update LangChainOpenAIHandler for langchain version 0.2 and read openai_api_base

[ryanzll]

User description

1. update LangChainOpenAIHandler to support langchain version 0.2
2. read openai_api_base from settings for llms that compatible with openai

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PR Type

Enhancement, Bug fix

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Description

• Updated LangChainOpenAIHandler to support langchain version 0.2 by changing import paths.
• Modified the initialization to read openai_api_base from settings for LLMs compatible with OpenAI.
• Enhanced the chat method to handle input messages, model, and temperature parameters.
• Removed TryAgain exception from the retry decorator to streamline error handling.

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Changes walkthrough 📝

	Relevant files
Enhancement	langchain_ai_handler.py Update LangChainOpenAIHandler for langchain v0.2 and custom API base pr_agent/algo/ai_handlers/langchain_ai_handler.py Updated imports to reflect changes in langchain version 0.2. Modified initialization to read openai_api_base from settings. Updated chat method to handle messages, model, and temperature parameters. Removed TryAgain exception from retry decorator. +13/-9

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[codiumai-pr-agent-pro]

PR Review 🔍

⏱️ Estimated effort to review [1-5]	2, because the changes are moderate in size and complexity. The modifications involve updates to import paths, handling of API base configuration, and method enhancements, which are straightforward to review for someone familiar with Python and the project's context.
🏅 Score	85
🧪 Relevant tests	No
⚡ Possible issues	Error Handling: The removal of the TryAgain exception from the retry decorator might affect the robustness of the system in handling transient errors effectively.
🔒 Security concerns	No
🔀 Multiple PR themes	No

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PR Code Suggestions ✨

Category	Suggestion	Score
Best practice	Catch only ImportError instead of all exceptions Add a specific exception type to the except block to avoid catching all exceptions, which can mask other issues. pr_agent/algo/ai_handlers/langchain_ai_handler.py [4-5] -except: # we don't enforce langchain as a dependency, so if it's not installed, just move on +except ImportError: # we don't enforce langchain as a dependency, so if it's not installed, just move on pass Apply this suggestion Suggestion importance[1-10]: 8 Why: Specifying ImportError instead of a generic exception is a best practice that prevents masking other unexpected issues. This is a crucial improvement for error handling.	8
Enhancement	Simplify the condition to check if openai_api_base is empty or None Instead of checking if openai_api_base is None or has a length of 0, you can use the or operator to simplify the condition. pr_agent/algo/ai_handlers/langchain_ai_handler.py [36-39] -if openai_api_base is None or len(openai_api_base) == 0: +if not openai_api_base: 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) Apply this suggestion Suggestion importance[1-10]: 7 Why: The suggestion correctly identifies a way to simplify the condition check for openai_api_base. This improves readability and maintainability of the code.	7
Possible issue	Validate that messages contains only HumanMessage or SystemMessage objects before invoking _chat Add a check to ensure messages is a list of HumanMessage or SystemMessage objects before invoking _chat. pr_agent/algo/ai_handlers/langchain_ai_handler.py [49] -return self._chat.invoke(input = messages, model=model, temperature=temperature, deployment_name=self.deployment_id) +if all(isinstance(msg, (HumanMessage, SystemMessage)) for msg in messages): + return self._chat.invoke(input = messages, model=model, temperature=temperature, deployment_name=self.deployment_id) +else: + raise ValueError("All messages must be instances of HumanMessage or SystemMessage") Apply this suggestion Suggestion importance[1-10]: 6 Why: Adding type validation for messages enhances the robustness of the method. However, the suggestion does not address if such validation is already handled internally by _chat.invoke.	6

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