feat: upgrade langchain (#430)

Co-authored-by: jyong <718720800@qq.com>

api/core/index/index.py

@@ -0,0 +1,41 @@
+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 models.dataset import Dataset
+
+
+class IndexBuilder:
+    @classmethod
+    def get_index(cls, dataset: Dataset, indexing_technique: str, ignore_high_quality_check: bool = False):
+        if indexing_technique == "high_quality":
+            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),
+                model_name='text-embedding-ada-002'
+            )
+
+            embeddings = CacheEmbedding(OpenAIEmbeddings(
+                **model_credentials
+            ))
+
+            return VectorIndex(
+                dataset=dataset,
+                config=current_app.config,
+                embeddings=embeddings
+            )
+        elif indexing_technique == "economy":
+            return KeywordTableIndex(
+                dataset=dataset,
+                config=KeywordTableConfig(
+                    max_keywords_per_chunk=10
+                )
+            )
+        else:
+            raise ValueError('Unknown indexing technique')