diff --git a/dbgpt/core/interface/knowledge.py b/dbgpt/core/interface/knowledge.py
index 369108883..e155e3169 100644
--- a/dbgpt/core/interface/knowledge.py
+++ b/dbgpt/core/interface/knowledge.py
@@ -111,13 +111,23 @@ class Chunk(Document):
     @classmethod
     def chunk2langchain(cls, chunk):
         """Transform Chunk to Langchain format."""
-        from langchain.schema import Document as LCDocument
-
+        try:
+            from langchain.schema import Document as LCDocument  # mypy: ignore
+        except ImportError:
+            raise ValueError(
+                "Could not import python package: langchain "
+                "Please install langchain by command `pip install langchain"
+            )
         return LCDocument(page_content=chunk.content, metadata=chunk.metadata)
 
     @classmethod
     def chunk2llamaindex(cls, chunk):
         """Transform Chunk to llama-index format."""
-        from llama_index.schema import TextNode
-
+        try:
+            from llama_index.schema import TextNode
+        except ImportError:
+            raise ValueError(
+                "Could not import python package: llama_index "
+                "Please install llama_index by command `pip install llama_index"
+            )
         return TextNode(text=chunk.content, metadata=chunk.metadata)
diff --git a/dbgpt/rag/embedding/_wrapped.py b/dbgpt/rag/embedding/_wrapped.py
index 4887d5838..de7e8cae9 100644
--- a/dbgpt/rag/embedding/_wrapped.py
+++ b/dbgpt/rag/embedding/_wrapped.py
@@ -5,7 +5,9 @@ from typing import TYPE_CHECKING, List
 from dbgpt.core import Embeddings
 
 if TYPE_CHECKING:
-    from langchain.embeddings.base import Embeddings as LangChainEmbeddings
+    from langchain.embeddings.base import (
+        Embeddings as LangChainEmbeddings,  # mypy: ignore
+    )
 
 
 class WrappedEmbeddings(Embeddings):
diff --git a/dbgpt/rag/knowledge/url.py b/dbgpt/rag/knowledge/url.py
index 4a89de290..87afca757 100644
--- a/dbgpt/rag/knowledge/url.py
+++ b/dbgpt/rag/knowledge/url.py
@@ -37,7 +37,7 @@ class URLKnowledge(Knowledge):
         if self._loader:
             documents = self._loader.load()
         else:
-            from langchain.document_loaders import WebBaseLoader
+            from langchain.document_loaders import WebBaseLoader  # mypy: ignore
 
             if self._path is not None:
                 web_reader = WebBaseLoader(web_path=self._path)
diff --git a/dbgpt/storage/vector_store/pgvector_store.py b/dbgpt/storage/vector_store/pgvector_store.py
index 6f48aaf36..40f4f27e3 100644
--- a/dbgpt/storage/vector_store/pgvector_store.py
+++ b/dbgpt/storage/vector_store/pgvector_store.py
@@ -56,8 +56,12 @@ class PGVectorStore(VectorStoreBase):
 
     def __init__(self, vector_store_config: PGVectorConfig) -> None:
         """Create a PGVectorStore instance."""
-        from langchain.vectorstores import PGVector
-
+        try:
+            from langchain.vectorstores import PGVector  # mypy: ignore
+        except ImportError:
+            raise ImportError(
+                "Please install the `langchain` package to use the PGVector."
+            )
         self.connection_string = vector_store_config.connection_string
         self.embeddings = vector_store_config.embedding_fn
         self.collection_name = vector_store_config.name
diff --git a/setup.py b/setup.py
index 6131108df..b746384d3 100644
--- a/setup.py
+++ b/setup.py
@@ -418,6 +418,7 @@ def core_requires():
         "typeguard",
         # Snowflake no additional dependencies.
         "snowflake-id",
+        "typing_inspect",
     ]
     # For DB-GPT python client SDK
     setup_spec.extras["client"] = setup_spec.extras["core"] + [