# Description: Gradio UI for Creating and Testing new Prompts
#
# Imports
import logging

import gradio as gr

from App_Function_Libraries.Chat.Chat_Functions import chat
from App_Function_Libraries.DB.DB_Manager import add_or_update_prompt
from App_Function_Libraries.Prompt_Engineering.Prompt_Engineering import generate_prompt, test_generated_prompt
from App_Function_Libraries.Utils.Utils import format_api_name, global_api_endpoints, default_api_endpoint


#
# Local Imports

#
########################################################################################################################
#
# Functions

# Gradio tab for prompt suggestion and testing
def create_prompt_suggestion_tab():
    try:
        default_value = None
        if default_api_endpoint:
            if default_api_endpoint in global_api_endpoints:
                default_value = format_api_name(default_api_endpoint)
            else:
                logging.warning(f"Default API endpoint '{default_api_endpoint}' not found in global_api_endpoints")
    except Exception as e:
        logging.error(f"Error setting default API endpoint: {str(e)}")
        default_value = None
    with gr.TabItem("Prompt Suggestion/Creation", visible=True):
        gr.Markdown("# Generate and Test AI Prompts with the Metaprompt Approach")

        with gr.Row():
            with gr.Column():
                # Task and variable inputs
                task_input = gr.Textbox(label="Task Description",
                                        placeholder="E.g., Draft an email responding to a customer complaint")
                variables_input = gr.Textbox(label="Variables (comma-separated)",
                                             placeholder="E.g., CUSTOMER_COMPLAINT, COMPANY_NAME")

                # API-related inputs
                # Refactored API selection dropdown
                api_name_input = gr.Dropdown(
                    choices=["None"] + [format_api_name(api) for api in global_api_endpoints],
                    value=default_value,
                    label="API for Analysis (Optional)"
                )

                api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key (if required)",
                                           type="password")

                # Temperature slider for controlling randomness of generation
                temperature_input = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.7, label="Temperature")

                # Button to generate the prompt
                generate_prompt_button = gr.Button("Generate Prompt")

            with gr.Column():
                # Output for the generated prompt
                generated_prompt_output = gr.Textbox(label="Generated Prompt", interactive=False)
                # FIXME - figure this out
                # copy_button = gr.HTML("""
                # <button onclick="copyToClipboard()">Copy</button>
                # <script>
                #     function copyToClipboard() {
                #         const textBox = document.querySelector('textarea'); // Select the textarea
                #         textBox.select(); // Select the text
                #         document.execCommand('copy'); // Copy it to clipboard
                #         alert('Copied to clipboard!');
                #     }
                # </script>
                # """)
        # Section to test the generated prompt
        with gr.Row():
            with gr.Column():
                # Input to test the prompt with variable values
                variable_values_input = gr.Textbox(label="Variable Values (comma-separated)",
                                                   placeholder="Enter variable values in order, comma-separated")
                test_prompt_button = gr.Button("Test Generated Prompt")
            with gr.Column():
                # Output for the test result
                test_output = gr.Textbox(label="Test Output", interactive=False)

        # Section to save the generated prompt to the database
        with gr.Row():
            with gr.Column():
                prompt_title_input = gr.Textbox(label="Prompt Title", placeholder="Enter a title for this prompt")
                prompt_author_input = gr.Textbox(label="Author",
                                                 placeholder="Enter the author's name")  # New author field
                prompt_description_input = gr.Textbox(label="Prompt Description", placeholder="Enter a description", lines=3)
                save_prompt_button = gr.Button("Save Prompt to Database")
                save_prompt_output = gr.Textbox(label="Save Prompt Output", interactive=False)

        # Callback function to generate prompt
        def on_generate_prompt(api_name, api_key, task, variables, temperature):
            # Generate the prompt using the metaprompt approach and API
            generated_prompt = generate_prompt(api_name, api_key, task, variables, temperature)
            return generated_prompt

        # Callback function to test the generated prompt
        def on_test_prompt(api_name, api_key, generated_prompt, variable_values, temperature):
            # Test the prompt by filling in variable values
            test_result = test_generated_prompt(api_name, api_key, generated_prompt, variable_values, temperature)
            return test_result

        # Callback function to save the generated prompt to the database
        def on_save_prompt(title, author, description, generated_prompt):
            if not title or not generated_prompt:
                return "Error: Title and generated prompt are required."

            # Add the generated prompt to the database
            result = add_or_update_prompt(title, author, description, system_prompt="", user_prompt=generated_prompt, keywords=None)
            return result

        # Connect the button to the function that generates the prompt
        generate_prompt_button.click(
            fn=on_generate_prompt,
            inputs=[api_name_input, api_key_input, task_input, variables_input, temperature_input],
            outputs=[generated_prompt_output]
        )

        # Connect the button to the function that tests the generated prompt
        test_prompt_button.click(
            fn=on_test_prompt,
            inputs=[api_name_input, api_key_input, generated_prompt_output, variable_values_input, temperature_input],
            outputs=[test_output]
        )

        # Connect the save button to the function that saves the prompt to the database
        save_prompt_button.click(
            fn=on_save_prompt,
            inputs=[prompt_title_input, prompt_author_input, prompt_description_input, generated_prompt_output],
            outputs=[save_prompt_output]
        )

# Example chat function based on your API structure
def chat_api_call(api_endpoint, api_key, input_data, prompt, temp, system_message=None):
    # Here you will call your chat function as defined previously
    response = chat(message=input_data, history=[], media_content={}, selected_parts=[],
                    api_endpoint=api_endpoint, api_key=api_key, prompt=prompt, temperature=temp,
                    system_message=system_message)
    return response
#
# End of Functions
########################################################################################################################