V4.6.6-2 (#673)

projects/app/src/service/core/ai/model.ts

@@ -24,13 +24,24 @@ export function getAudioSpeechModel(model?: string) {
   );
 }
 
+export function getWhisperModel(model?: string) {
+  return global.whisperModel;
+}
+
+export function getReRankModel(model?: string) {
+  return global.reRankModels.find((item) => item.model === model);
+}
+
 export enum ModelTypeEnum {
   chat = 'chat',
   qa = 'qa',
   cq = 'cq',
   extract = 'extract',
   qg = 'qg',
-  vector = 'vector'
+  vector = 'vector',
+  audioSpeech = 'audioSpeech',
+  whisper = 'whisper',
+  rerank = 'rerank'
 }
 export const getModelMap = {
   [ModelTypeEnum.chat]: getChatModel,
@@ -38,5 +49,8 @@ export const getModelMap = {
   [ModelTypeEnum.cq]: getCQModel,
   [ModelTypeEnum.extract]: getExtractModel,
   [ModelTypeEnum.qg]: getQGModel,
-  [ModelTypeEnum.vector]: getVectorModel
+  [ModelTypeEnum.vector]: getVectorModel,
+  [ModelTypeEnum.audioSpeech]: getAudioSpeechModel,
+  [ModelTypeEnum.whisper]: getWhisperModel,
+  [ModelTypeEnum.rerank]: getReRankModel
 };

projects/app/src/service/core/ai/rerank.ts

@@ -20,8 +20,14 @@ export function reRankRecall({ query, inputs }: PostReRankProps) {
         Authorization: `Bearer ${model.requestAuth}`
       }
     }
-  ).then((data) => {
-    console.log('rerank time:', Date.now() - start);
-    return data;
-  });
+  )
+    .then((data) => {
+      console.log('rerank time:', Date.now() - start);
+      return data;
+    })
+    .catch((err) => {
+      console.log(err);
+
+      return [];
+    });
 }

projects/app/src/service/core/ai/vector.ts

@@ -1,73 +0,0 @@
-import { getAIApi } from '@fastgpt/service/core/ai/config';
-
-export type GetVectorProps = {
-  model: string;
-  input: string | string[];
-};
-
-// text to vector
-export async function getVectorsByText({
-  model = 'text-embedding-ada-002',
-  input
-}: GetVectorProps) {
-  try {
-    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'
-          });
-        }
-      }
-    }
-
-    // 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 {
-          tokenLen: 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);
-}