Code Coherence Review

#### Description
This code was generated using an LLM (Large Language Model). While the generated code appears functional, it is essential to review its **coherence** to ensure:
- Consistency in naming conventions, structure, and style.
- Logical flow and alignment with the project's architecture.
- Proper integration with existing modules and dependencies.

#### Areas to Review
1. **Naming Conventions**: Are variable, function, and class names consistent and meaningful?
2. **Code Structure**: Does the code follow the project's established patterns and structure?
3. **Logic Flow**: Are there any redundant or illogical steps in the implementation?
4. **Integration**: Does the code integrate seamlessly with the rest of the project?
5. **Comments and Documentation**: Are the comments and docstrings clear, concise, and helpful?

#### Files to Review
- [generator/main.py](generator/main.py)
- [generator/core/generator.py](generator/core/generator.py)
- [generator/clients/gemini_client.py](generator/clients/gemini_client.py)
- [generator/prompts/system_prompt.py](generator/prompts/system_prompt.py)

#### Additional Notes
- The code was generated based on the prompt provided in [`system_prompt.py`](generator/prompts/system_prompt.py).
- Pay special attention to any potential inconsistencies or areas where the LLM might have made assumptions that don't align with the project's goals.