diff --git a/llm_demo/orchestrator/langchain_tools/langchain_tools_orchestrator.py b/llm_demo/orchestrator/langchain_tools/langchain_tools_orchestrator.py
index f1b601ad..f1ee7679 100644
--- a/llm_demo/orchestrator/langchain_tools/langchain_tools_orchestrator.py
+++ b/llm_demo/orchestrator/langchain_tools/langchain_tools_orchestrator.py
@@ -28,7 +28,7 @@
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.tools import StructuredTool
-from langchain_google_vertexai import VertexAI
+from langchain_google_vertexai import ChatVertexAI
 from pytz import timezone
 
 from ..orchestrator import BaseOrchestrator, classproperty
@@ -69,7 +69,8 @@ def initialize_agent(
         prompt: ChatPromptTemplate,
         model: str,
     ) -> "UserAgent":
-        llm = VertexAI(max_output_tokens=512, model_name=model, temperature=0.0)
+        # TODO: Use .bind_tools(tools) to bind the tools with the LLM.
+        llm = ChatVertexAI(max_output_tokens=512, model_name=model, temperature=0.0)
         memory = ConversationBufferMemory(
             chat_memory=ChatMessageHistory(messages=history),
             memory_key="chat_history",
diff --git a/llm_demo/orchestrator/langgraph/langgraph_orchestrator.py b/llm_demo/orchestrator/langgraph/langgraph_orchestrator.py
index 6a2a71a7..4b2d7a19 100644
--- a/llm_demo/orchestrator/langgraph/langgraph_orchestrator.py
+++ b/llm_demo/orchestrator/langgraph/langgraph_orchestrator.py
@@ -160,7 +160,9 @@ def user_session_reset(self, session: dict[str, Any], uuid: str):
         # Reset graph checkpointer
         checkpoint = empty_checkpoint()
         config = self.get_config(uuid)
-        self._checkpointer.put(config=config, checkpoint=checkpoint, metadata={})
+        self._checkpointer.put(
+            config=config, checkpoint=checkpoint, metadata={}, new_versions={}
+        )
 
         # Update state with message history
         self._langgraph_app.update_state(config, {"messages": history})
@@ -242,7 +244,7 @@ def get_base_history(self, session: dict[str, Any]):
         return BASE_HISTORY
 
     def get_config(self, uuid: str):
-        return {"configurable": {"thread_id": uuid}}
+        return {"configurable": {"thread_id": uuid, "checkpoint_ns": ""}}
 
     async def user_session_signout(self, uuid: str):
         checkpoint = empty_checkpoint()
diff --git a/llm_demo/orchestrator/langgraph/react_graph.py b/llm_demo/orchestrator/langgraph/react_graph.py
index cd3dc44f..b05134f1 100644
--- a/llm_demo/orchestrator/langgraph/react_graph.py
+++ b/llm_demo/orchestrator/langgraph/react_graph.py
@@ -26,7 +26,7 @@
 )
 from langchain_core.prompts.chat import ChatPromptTemplate
 from langchain_core.runnables import RunnableConfig, RunnableLambda
-from langchain_google_vertexai import VertexAI
+from langchain_google_vertexai import ChatVertexAI
 from langgraph.checkpoint.memory import MemorySaver
 from langgraph.graph import END, StateGraph
 from langgraph.graph.message import add_messages
@@ -85,7 +85,8 @@ async def create_graph(
     tool_node = ToolNode(tools)
 
     # model node
-    model = VertexAI(max_output_tokens=512, model_name=model_name, temperature=0.0)
+    # TODO: Use .bind_tools(tools) to bind the tools with the LLM.
+    model = ChatVertexAI(max_output_tokens=512, model_name=model_name, temperature=0.0)
 
     # Add the prompt to the model to create a model runnable
     model_runnable = prompt | model
@@ -97,27 +98,36 @@ async def acall_model(state: UserState, config: RunnableConfig):
         """
         messages = state["messages"]
         res = await model_runnable.ainvoke({"messages": messages}, config)
-        response = res.replace("```json", "").replace("```", "")
-        try:
-            json_response = json.loads(response)
-            action = json_response.get("action")
-            action_input = json_response.get("action_input")
-            if action == "Final Answer":
-                new_message = AIMessage(content=action_input)
-            else:
-                new_message = AIMessage(
-                    content="suggesting a tool call",
-                    tool_calls=[
-                        ToolCall(id=str(uuid.uuid4()), name=action, args=action_input)
-                    ],
+
+        # TODO: Remove the temporary fix of parsing LLM response and invoking
+        # tools until we use bind_tools API and have automatic response parsing
+        # and tool calling. (see
+        # https://langchain-ai.github.io/langgraph/#example)
+        if "```json" in res.content:
+            try:
+                response = str(res.content).replace("```json", "").replace("```", "")
+                json_response = json.loads(response)
+                action = json_response.get("action")
+                action_input = json_response.get("action_input")
+                if action == "Final Answer":
+                    res = AIMessage(content=action_input)
+                else:
+                    res = AIMessage(
+                        content="suggesting a tool call",
+                        tool_calls=[
+                            ToolCall(
+                                id=str(uuid.uuid4()), name=action, args=action_input
+                            )
+                        ],
+                    )
+            except Exception as e:
+                json_response = response
+                res = AIMessage(
+                    content="Sorry, failed to generate the right format for response"
                 )
-        except Exception as e:
-            json_response = response
-            new_message = AIMessage(
-                content="Sorry, failed to generate the right format for response"
-            )
+
         # if model exceed the number of steps and has not yet return a final answer
-        if state["is_last_step"] and hasattr(new_message, "tool_calls"):
+        if state["is_last_step"] and hasattr(res, "tool_calls"):
             return {
                 "messages": [
                     AIMessage(
@@ -125,7 +135,7 @@ async def acall_model(state: UserState, config: RunnableConfig):
                     )
                 ]
             }
-        return {"messages": [new_message]}
+        return {"messages": [res]}
 
     def agent_should_continue(
         state: UserState,
diff --git a/llm_demo/requirements.txt b/llm_demo/requirements.txt
index f0c63c2b..72550b2b 100644
--- a/llm_demo/requirements.txt
+++ b/llm_demo/requirements.txt
@@ -5,7 +5,7 @@ itsdangerous==2.2.0
 jinja2==3.1.4
 langchain-community==0.3.2
 langchain==0.3.7
-langchain-google-vertexai==2.0.4
+langchain-google-vertexai==2.0.7
 markdown==3.7
 types-Markdown==3.7.0.20240822
 uvicorn[standard]==0.31.0
@@ -16,3 +16,4 @@ langgraph==0.2.48
 httpx==0.27.2
 pandas-stubs==2.2.2.240807
 pandas==2.2.3
+pydantic==2.9.0
\ No newline at end of file
diff --git a/retrieval_service/requirements.txt b/retrieval_service/requirements.txt
index 33a7e640..07b163d0 100644
--- a/retrieval_service/requirements.txt
+++ b/retrieval_service/requirements.txt
@@ -6,7 +6,7 @@ google-cloud-aiplatform==1.72.0
 google-cloud-spanner==3.49.1
 langchain-core==0.3.18
 pgvector==0.3.5
-pydantic==2.9.2
+pydantic==2.9.0
 uvicorn[standard]==0.31.0
 cloud-sql-python-connector==1.12.1
 google-cloud-alloydb-connector[asyncpg]==1.4.0