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LittleWhiteBox/modules/story-summary/vector/llm/siliconflow.js

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// ═══════════════════════════════════════════════════════════════════════════
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// siliconflow.js - Embedding + 多 Key 轮询
//
// 在 API Key 输入框中用逗号、分号、竖线或换行分隔多个 Key例如
// sk-aaa,sk-bbb,sk-ccc
// 每次调用自动轮询到下一个 Key并发请求会均匀分布到所有 Key 上。
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// ═══════════════════════════════════════════════════════════════════════════
const BASE_URL = 'https://api.siliconflow.cn';
const EMBEDDING_MODEL = 'BAAI/bge-m3';
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// ★ 多 Key 轮询状态
let _keyIndex = 0;
/**
* localStorage 解析所有 Key支持逗号分号竖线换行分隔
*/
function parseKeys() {
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try {
const raw = localStorage.getItem('summary_panel_config');
if (raw) {
const parsed = JSON.parse(raw);
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const keyStr = parsed.vector?.online?.key || '';
return keyStr
.split(/[,;|\n]+/)
.map(k => k.trim())
.filter(k => k.length > 0);
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}
} catch { }
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return [];
}
/**
* 获取下一个可用的 API Key轮询
* 每次调用返回不同的 Key自动循环
*/
export function getApiKey() {
const keys = parseKeys();
if (!keys.length) return null;
if (keys.length === 1) return keys[0];
const idx = _keyIndex % keys.length;
const key = keys[idx];
_keyIndex = (_keyIndex + 1) % keys.length;
const masked = key.length > 10 ? key.slice(0, 6) + '***' + key.slice(-4) : '***';
console.log(`[SiliconFlow] 使用 Key ${idx + 1}/${keys.length}: ${masked}`);
return key;
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}
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/**
* 获取当前配置的 Key 数量供外部模块动态调整并发用
*/
export function getKeyCount() {
return Math.max(1, parseKeys().length);
}
// ═══════════════════════════════════════════════════════════════════════════
// Embedding
// ═══════════════════════════════════════════════════════════════════════════
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export async function embed(texts, options = {}) {
if (!texts?.length) return [];
const key = getApiKey();
if (!key) throw new Error('未配置硅基 API Key');
const { timeout = 30000, signal } = options;
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), timeout);
try {
const response = await fetch(`${BASE_URL}/v1/embeddings`, {
method: 'POST',
headers: {
'Authorization': `Bearer ${key}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: EMBEDDING_MODEL,
input: texts,
}),
signal: signal || controller.signal,
});
clearTimeout(timeoutId);
if (!response.ok) {
const errorText = await response.text().catch(() => '');
throw new Error(`Embedding ${response.status}: ${errorText.slice(0, 200)}`);
}
const data = await response.json();
return (data.data || [])
.sort((a, b) => a.index - b.index)
.map(item => Array.isArray(item.embedding) ? item.embedding : Array.from(item.embedding));
} finally {
clearTimeout(timeoutId);
}
}
export { EMBEDDING_MODEL as MODELS };