V4.6.6-2 (#673)

packages/service/core/ai/embedding/index.ts

@@ -0,0 +1,73 @@
+import { getAIApi } from '../config';
+
+export type GetVectorProps = {
+  model: string;
+  input: string | string[];
+};
+
+// text to vector
+export async function getVectorsByText({
+  model = 'text-embedding-ada-002',
+  input
+}: GetVectorProps) {
+  if (typeof input === 'string' && !input) {
+    return Promise.reject({
+      code: 500,
+      message: 'input is empty'
+    });
+  } else if (Array.isArray(input)) {
+    for (let i = 0; i < input.length; i++) {
+      if (!input[i]) {
+        return Promise.reject({
+          code: 500,
+          message: 'input array is empty'
+        });
+      }
+    }
+  }
+
+  try {
+    // 获取 chatAPI
+    const ai = getAIApi();
+
+    // 把输入的内容转成向量
+    const result = await ai.embeddings
+      .create({
+        model,
+        input
+      })
+      .then(async (res) => {
+        if (!res.data) {
+          return Promise.reject('Embedding API 404');
+        }
+        if (!res?.data?.[0]?.embedding) {
+          console.log(res?.data);
+          // @ts-ignore
+          return Promise.reject(res.data?.err?.message || 'Embedding API Error');
+        }
+        return {
+          tokens: res.usage.total_tokens || 0,
+          vectors: await Promise.all(res.data.map((item) => unityDimensional(item.embedding)))
+        };
+      });
+
+    return result;
+  } catch (error) {
+    console.log(`Embedding Error`, error);
+
+    return Promise.reject(error);
+  }
+}
+
+function unityDimensional(vector: number[]) {
+  if (vector.length > 1536) {
+    console.log(`当前向量维度为: ${vector.length}, 向量维度不能超过 1536, 已自动截取前 1536 维度`);
+    return vector.slice(0, 1536);
+  }
+  let resultVector = vector;
+  const vectorLen = vector.length;
+
+  const zeroVector = new Array(1536 - vectorLen).fill(0);
+
+  return resultVector.concat(zeroVector);
+}