fix(gpt): fix the stack smashing due to long error messsges and do some refactor.

[hjxilinx]

Description

fix(gpt): fix the stack smashing due to long error messsges and do some refactor.

Checklist

Please check the items in the checklist if applicable.

• Is the user manual updated?
• Are the test cases passed and automated?
• Is there no significant decrease in test coverage?

[gemini-code-assist]

Summary of Changes

Hello @hjxilinx, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request primarily focuses on improving the robustness and error handling within the system. It resolves a potential stack smashing issue in the error message parsing logic by switching to dynamic memory allocation, and refines error classification for model loading failures. Additionally, it includes a minor refactoring in the Python-based autoencoder to standardize exception handling.

Highlights

• Memory Safety: Addressed a potential stack smashing vulnerability in the parseErrorMsgFromAnalyticServer function by dynamically allocating memory for error messages instead of using a fixed-size buffer, ensuring proper handling of long error strings.
• Error Handling Improvement: Enhanced error message parsing in executil.c to specifically identify and handle "failed to load model" scenarios, mapping them to the TSDB_CODE_ANA_ALGO_NOT_LOAD error code.
• Code Refactoring: Streamlined error handling in autoencoder.py by replacing a direct FileNotFoundError with a dedicated failed_load_model_except helper function for consistent exception reporting.

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[gemini-code-assist]

Code Review

This pull request fixes a critical stack smashing vulnerability in parseErrorMsgFromAnalyticServer by replacing a fixed-size stack buffer with dynamic memory allocation using tjsonDupStringValue. This is a significant improvement for security and stability. The changes also include refactoring in Python to raise a more specific error when a model fails to load, which is then handled by the C code. My review includes a critical fix to prevent a potential null pointer dereference in the C code if the JSON message is null.