成的最大令牌数 |
|
||
| `stream` | boolean | 否 | 启用流式传输（默认：true） |
|
||
|
||
#### 消息对象
|
||
|
||
| 字段 | 类型 | 必需 | 描述 |
|
||
|------|------|------|------|
|
||
| `role` | string | 是 | "system"、"user" 或 "assistant" |
|
||
| `content` | string/array | 是 | 消息内容（字符串或多模态数组） |
|
||
|
||
#### 多模态内容
|
||
|
||
对于视觉/音频模型，内容可以是数组：
|
||
|
||
```json
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "text", "text": "描述这张图片"},
|
||
{"type": "image", "image_url": {"url": "file:///path/to/image.jpg"}}
|
||
]
|
||
}
|
||
```
|
||
|
||
支持的内容类型：
|
||
- `text` - 文本内容
|
||
- `image` - 图像文件（file://,base64://, https:// 或 http://）
|
||
- `audio` - 音频文件（file://,base64://, https:// 或 http://）
|
||
|
||
#### 示例
|
||
|
||
**简单对话：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "qwen3-0.6b",
|
||
"messages": [
|
||
{"role": "user", "content": "你好！"}
|
||
]
|
||
}'
|
||
```
|
||
|
||
**带系统消息：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "qwen3-0.6b",
|
||
"messages": [
|
||
{"role": "system", "content": "你是一个有用的助手。"},
|
||
{"role": "user", "content": "用一句话解释 Rust。"}
|
||
],
|
||
"max_tokens": 50,
|
||
"temperature": 0.7
|
||
}'
|
||
```
|
||
|
||
**视觉理解：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "qwen3vl-2b",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "text", "text": "这张图片里有什么？"},
|
||
{"type": "image", "image_url": {"url": "file:///path/to/image.jpg"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
**OCR（文本提取）：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "deepseek-ocr",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "text", "text": "提取所有文本"},
|
||
{"type": "image", "image_url": {"url": "file:///path/to/document.png"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
**ASR（语音识别）：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "glm-asr-nano-2512",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "text", "text": "转写这段音频"},
|
||
{"type": "audio", "audio_url": {"url": "file:///path/to/audio.wav"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
**流式响应：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/chat/completions \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "qwen3-0.6b",
|
||
"messages": [
|
||
{"role": "user", "content": "给我讲个故事"}
|
||
],
|
||
"stream": true
|
||
}'
|
||
```
|
||
|
||
流式响应作为服务器发送事件（SSE）发送：
|
||
```
|
||
data: {"id": "1", "choices": [{"delta": {"content": "从前"}}]}
|
||
|
||
data: {"id": "1", "choices": [{"delta": {"content": "有"}}]}
|
||
|
||
data: [DONE]
|
||
```
|
||
|
||
#### 响应
|
||
|
||
**非流式：**
|
||
|
||
```json
|
||
{
|
||
"id": "chatcmpl-123",
|
||
"object": "chat.completion",
|
||
"created": 1677652288,
|
||
"model": "qwen3-0.6b",
|
||
"choices": [
|
||
{
|
||
"index": 0,
|
||
"message": {
|
||
"role": "assistant",
|
||
"content": "你好！今天我能帮你什么？"
|
||
},
|
||
"finish_reason": "stop"
|
||
}
|
||
],
|
||
"usage": {
|
||
"total_tokens": 19
|
||
}
|
||
}
|
||
```
|
||
|
||
#### 支持的模型
|
||
|
||
- 文本：`qwen3-0.6b`、`minicpm4-0.5b`
|
||
- 视觉：`qwen2.5vl-3b`、`qwen2.5vl-7b`、`qwen3vl-2b`、`qwen3vl-4b`、`qwen3vl-8b`、`qwen3vl-32b`
|
||
- OCR：`deepseek-ocr`、`hunyuan-ocr`、`paddleocr-vl`
|
||
- ASR：`glm-asr-nano-2512`、`fun-asr-nano-2512`、`qwen3asr-0.6b`、`qwen3asr-1.7b`
|
||
|
||
### 语音生成
|
||
|
||
从文本生成语音（文本转语音）。
|
||
|
||
#### 端点
|
||
```
|
||
POST /audio/speech
|
||
```
|
||
|
||
#### 请求体
|
||
|
||
| 参数 | 类型 | 必需 | 描述 |
|
||
|------|------|------|------|
|
||
| `model` | string | 是 | 模型标识符（如 "voxcpm1.5"） |
|
||
| `messages` | array | 是 | 消息对象数组 |
|
||
|
||
#### 示例
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/audio/speech \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "voxcpm1.5",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "text", "text": "你好，这是 AHA 在说话。"},
