Delete ranking.py

ranking.py

@@ -1,154 +0,0 @@
-import gradio as gr
-import json
-import os
-import zipfile
-
-def load_data(filepath):
-    """Loads data from the JSON file."""
-    with open(filepath, 'r') as f:
-        data = json.load(f)
-    return data
-
-def create_comparison_app(file_paths):
-    """Creates the Gradio app for comparing LLM responses with side-by-side layout for multiple files and browser download."""
-
-    all_data = {}  # Dictionary to store data for each file, keyed by filepath
-    current_file_index = 0
-    current_prompt_index = 0
-    current_filepath = ""
-    results_data = {} # store results data in memory
-
-    def initialize_data(filepath):
-        nonlocal all_data, current_prompt_index, current_filepath, results_data
-        if filepath not in all_data:
-            all_data[filepath] = load_data(filepath)
-            results_data[filepath] = list(all_data[filepath]) # Create a copy to store results, important to not modify original data in all_data directly
-        current_filepath = filepath
-        current_prompt_index = 0
-
-    def get_progress_text():
-        nonlocal current_file_index, file_paths, current_prompt_index
-        files_left = len(file_paths) - (current_file_index + 1)
-        if current_filepath:
-            prompts_left = len(results_data[current_filepath]) - (current_prompt_index + 1) if current_prompt_index < len(results_data[current_filepath]) else 0
-            return f"File {current_file_index + 1}/{len(file_paths)} - {prompts_left + 1} prompts left in this file, {files_left} files remaining."
-        else:
-            return "No file loaded."
-
-    def display_prompt_and_responses(filepath, index):
-        """Displays the prompt and responses for a given index within the current file."""
-        if not filepath or filepath not in results_data: # Use results_data here
-            return "No file loaded.", "", "", get_progress_text(), None
-
-        data = results_data[filepath] # Use results_data
-        if 0 <= index < len(data):
-            item = data[index]
-            prompt_text = item.get("prompt", "No prompt available")
-            finetuned_output_text = item.get("finetuned_output", "No finetuned output")
-            base_output_text = item.get("base_output", "No base output")
-            return prompt_text, finetuned_output_text, base_output_text, get_progress_text(), None # None for file download initially
-        else:
-            return "File finished! Please proceed to the next file.", "", "", get_progress_text(), None # Indicate file completion, None for file download
-
-    def record_choice(choice):
-        """Records the user's choice and moves to the next prompt or file, provides download at the end."""
-        nonlocal current_prompt_index, results_data, current_filepath, current_file_index, file_paths
-
-        if not current_filepath:
-            return "No file loaded.", "", "", get_progress_text(), None
-
-        data = results_data[current_filepath] # Use results_data
-        if 0 <= current_prompt_index < len(data):
-            if choice == "finetuned":
-                data[current_prompt_index]["choice"] = "finetuned"
-            elif choice == "base":
-                data[current_prompt_index]["choice"] = "base_output"
-
-            current_prompt_index += 1
-            if current_prompt_index < len(data):
-                return display_prompt_and_responses(current_filepath, current_prompt_index) + (None,) # None for file download
-            else:
-                # File finished, prepare for download
-                if current_file_index < len(file_paths) - 1:
-                    current_file_index += 1
-                    next_filepath = file_paths[current_file_index]
-                    initialize_data(next_filepath) # Initialize for the next file
-                    return display_prompt_and_responses(current_filepath, current_prompt_index) + (None,) # None for file download, start next
-                else:
-                    # All files finished, prepare zip archive for download
-                    zip_filepath = create_zip_archive(results_data)
-                    return "Comparison finished for all files! Please download the results ('Download results' button).", "", "", "Comparison finished for all files!", gr.update(visible=True, value=zip_filepath, label="Download results") # Final completion, with file download
-        else:
-            # Should not reach here normally, but handle for robustness - in case record_choice is called after file is finished
-            if current_file_index < len(file_paths) - 1:
-                current_file_index += 1
-                next_filepath = file_paths[current_file_index]
-                initialize_data(next_filepath) # Initialize for the next file
-                return display_prompt_and_responses(current_filepath, current_prompt_index) + (None,) # None for file download, start next
-            else:
-                # All files finished, prepare zip archive for download
-                zip_filepath = create_zip_archive(results_data)
-                return "Comparison finished for all files! Please download the results ('Download results' button).", "", "", "Comparison finished for all files!", gr.update(visible=True, value=zip_filepath, label="Download results")
-
-    def create_zip_archive(results_data):
-        """Creates a zip archive of all result files."""
-        zip_filepath = "/tmp/results.zip"
-        with zipfile.ZipFile(zip_filepath, 'w') as zipf:
-            for filepath, data in results_data.items():
-                results_filename = os.path.basename(filepath).replace(".json", "_results.json")
-                results_json_string = json.dumps(data, indent=2)
-                zipf.writestr(results_filename, results_json_string)
-        return zip_filepath
-
-    with gr.Blocks() as iface:
-        progress_markdown = gr.Markdown(get_progress_text()) # Progress indication at the top
-        gr.Markdown("# LLM song lyrics generation ranking")
-        gr.Markdown("There are 5 files (each with 50 prompts) to compare. For each prompt, choose the better lyrics between Model A and Model B. After you complete all files and prompts, you can download the results.")
-        prompt_output = gr.Textbox(label="Lyrics description", lines=3, interactive=False, max_lines=3) # Fixed lines for prompt
-
-        with gr.Row(): # Row for side-by-side outputs
-            with gr.Column(): # Column for Finetuned Output
-                finetuned_output_box = gr.Textbox(label="Model A", lines=10, interactive=False, max_lines=10) # Fixed lines for finetuned
-            with gr.Column(): # Column for Base Output
-                base_output_box = gr.Textbox(label="Model B", lines=10, interactive=False, max_lines=10) # Fixed lines for base
-
-        with gr.Row(): # Row for buttons
-            finetuned_button = gr.Button("Model A is better")
-            base_button = gr.Button("Model B is better")
-
-        file_download_output = gr.DownloadButton(label="Download results", visible=False) # File output component
-
-        def load_initial_file(files):
-            if files:
-                filepath = files[0] # Take the first file path from the list
-                initialize_data(filepath)
-                return display_prompt_and_responses(current_filepath, current_prompt_index) + (None,) # None for initial file download
-            return "No file loaded.", "", "", get_progress_text(), None # None for initial file download
-
-        # Initial display - needs to load the first file
-        iface.load(
-            load_initial_file,
-            inputs=[gr.State(file_paths)], # Pass the list of filepaths as state
-            outputs=[prompt_output, finetuned_output_box, base_output_box, progress_markdown, file_download_output] # Added file_download_output
-        )
-
-        # Button click events
-        finetuned_button.click(
-            fn=record_choice,
-            inputs=[gr.State("finetuned")], # Pass "finetuned" string
-            outputs=[prompt_output, finetuned_output_box, base_output_box, progress_markdown, file_download_output], # Added file_download_output
-            api_name="choose_finetuned"
-        )
-        base_button.click(
-            fn=record_choice,
-            inputs=[gr.State("base")], # Pass "base" string
-            outputs=[prompt_output, finetuned_output_box, base_output_box, progress_markdown, file_download_output], # Added file_download_output
-            api_name="choose_base"
-        )
-
-    return iface
-
-if __name__ == '__main__':
-    json_files = ["./Qwen2.5-0.5B.json", "./SmolLM135.json", "./SmolLM135-instruct.json", "./SmolLM360.json", "./SmolLM360-instruct.json"]
-    app = create_comparison_app(json_files)
-    app.launch()