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| import gradio as gr | |
| from prompt_refiner import PromptRefiner | |
| from variables import models, explanation_markdown, metaprompt_list, examples | |
| from custom_css import custom_css | |
| class GradioInterface: | |
| def __init__(self, prompt_refiner: PromptRefiner, custom_css): | |
| self.prompt_refiner = prompt_refiner | |
| with gr.Blocks(css=custom_css, theme=gr.themes.Default()) as self.interface: | |
| # CONTAINER 1 | |
| with gr.Column(elem_classes=["container", "title-container"]): | |
| gr.Markdown("# PROMPT++") | |
| gr.Markdown("### Automating Prompt Engineering by Refining your Prompts") | |
| gr.Markdown("Learn how to generate an improved version of your prompts.") | |
| # CONTAINER 2 | |
| with gr.Column(elem_classes=["container", "input-container"]): | |
| prompt_text = gr.Textbox(label="Type your prompt (or leave empty to see metaprompt)",lines=5) | |
| automatic_metaprompt_button = gr.Button("Automatic Choice for Refinement Method ") | |
| #with gr.Row(elem_classes=["container2"]): | |
| MetaPrompt_analysis = gr.Markdown() | |
| # CONTAINER 3 | |
| # with gr.Column(elem_classes=["container"]): | |
| with gr.Column(elem_classes=["container","meta-container"]): | |
| meta_prompt_choice = gr.Radio( | |
| choices=metaprompt_list, | |
| label="Choose Meta Prompt", | |
| value=metaprompt_list[0], | |
| elem_classes=["no-background", "radio-group"] | |
| ) | |
| refine_button = gr.Button("Refine Prompt") | |
| with gr.Accordion("Metaprompt Explanation", open=False, visible=True): | |
| gr.Markdown(explanation_markdown) | |
| gr.Examples( | |
| examples=examples, | |
| inputs=[prompt_text, meta_prompt_choice] | |
| ) | |
| with gr.Column(elem_classes=["container", "analysis-container"]): | |
| gr.Markdown(" ") | |
| prompt_evaluation = gr.Markdown() # Added this component | |
| gr.Markdown("### Refined Prompt") | |
| refined_prompt = gr.Textbox( | |
| label=" ", | |
| interactive=True, | |
| show_label=True, | |
| show_copy_button=True, | |
| ) | |
| #gr.Markdown("### Explanation of Refinements") | |
| explanation_of_refinements = gr.Markdown() | |
| with gr.Column(elem_classes=["container", "model-container"]): | |
| with gr.Row(): | |
| apply_model = gr.Dropdown( | |
| choices=models, | |
| value=models[0] if models else None, | |
| label="Choose the Model", | |
| container=False, | |
| scale=1, | |
| min_width=300 | |
| ) | |
| apply_button = gr.Button("Apply Prompts") | |
| gr.Markdown("### Prompts on Chosen Model") | |
| with gr.Tabs(): | |
| with gr.TabItem("Original Prompt Output"): | |
| original_output = gr.Markdown() | |
| with gr.TabItem("Refined Prompt Output"): | |
| refined_output = gr.Markdown() | |
| with gr.Accordion("Full Response JSON", open=False, visible=True): | |
| full_response_json = gr.JSON() | |
| # Button click handlers | |
| automatic_metaprompt_button.click( | |
| fn=self.automatic_metaprompt, | |
| inputs=[prompt_text], | |
| outputs=[MetaPrompt_analysis, meta_prompt_choice] | |
| ) | |
| refine_button.click( | |
| fn=self.refine_prompt, | |
| inputs=[prompt_text, meta_prompt_choice], | |
| outputs=[ | |
| prompt_evaluation, | |
| refined_prompt, | |
| explanation_of_refinements, | |
| full_response_json | |
| ] | |
| ) | |
| apply_button.click( | |
| fn=self.apply_prompts, | |
| inputs=[prompt_text, refined_prompt, apply_model], | |
| outputs=[original_output, refined_output] | |
| ) | |
| gr.HTML( | |
| "<p style='text-align: center; color:orange;'>⚠ This space is in progress, and we're actively working on it, so you might find some bugs! Please report any issues you have in the Community tab to help us make it better for all.</p>" | |
| ) | |
| def automatic_metaprompt(self, prompt: str) -> tuple: | |
| """Handle automatic metaprompt selection""" | |
| try: | |
| if not prompt.strip(): | |
| return "Please enter a prompt to analyze.", None | |
| metaprompt_analysis, recommended_key = self.prompt_refiner.automatic_metaprompt(prompt) | |
| return metaprompt_analysis, recommended_key | |
| except Exception as e: | |
| error_message = f"Error in automatic metaprompt: {str(e)}" | |
| return error_message, None | |
| def refine_prompt(self, prompt: str, meta_prompt_choice: str) -> tuple: | |
| """Handle manual prompt refinement""" | |
| try: | |
| if not prompt.strip(): | |
| return ( | |
| "No prompt provided.", | |
| "", | |
| "", | |
| {} | |
| ) | |
| result = self.prompt_refiner.refine_prompt(prompt, meta_prompt_choice) | |
| return ( | |
| result[0], # initial_prompt_evaluation | |
| result[1], # refined_prompt | |
| result[2], # explanation_of_refinements | |
| result[3] # full_response | |
| ) | |
| except Exception as e: | |
| error_message = f"Error in refine_prompt: {str(e)}" | |
| return error_message, "", "", {} | |
| def apply_prompts(self, original_prompt: str, refined_prompt: str, model: str) -> tuple: | |
| """Apply both original and refined prompts to the selected model""" | |
| try: | |
| if not original_prompt.strip() or not refined_prompt.strip(): | |
| return "No prompt provided.", "No prompt provided." | |
| original_output = self.prompt_refiner.apply_prompt(original_prompt, model) | |
| refined_output = self.prompt_refiner.apply_prompt(refined_prompt, model) | |
| return original_output, refined_output | |
| except Exception as e: | |
| error_message = f"Error applying prompts: {str(e)}" | |
| return error_message, error_message | |
| def launch(self, share=False): | |
| """Launch the Gradio interface""" | |
| self.interface.launch(share=share) | |
| if __name__ == '__main__': | |
| from variables import api_token, meta_prompts, metaprompt_explanations | |
| # Initialize the prompt refiner | |
| prompt_refiner = PromptRefiner(api_token, meta_prompts, metaprompt_explanations) | |
| # Create and launch the Gradio interface | |
| gradio_interface = GradioInterface(prompt_refiner, custom_css) | |
| gradio_interface.launch(share=True) |