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| import gradio as gr | |
| import os | |
| from utils.text_dataset_parser import load_text_file, load_builtin_datasets | |
| def create_dataset_input(): | |
| """ | |
| Create the dataset input interface with prompt, response, and model fields. | |
| Returns: | |
| tuple: (dataset_inputs, example_dropdown, load_example_btn, create_btn, prompt, response1, model1, response2, model2) | |
| """ | |
| # Get built-in text datasets | |
| text_datasets_dir = os.path.join("dataset") | |
| # Check if directory exists | |
| if os.path.exists(text_datasets_dir): | |
| # Filter out summary files when listing available datasets | |
| text_datasets = [file.name for file in os.scandir(text_datasets_dir) | |
| if file.is_file() and file.name.endswith(".txt") and not file.name.startswith("summary-")] | |
| else: | |
| # Create directory if it doesn't exist | |
| os.makedirs(text_datasets_dir, exist_ok=True) | |
| text_datasets = [] | |
| with gr.Column() as dataset_inputs: | |
| gr.Markdown("## LLM Response Comparison Dataset") | |
| gr.Markdown(""" | |
| Enter a prompt and responses from two different LLMs for comparison, | |
| or load one of the built-in datasets. | |
| """) | |
| # Example dataset selection | |
| with gr.Row(): | |
| example_dropdown = gr.Dropdown( | |
| choices=text_datasets, | |
| value=text_datasets[0] if text_datasets else None, | |
| label="Built-in Datasets", | |
| info="Select a pre-made dataset to load" | |
| ) | |
| load_example_btn = gr.Button("Load Dataset", variant="secondary") | |
| # User input fields | |
| gr.Markdown("### Create Your Own Dataset") | |
| with gr.Row(): | |
| prompt = gr.Textbox(label="Prompt", lines=2, placeholder="Enter a prompt/question...") | |
| with gr.Row(): | |
| response1 = gr.Textbox(label="Response 1", lines=4, placeholder="Enter the first model's response...") | |
| model1 = gr.Textbox(label="Model 1", placeholder="Enter the first model's name...") | |
| with gr.Row(): | |
| response2 = gr.Textbox(label="Response 2", lines=4, placeholder="Enter the second model's response...") | |
| model2 = gr.Textbox(label="Model 2", placeholder="Enter the second model's name...") | |
| create_btn = gr.Button("Create Dataset", variant="primary") | |
| return dataset_inputs, example_dropdown, load_example_btn, create_btn, prompt, response1, model1, response2, model2 | |
| def load_example_dataset(file_name): | |
| """ | |
| Load a built-in dataset from a text file. | |
| Args: | |
| file_name (str): Name of the text file to load. | |
| Returns: | |
| tuple: Values for prompt, response1, model1, response2, and model2. | |
| """ | |
| if not file_name: | |
| return "", "", "", "", "" | |
| file_path = os.path.join("dataset", file_name) | |
| if os.path.exists(file_path): | |
| try: | |
| dataset = load_text_file(file_path) | |
| return ( | |
| dataset.get("prompt", ""), | |
| dataset.get("response1", ""), | |
| dataset.get("model1", ""), | |
| dataset.get("response2", ""), | |
| dataset.get("model2", "") | |
| ) | |
| except Exception as e: | |
| print(f"Error loading dataset: {e}") | |
| return "Error loading dataset", "", "", "", "" | |
| else: | |
| print(f"File not found: {file_path}") | |
| return "File not found", "", "", "", "" # Clear error message as first field | |
| def create_user_dataset(prompt, response1, model1, response2, model2): | |
| """ | |
| Create a user-defined dataset entry. | |
| Args: | |
| prompt (str): The prompt text. | |
| response1 (str): The first model's response. | |
| model1 (str): The first model's name. | |
| response2 (str): The second model's response. | |
| model2 (str): The second model's name. | |
| Returns: | |
| dict: Dataset entry with prompt, response1, model1, response2, and model2. | |
| """ | |
| # Validate inputs | |
| if not prompt.strip(): | |
| raise ValueError("Prompt cannot be empty") | |
| if not response1.strip(): | |
| raise ValueError("Response 1 cannot be empty") | |
| if not response2.strip(): | |
| raise ValueError("Response 2 cannot be empty") | |
| # Use default model names if not provided | |
| model1_name = model1.strip() if model1.strip() else "Model 1" | |
| model2_name = model2.strip() if model2.strip() else "Model 2" | |
| return { | |
| "prompt": prompt.strip(), | |
| "response1": response1.strip(), | |
| "model1": model1_name, | |
| "response2": response2.strip(), | |
| "model2": model2_name | |
| } |