207 lines
5.3 KiB
Markdown
207 lines
5.3 KiB
Markdown
# 自定义接口示例
|
||
|
||
## 谷歌翻译接口
|
||
|
||
> 此接口不支持聚合
|
||
|
||
URL
|
||
|
||
```
|
||
https://translate.googleapis.com/translate_a/single?client=gtx&dj=1&dt=t&ie=UTF-8&q={{text}}&sl=en&tl=zh-CN
|
||
```
|
||
|
||
Request Hook
|
||
|
||
```js
|
||
async (args) => {
|
||
const url = args.url.replace("{{text}}", args.texts[0]);
|
||
const method = "GET";
|
||
return { url, method };
|
||
};
|
||
```
|
||
|
||
Response Hook
|
||
|
||
```js
|
||
async ({ res }) => {
|
||
return { translations: [[res?.sentences?.[0]?.trans || "", res?.src]] };
|
||
};
|
||
```
|
||
|
||
|
||
## Ollama
|
||
|
||
> 此示例为支持聚合的模型类(要支持上下文,需进一步改动)
|
||
|
||
* 注意 ollama 启动参数需要添加环境变量 `OLLAMA_ORIGINS=*`
|
||
* 检查环境变量生效命令:`systemctl show ollama | grep OLLAMA_ORIGINS`
|
||
|
||
URL
|
||
|
||
```
|
||
http://localhost:11434/v1/chat/completions
|
||
```
|
||
|
||
Request Hook
|
||
|
||
```js
|
||
async (args) => {
|
||
const url = args.url;
|
||
const method = "POST";
|
||
const headers = { "Content-type": "application/json" };
|
||
const body = {
|
||
model: "gemma3",
|
||
messages: [
|
||
{
|
||
role: "system",
|
||
content:
|
||
'Act as a translation API. Output a single raw JSON object only. No extra text or fences.\n\nInput:\n{"targetLanguage":"<lang>","title":"<context>","description":"<context>","segments":[{"id":1,"text":"..."}],"glossary":{"sourceTerm":"targetTerm"},"tone":"<formal|casual>"}\n\nOutput:\n{"translations":[{"id":1,"text":"...","sourceLanguage":"<detected>"}]}\n\nRules:\n1. Use title/description for context only; do not output them.\n2. Keep id, order, and count of segments.\n3. Preserve whitespace, HTML entities, and all HTML-like tags (e.g., <i1>, <a1>). Translate inner text only.\n4. Highest priority: Follow \'glossary\'. Use value for translation; if value is "", keep the key.\n5. Do not translate: content in <code>, <pre>, text enclosed in backticks, or placeholders like {1}, {{1}}, [1], [[1]].\n6. Apply the specified tone to the translation.\n7. Detect sourceLanguage for each segment.\n8. Return empty or unchanged inputs as is.\n\nExample:\nInput: {"targetLanguage":"zh-CN","segments":[{"id":1,"text":"A <b>React</b> component."}],"glossary":{"component":"组件","React":""}}\nOutput: {"translations":[{"id":1,"text":"一个<b>React</b>组件","sourceLanguage":"en"}]}\n\nFail-safe: On any error, return {"translations":[]}.',
|
||
},
|
||
{
|
||
role: "user",
|
||
content: JSON.stringify({
|
||
targetLanguage: args.to,
|
||
segments: args.texts.map((text, id) => ({ id, text })),
|
||
glossary: {},
|
||
}),
|
||
},
|
||
],
|
||
temperature: 0,
|
||
max_tokens: 20480,
|
||
think: false,
|
||
stream: false,
|
||
};
|
||
|
||
return { url, body, headers, method };
|
||
};
|
||
```
|
||
|
||
v2.0.2 Request Hook 可以简化为:
|
||
|
||
```js
|
||
async (args) => {
|
||
const url = args.url;
|
||
const method = "POST";
|
||
const headers = { "Content-type": "application/json" };
|
||
const body = {
|
||
model: "gemma3", // v2.0.2 版后此处可填 args.model
|
||
messages: [
|
||
{
|
||
role: "system",
|
||
content: args.defaultSystemPrompt, // 或者 args.systemPrompt
|
||
},
|
||
{
|
||
role: "user",
|
||
content: JSON.stringify({
|
||
targetLanguage: args.to,
|
||
segments: args.texts.map((text, id) => ({ id, text })),
|
||
glossary: {},
|
||
}),
|
||
},
|
||
],
|
||
temperature: 0,
|
||
max_tokens: 20480,
|
||
think: false,
|
||
stream: false,
|
||
};
|
||
|
||
return { url, body, headers, method };
|
||
};
|
||
```
|
||
|
||
Response Hook
|
||
|
||
```js
|
||
async ({ res }) => {
|
||
const extractJson = (raw) => {
|
||
const jsonRegex = /({.*}|\[.*\])/s;
|
||
const match = raw.match(jsonRegex);
|
||
return match ? match[0] : null;
|
||
};
|
||
|
||
const parseAIRes = (raw) => {
|
||
if (!raw) return [];
|
||
|
||
try {
|
||
const jsonString = extractJson(raw);
|
||
if (!jsonString) return [];
|
||
|
||
const data = JSON.parse(jsonString);
|
||
if (Array.isArray(data.translations)) {
|
||
return data.translations.map((item) => [
|
||
item?.text ?? "",
|
||
item?.sourceLanguage ?? "",
|
||
]);
|
||
}
|
||
} catch (err) {
|
||
console.log("parseAIRes", err);
|
||
}
|
||
|
||
return [];
|
||
};
|
||
|
||
const translations = parseAIRes(res?.choices?.[0]?.message?.content);
|
||
|
||
return { translations };
|
||
};
|
||
```
|
||
|
||
v2.0.2 版后内置`parseAIRes`函数,Response Hook 可以简化为:
|
||
|
||
```js
|
||
async ({ res, parseAIRes, }) => {
|
||
const translations = parseAIRes(res?.choices?.[0]?.message?.content);
|
||
return { translations };
|
||
};
|
||
```
|
||
|
||
|
||
## 硅基流动
|
||
|
||
> 此示例为不支持聚合模型类,支持聚合的模型类参考上面 Ollama 的写法
|
||
|
||
URL
|
||
|
||
```
|
||
https://api.siliconflow.cn/v1/chat/completions
|
||
```
|
||
|
||
Request Hook
|
||
|
||
```js
|
||
async (args) => {
|
||
const url = args.url;
|
||
const method = "POST";
|
||
const headers = {
|
||
"Content-type": "application/json",
|
||
Authorization: `Bearer ${args.key}`,
|
||
};
|
||
const body = {
|
||
model: "tencent/Hunyuan-MT-7B", // v2.0.2 版后此处可填 args.model
|
||
messages: [
|
||
{
|
||
role: "system",
|
||
content:
|
||
"You are a professional, authentic machine translation engine.",
|
||
},
|
||
{
|
||
role: "user",
|
||
content: `Translate the following source text from to ${args.to}. Output translation directly without any additional text.\n\nSource Text: ${args.texts[0]}\n\nTranslated Text:`,
|
||
},
|
||
],
|
||
temperature: 0,
|
||
max_tokens: 20480,
|
||
};
|
||
|
||
return { url, body, headers, method };
|
||
};
|
||
```
|
||
|
||
Response Hook
|
||
|
||
```js
|
||
async ({ res }) => {
|
||
return { translations: [[res?.choices?.[0]?.message?.content || ""]] };
|
||
};
|
||
```
|