Usage ===== This section provides detailed examples of using **chat2llms** to compare responses from large language models (LLMs). The examples include basic usage, and command-line interface (CLI). Basic Comparison ---------------- Compare responses from two mock LLM clients (DeepSeek and Grok) for a simple prompt: .. code-block:: python from chat2llms.analyzer import AnswerAnalyzer from chat2llms.model_response import OpenAIResponse, GeminiResponse from chat2llms.base_client import BaseClient # Initialize clients gemini = BaseClient("gemini") deepseek = BaseClient("deepseek") # Create responses question = "What is 2 + 2?" gemini_response = GeminiResponse(gemini) deepseek_response = OpenAIResponse(deepseek) # Analyze differences analyzer = AnswerAnalyzer(gemini_response, deepseek_response, question) print(f"Similarity: {analyzer.compute_similarity():.2f}") print(f"semantic_sim: {analyzer.compute_semantic_similarity():.2f}") print(analyzer.highlight_differences()) **Output**: .. code-block:: text Text Similarity: 0.09 Semantic Similarity: 0.77 Response 1 (gemini-1.5-pro): 2 + 2 = 4 Response 2 (deepseek-reasoner): The sum of 2 and 2 is calculated as follows: **Step 1:** Start with the number 2. **Step 2:** Add 2 to it. **Step 3:** Combining the quantities results in 4. Command-Line Interface ---------------------------- **chat2llms** provides a Command-Line Interface (CLI) for quick comparisons. After installing (Refer to :doc:`installation`) the package, run: .. code-block:: bash chat2llms --model1 openai --model2 gemini --prompt "Solve 2 + 2" **Output**: .. code-block:: text === Prompt === Solve 2 + 2 === OPENAI Response === 2 + 2 = 4 === GEMINI Response === 2 + 2 = 4 === Text Similarity === 0.9473684210526315 === Semantic Similarity === 0.9281893463830239 === Highlight of Differences === Response 1 (gpt-3.5-turbo): 2 + 2 = 4 Response 2 (gemini-1.5-pro): 2 + 2 = 4