|
||
{"type": "audio", "audio_url": {"url": "https://package-release.coderbox.cn/aiway/test/other/%E5%93%AA%E5%90%92.wav"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
#### 响应
|
||
|
||
以 base64 WAV 格式返回音频数据。
|
||
|
||
#### 支持的模型
|
||
|
||
- `voxcpm`、`voxcpm1.5`
|
||
|
||
### 图像背景移除
|
||
|
||
从图像中移除背景。
|
||
|
||
#### 端点
|
||
```
|
||
POST /images/remove_background
|
||
```
|
||
|
||
#### 请求体
|
||
|
||
| 参数 | 类型 | 必需 | 描述 |
|
||
|------|------|------|------|
|
||
| `model` | string | 是 | 模型标识符（如 "rmbg2.0"） |
|
||
| `messages` | array | 是 | 消息对象数组 |
|
||
|
||
#### 示例
|
||
|
||
**从文件：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/images/remove_background \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "rmbg2.0",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "image", "image_url": {"url": "file:///path/to/document.jpg"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
**从 Base64：**
|
||
|
||
```bash
|
||
curl http://127.0.0.1:10100/images/remove_background \
|
||
-H "Content-Type: application/json" \
|
||
-d '{
|
||
"model": "rmbg2.0",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": [
|
||
{"type": "image", "image_url": {"url": "base64://$(base64 -w 0 photo.png)"}}
|
||
]
|
||
}
|
||
]
|
||
}'
|
||
```
|
||
|
||
#### 响应
|
||
|
||
以base64 PNG 格式返回处理后的图像。
|
||
|
||
#### 支持的模型
|
||
|
||
- `rmbg2.0`
|
||
|
||
## 错误处理
|
||
|
||
### 错误代码
|
||
|
||
| 代码 | 描述 |
|
||
|------|------|
|
||
| 400 | 错误请求 - 无效参数 |
|
||
| 404 | 未找到 - 模型或端点未找到 |
|
||
| 500 | 内部服务器错误 - 模型推理错误 |
|
||
| 503 | 服务不可用 - 模型未加载 |
|
||
|
||
### 错误响应格式
|
||
|
||
```json
|
||
{
|
||
"error": {
|
||
"message": "未找到模型 'unknown-model'",
|
||
"type": "invalid_request_error",
|
||
"code": "model_not_found"
|
||
}
|
||
}
|
||
```
|
||
|
||
## 速率限制
|
||
|
||
目前，AHA 不实现速率限制。服务器可以处理并发请求，仅受系统资源限制。
|
||
|
||
## 文件上传限制
|
||
|
||
- 字符串数据：5 MB
|
||
- 文件上传：100 MB
|
||
|
||
## OpenAI 兼容性
|
||
|
||
AHA 的 文本生成 API 设计与 OpenAI 的 API 格式兼容。多模态 API 源自文本生成 API，仅做了少量改动：
|
||
|
||
### Python 示例
|
||
|
||
```python
|
||
from openai import OpenAI
|
||
|
||
client = OpenAI(
|
||
base_url="http://127.0.0.1:10100",
|
||
api_key="dummy" # 不使用但库需要
|
||
)
|
||
|
||
response = client.chat.completions.create(
|
||
model="qwen3-0.6b",
|
||
messages=[
|
||
{"role": "user", "content": "你好！"}
|
||
]
|
||
)
|
||
|
||
print(response.choices[0].message.content)
|
||
```
|
||
|
||
### JavaScript 示例
|
||
|
||
```javascript
|
||
import OpenAI from 'openai';
|
||
|
||
const client = new OpenAI({
|
||
baseURL: 'http://127.0.0.1:10100',
|
||
apiKey: 'dummy' // 不使用但需要
|
||
});
|
||
|
||
const response = await client.chat.completions.create({
|
||
model: 'qwen3-0.6b',
|
||
messages: [{ role: 'user', content: '你好！' }]
|
||
});
|
||
|
||
console.log(response.choices[0].message.content);
|
||
```
|
||
|
||
## 最佳实践
|
||
|
||
### 1. 对长响应使用流式传输
|
||
|
||
对于长文本生成，使用流式传输增量获取响应：
|
||
|
||
```bash
|
||
curl ... -d '{"stream": true, ...}'
|
||
```
|
||
|
||
### 2. 设置适当的令牌限制
|
||
|
||
防止过长的响应：
|
||
|
||
```json
|
||
{
|
||
"max_tokens": 500
|
||
}
|
||
```
|
||
|
||
### 3. 调整温度
|
||
|
||
控制响应创造性：
|
||
- `0.0-0.3`：确定性、专注
|
||
- `0.4-0.7`：平衡（默认：1.0）
|
||
- `0.8-2.0`：创造性、多样
|
||
|
||
### 4. 使用系统消息
|
||
|
||
使用系统消息设置行为：
|
||
|
||
```json
|
||
{
|
||
"messages": [
|
||
{"role": "system", "content": "你是一个技术写作助手。"},
|
||
{"role": "user", "content": "..."}
|
||
]
|
||
}
|
||
```
|
||
|
||
## 另见
|
||
|
||
- [快速入门](./getting-started.zh-CN.md) - 快速入门指南
|
||
- [CLI 参考](./cli.zh-CN.md) - 命令行使用
|
||
- [安装](./installation.zh-CN.md) - 安装指南
|
||
- [开发](./development.zh-CN.md) - 贡献指南
|