1. update LangChainOpenAIHandler to support langchain version 0.2

2. read openai_api_base from settings for llms that compatible with openai

pr_agent/algo/ai_handlers/langchain_ai_handler.py

@@ -1,6 +1,6 @@
 try:
-    from langchain.chat_models import ChatOpenAI, AzureChatOpenAI
-    from langchain.schema import SystemMessage, HumanMessage
+    from langchain_openai import ChatOpenAI, AzureChatOpenAI
+    from langchain_core.messages import SystemMessage, HumanMessage
 except:  # we don't enforce langchain as a dependency, so if it's not installed, just move on
     pass
 
@@ -8,7 +8,7 @@ from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
 from pr_agent.config_loader import get_settings
 from pr_agent.log import get_logger
 
-from openai.error import APIError, RateLimitError, Timeout, TryAgain
+from openai import APIError, RateLimitError, Timeout
 from retry import retry
 import functools
 
@@ -31,20 +31,24 @@ class LangChainOpenAIHandler(BaseAiHandler):
                     openai_api_version=get_settings().openai.api_version,
                 )
             else:
-                self._chat = ChatOpenAI(openai_api_key=get_settings().openai.key)
+                # 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:
+                    self._chat = ChatOpenAI(openai_api_key=get_settings().openai.key)
+                else:
+                    self._chat = 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
 
-    @property
-    def chat(self):
+    def chat(self, messages: list, model: str, temperature: float):
         if self.azure:
             # we must set the deployment_id only here (instead of the __init__ method) to support fallback_deployments
-            return self._chat(deployment_name=self.deployment_id)
+            return self._chat.invoke(input = messages, model=model, temperature=temperature, deployment_name=self.deployment_id)
         else:
-            return self._chat
+            return self._chat.invoke(input = messages, model=model, temperature=temperature)
 
     @property
     def deployment_id(self):
@@ -53,7 +57,7 @@ class LangChainOpenAIHandler(BaseAiHandler):
         """
         return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
 
-    @retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
+    @retry(exceptions=(APIError, Timeout, AttributeError, RateLimitError),
            tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
     async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
         try: