feat: server multi models support (#799)

api/core/index/index.py

@@ -1,10 +1,9 @@
 from flask import current_app
-from langchain.embeddings import OpenAIEmbeddings
 
 from core.embedding.cached_embedding import CacheEmbedding
 from core.index.keyword_table_index.keyword_table_index import KeywordTableIndex, KeywordTableConfig
 from core.index.vector_index.vector_index import VectorIndex
-from core.llm.llm_builder import LLMBuilder
+from core.model_providers.model_factory import ModelFactory
 from models.dataset import Dataset
 
 
@@ -15,16 +14,11 @@ class IndexBuilder:
             if not ignore_high_quality_check and dataset.indexing_technique != 'high_quality':
                 return None
 
-            model_credentials = LLMBuilder.get_model_credentials(
-                tenant_id=dataset.tenant_id,
-                model_provider=LLMBuilder.get_default_provider(dataset.tenant_id, 'text-embedding-ada-002'),
-                model_name='text-embedding-ada-002'
+            embedding_model = ModelFactory.get_embedding_model(
+                tenant_id=dataset.tenant_id
             )
 
-            embeddings = CacheEmbedding(OpenAIEmbeddings(
-                max_retries=1,
-                **model_credentials
-            ))
+            embeddings = CacheEmbedding(embedding_model)
 
             return VectorIndex(
                 dataset=dataset,