diff --git a/open_notebook/domain/notebook.py b/open_notebook/domain/notebook.py
index c15e8e2..207f5ca 100644
--- a/open_notebook/domain/notebook.py
+++ b/open_notebook/domain/notebook.py
@@ -265,7 +265,9 @@ def text_search(keyword: str, results: int, source: bool = True, note: bool = Tr
         raise DatabaseOperationError("Failed to perform text search")
 
 
-def vector_search(keyword: str, results: int, source: bool = True, note: bool = True):
+def vector_search(
+    keyword: List[float], results: int, source: bool = True, note: bool = True
+):
     if not keyword:
         raise InvalidInputError("Search keyword cannot be empty")
     try:
diff --git a/open_notebook/models/__init__.py b/open_notebook/models/__init__.py
index 5b4cdea..679f262 100644
--- a/open_notebook/models/__init__.py
+++ b/open_notebook/models/__init__.py
@@ -1,7 +1,8 @@
-from typing import Dict, Optional
+from typing import Dict, Optional, Union
 
 from open_notebook.domain.models import DefaultModels, Model
 from open_notebook.models.embedding_models import (
+    EmbeddingModel,
     GeminiEmbeddingModel,
     OllamaEmbeddingModel,
     OpenAIEmbeddingModel,
@@ -10,6 +11,7 @@ from open_notebook.models.embedding_models import (
 from open_notebook.models.llms import (
     AnthropicLanguageModel,
     GeminiLanguageModel,
+    LanguageModel,
     LiteLLMLanguageModel,
     OllamaLanguageModel,
     OpenAILanguageModel,
@@ -17,10 +19,14 @@ from open_notebook.models.llms import (
     VertexAILanguageModel,
     VertexAnthropicLanguageModel,
 )
-from open_notebook.models.speech_to_text_models import OpenAISpeechToTextModel
+from open_notebook.models.speech_to_text_models import (
+    OpenAISpeechToTextModel,
+    SpeechToTextModel,
+)
 from open_notebook.models.text_to_speech_models import (
     ElevenLabsTextToSpeechModel,
     OpenAITextToSpeechModel,
+    TextToSpeechModel,
 )
 
 # Unified model class map with type information
@@ -77,7 +83,9 @@ class ModelManager:
             self.refresh_defaults()
         return self._default_models
 
-    def get_model(self, model_id: str, **kwargs) -> object:
+    def get_model(
+        self, model_id: str, **kwargs
+    ) -> Union[LanguageModel, EmbeddingModel, SpeechToTextModel, TextToSpeechModel]:
         """
         Get a model instance based on model_id. Uses caching to avoid recreating instances.
 
@@ -110,12 +118,14 @@ class ModelManager:
 
         # Special handling for language models that need langchain conversion
         if model.type == "language":
-            model_instance = model_instance.to_langchain()
+            model_instance = model_instance
 
         self._model_cache[cache_key] = model_instance
         return model_instance
 
-    def get_default_model(self, model_type: str, **kwargs) -> object:
+    def get_default_model(
+        self, model_type: str, **kwargs
+    ) -> Union[LanguageModel, EmbeddingModel, SpeechToTextModel, TextToSpeechModel]:
         """
         Get the default model for a specific type.
 
diff --git a/pages/3_🔍_Search.py b/pages/3_🔍_Search.py
index b092af3..1d7dd4d 100644
--- a/pages/3_🔍_Search.py
+++ b/pages/3_🔍_Search.py
@@ -1,7 +1,7 @@
 import streamlit as st
 
 from open_notebook.domain.notebook import text_search, vector_search
-from open_notebook.models import model_manager
+from open_notebook.models import EmbeddingModel, model_manager
 from stream_app.note import note_list_item
 from stream_app.source import source_list_item
 from stream_app.utils import page_commons
@@ -11,7 +11,7 @@ st.set_page_config(
 )
 page_commons()
 
-EMBEDDING_MODEL = model_manager.get_default_model("embedding")
+EMBEDDING_MODEL: EmbeddingModel = model_manager.get_default_model("embedding")
 
 # search_tab, ask_tab = st.tabs(["Search", "Ask"])
 # notebooks = Notebook.get_all()