diff --git a/autorag/__init__.py b/autorag/__init__.py
index 3c1f9b7e7..df88f4acf 100644
--- a/autorag/__init__.py
+++ b/autorag/__init__.py
@@ -5,8 +5,10 @@
 
 from rich.logging import RichHandler
 
-from llama_index import OpenAIEmbedding
-from llama_index.llms import OpenAI
+from llama_index.embeddings import OpenAIEmbedding, HuggingFaceEmbedding
+from llama_index.embeddings.openai import OpenAIEmbeddingModelType
+from llama_index.llms import OpenAI, Anthropic, AzureOpenAI, HuggingFaceLLM, LangChainLLM, GradientBaseModelLLM, \
+    GradientModelAdapterLLM, LiteLLM, LlamaCPP, OpenAILike, OpenLLM, PaLM, PredibaseLLM, Replicate, Xinference
 
 root_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
 version_path = os.path.join(root_path, 'VERSION')
@@ -15,11 +17,32 @@
     __version__ = f.read().strip()
 
 embedding_models = {
-    'openai': OpenAIEmbedding(),
+    'openai': OpenAIEmbedding(),  # default model is OpenAIEmbeddingModelType.TEXT_EMBED_ADA_002
+    'openai_babbage': OpenAIEmbedding(model=OpenAIEmbeddingModelType.BABBAGE),
+    'openai_ada': OpenAIEmbedding(model=OpenAIEmbeddingModelType.ADA),
+    'openai_davinci': OpenAIEmbedding(model=OpenAIEmbeddingModelType.DAVINCI),
+    'openai_curie': OpenAIEmbedding(model=OpenAIEmbeddingModelType.CURIE),
+    # you can use your own model in this way.
+    'huggingface_baai_bge_small': HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5"),
+    'huggingface_cointegrated_rubert_tiny2': HuggingFaceEmbedding(model_name="cointegrated/rubert-tiny2"),
 }
 
 generator_models = {
     'openai': OpenAI,
+    'anthropic': Anthropic,
+    'azureopenai': AzureOpenAI,
+    'huggingfacellm': HuggingFaceLLM,
+    'langchainllm': LangChainLLM,
+    'gradientbasemodelllm': GradientBaseModelLLM,
+    'gradientmodeladapterllm': GradientModelAdapterLLM,
+    'litellm': LiteLLM,
+    'llamacpp': LlamaCPP,
+    'openailike': OpenAILike,
+    'openllm': OpenLLM,
+    'palm': PaLM,
+    'predibasellm': PredibaseLLM,
+    'replicate': Replicate,
+    'xinference': Xinference,
 }
 
 rich_format = "[%(filename)s:%(lineno)s] >> %(message)s"