How to improve the quality and accuracy of DeepSeek-V3.1-Base generated code?

2025-08-20

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Optimization Methodology for Code Generation

The following enhancement strategies are recommended for the specific needs of the technology scenario:

Prompt Engineering
Use structured templates to specify output requirements:
"""Generate Python code that implements [功能描述]. Requirements: 1. Use PEP8 style 2. Include type hints 3. Add docstrings"""
Temperature parameter adjustment
set uptemperature=0.3Reduce randomness withtop_p=0.9Maintaining some diversity
Post-processing validation
1. utilizationpyflakesPerform static syntax checking
2. pass (a bill or inspection etc)pylintVerification Code Specification
3. Adding Unit Tests to Key Functions
Iterative optimization
Adopt RCI (Repair-Code-Iterate) process: first round generation → error analysis → feedback correction → re-generation
domain enhancement
LoRA fine-tuning of the model for code-related tasks, using specialized datasets such as CodeSearchNet

Special Note: Complex functions are recommended to be split into multiple sub-tasks to be generated separately and then combined.