diff --git a/pr_agent/algo/ai_handlers/langchain_ai_handler.py b/pr_agent/algo/ai_handlers/langchain_ai_handler.py
index 8e29b8bb..2d4fa08b 100644
--- a/pr_agent/algo/ai_handlers/langchain_ai_handler.py
+++ b/pr_agent/algo/ai_handlers/langchain_ai_handler.py
@@ -8,10 +8,10 @@ except:  # we don't enforce langchain as a dependency, so if it's not installed,
     pass
 
 import functools
-from typing import Optional
 
 import openai
 from tenacity import retry, retry_if_exception_type, retry_if_not_exception_type, stop_after_attempt
+from langchain_core.runnables import Runnable
 
 from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
 from pr_agent.config_loader import get_settings
@@ -30,13 +30,6 @@ class LangChainOpenAIHandler(BaseAiHandler):
         super().__init__()
         self.azure = get_settings().get("OPENAI.API_TYPE", "").lower() == "azure"
 
-        # Create a default unused chat object to trigger early validation
-        self._create_chat(self.deployment_id)
-
-    def chat(self, messages: list, model: str, temperature: float):
-        chat = self._create_chat(self.deployment_id)
-        return chat.invoke(input=messages, model=model, temperature=temperature)
-
     @property
     def deployment_id(self):
         """
@@ -81,9 +74,9 @@ class LangChainOpenAIHandler(BaseAiHandler):
             messages = [SystemMessage(content=system), HumanMessage(content=user)]
             llm = await self._create_chat_async(deployment_id=self.deployment_id)
             
-            if not hasattr(llm, 'ainvoke'):
+            if not isinstance(llm, Runnable):
                 error_message = (
-                    f"The Langchain LLM object ({type(llm)}) does not have an 'ainvoke' async method. "
+                    f"The Langchain LLM object ({type(llm)}) does not implement the Runnable interface. "
                     f"Please update your Langchain library to the latest version or "
                     f"check your LLM configuration to support async calls. "
                     f"PR-Agent is designed to utilize Langchain's async capabilities."
@@ -116,27 +109,3 @@ class LangChainOpenAIHandler(BaseAiHandler):
         except Exception as e:
             get_logger().warning(f"Unknown error during LLM inference: {e}")
             raise openai.APIError from e
-
-    def _create_chat(self, deployment_id=None):
-        try:
-            if self.azure:
-                # using a partial function so we can set the deployment_id later to support fallback_deployments
-                # but still need to access the other settings now so we can raise a proper exception if they're missing
-                return AzureChatOpenAI(
-                    openai_api_key=get_settings().openai.key,
-                    openai_api_version=get_settings().openai.api_version,
-                    azure_deployment=deployment_id,
-                    azure_endpoint=get_settings().openai.api_base,
-                )
-            else:
-                # for llms that compatible with openai, should use custom api base
-                openai_api_base = get_settings().get("OPENAI.API_BASE", None)
-                if openai_api_base is None or len(openai_api_base) == 0:
-                    return ChatOpenAI(openai_api_key=get_settings().openai.key)
-                else:
-                    return ChatOpenAI(openai_api_key=get_settings().openai.key, openai_api_base=openai_api_base)
-        except AttributeError as e:
-            if getattr(e, "name"):
-                raise ValueError(f"OpenAI {e.name} is required") from e
-            else:
-                raise e