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This pull request adds four new mock tests to improve the robustness of the query_llm_robust function, ensuring it handles various edge cases and errors effectively. The tests include: test_llm_normal_response, which verifies the correct handling of a valid LLM response with accurate translations; test_llm_gibberish_response, which ensures gibberish inputs are identified and appropriately flagged as "Unintelligible"; test_llm_unexpected_language, which tests the system's resilience to unexpected response formats from the LLM; and test_llm_api_error, which simulates API failures and checks if the function provides a safe fallback response. These tests use unittest.mock.patch to simulate LLM behavior, replacing actual API calls with predefined mock responses. By adding these cases to the test_translator.py file, the system is better equipped to manage diverse scenarios, ensuring reliable performance and graceful error handling.