fix: ollama embedding knowledge query score always 100% (#7001)

* fix: ollama embedding knowledge query score always 100%

* fix: force ollama to use api without v1

src/main/embeddings/Embeddings.ts

@@ -5,8 +5,15 @@ import EmbeddingsFactory from './EmbeddingsFactory'
 
 export default class Embeddings {
   private sdk: BaseEmbeddings
-  constructor({ model, apiKey, apiVersion, baseURL, dimensions }: KnowledgeBaseParams) {
-    this.sdk = EmbeddingsFactory.create({ model, apiKey, apiVersion, baseURL, dimensions } as KnowledgeBaseParams)
+  constructor({ model, provider, apiKey, apiVersion, baseURL, dimensions }: KnowledgeBaseParams) {
+    this.sdk = EmbeddingsFactory.create({
+      model,
+      provider,
+      apiKey,
+      apiVersion,
+      baseURL,
+      dimensions
+    } as KnowledgeBaseParams)
   }
   public async init(): Promise<void> {
     return this.sdk.init()

src/main/embeddings/EmbeddingsFactory.ts

@@ -1,4 +1,5 @@
 import type { BaseEmbeddings } from '@cherrystudio/embedjs-interfaces'
+import { OllamaEmbeddings } from '@cherrystudio/embedjs-ollama'
 import { OpenAiEmbeddings } from '@cherrystudio/embedjs-openai'
 import { AzureOpenAiEmbeddings } from '@cherrystudio/embedjs-openai/src/azure-openai-embeddings'
 import { getInstanceName } from '@main/utils'
@@ -7,9 +8,9 @@ import { KnowledgeBaseParams } from '@types'
 import VoyageEmbeddings from './VoyageEmbeddings'
 
 export default class EmbeddingsFactory {
-  static create({ model, apiKey, apiVersion, baseURL, dimensions }: KnowledgeBaseParams): BaseEmbeddings {
+  static create({ model, provider, apiKey, apiVersion, baseURL, dimensions }: KnowledgeBaseParams): BaseEmbeddings {
     const batchSize = 10
-    if (model.includes('voyage')) {
+    if (provider === 'voyageai') {
       return new VoyageEmbeddings({
         modelName: model,
         apiKey,
@@ -17,6 +18,26 @@ export default class EmbeddingsFactory {
         batchSize: 8
       })
     }
+    if (provider === 'ollama') {
+      if (baseURL.includes('v1/')) {
+        return new OllamaEmbeddings({
+          model: model,
+          baseUrl: baseURL.replace('v1/', ''),
+          requestOptions: {
+            // @ts-ignore expected
+            'encoding-format': 'float'
+          }
+        })
+      }
+      return new OllamaEmbeddings({
+        model: model,
+        baseUrl: baseURL,
+        requestOptions: {
+          // @ts-ignore expected
+          'encoding-format': 'float'
+        }
+      })
+    }
     if (apiVersion !== undefined) {
       return new AzureOpenAiEmbeddings({
         azureOpenAIApiKey: apiKey,

src/main/services/KnowledgeService.ts

@@ -110,13 +110,21 @@ class KnowledgeService {
   private getRagApplication = async ({
     id,
     model,
+    provider,
     apiKey,
     apiVersion,
     baseURL,
     dimensions
   }: KnowledgeBaseParams): Promise<RAGApplication> => {
     let ragApplication: RAGApplication
-    const embeddings = new Embeddings({ model, apiKey, apiVersion, baseURL, dimensions } as KnowledgeBaseParams)
+    const embeddings = new Embeddings({
+      model,
+      provider,
+      apiKey,
+      apiVersion,
+      baseURL,
+      dimensions
+    } as KnowledgeBaseParams)
     try {
       ragApplication = await new RAGApplicationBuilder()
         .setModel('NO_MODEL')

src/renderer/src/services/KnowledgeService.ts

@@ -39,6 +39,7 @@ export const getKnowledgeBaseParams = (base: KnowledgeBase): KnowledgeBaseParams
   return {
     id: base.id,
     model: base.model.id,
+    provider: base.model.provider,
     dimensions: ONLY_SUPPORTED_DIMENSION_PROVIDERS.includes(base.model.provider) ? base.dimensions : undefined,
     apiKey: aiProvider.getApiKey() || 'secret',
     apiVersion: provider.apiVersion,

src/renderer/src/types/index.ts

@@ -423,6 +423,7 @@ export interface KnowledgeBase {
 export type KnowledgeBaseParams = {
   id: string
   model: string
+  provider: string
   dimensions?: number
   apiKey: string
   apiVersion?: string