import gradio as gr
from  backend import BackEnd
import argparse
import configparser




class Demo:
    def __init__(self, config):
        self.config = config
        self.backend = BackEnd(self.config)
        self.lang = self.config['General']['language'].lower()[:2]        


    def process_query(self,history, query):
        res,context = self.backend.process_query(query)
        documents = '\n\n'.join(context)

        if self.lang == 'fr':
            response = res['réponse']
            rationale = res['justification']
        elif lang == 'en':
            response = res['answer']
            rationale = res['rationale']

        source = res['source']
        history.append((query,response))#, "See details below))"))
        return history, "",response, rationale, source, documents

        
    def run_demo(self):
        if self.lang == 'fr':
            with gr.Blocks(theme=gr.themes.Glass()) as demo:
                gr.Image(value = 'crim_logo.png')
                gr.Markdown("## Démonstration d'IA générative")


                chatbot = gr.Chatbot(label="Conversation", height=400)
                gr.Markdown("Saisissez une requête ci-dessous et voyez la réponse et le raisonnement du système.")
                with gr.Row():
                    query_input = gr.Textbox(
                        show_label=False,
                        placeholder="Tapez quelque chose ...",
                        lines=1
                    )

                send_btn = gr.Button("Envoyer", scale = 0)
                gr.Markdown("### Dernière réponse")
                with gr.Row():
                    answer_output = gr.Textbox(label="Réponse", lines = 3, interactive=False)
                with gr.Row():
                    reasoning_output = gr.Textbox(label="Raisonnement du système", lines = 5,interactive=False)
                with gr.Row():
                        source_output = gr.Textbox(label="Source", interactive=False)


                with gr.Accordion("Documents récupérés", open=False):
                    docs_output = gr.Textbox(label="Documents justificatifs", interactive=False, lines=30)

                inputs = [chatbot, query_input]
                outputs = [chatbot, query_input, answer_output, reasoning_output, source_output,docs_output]
                query_input.submit(fn=self.process_query, inputs=inputs, outputs=outputs)
                send_btn.click(fn=self.process_query, inputs=inputs, outputs=outputs)

        elif self.lang == 'en':
            with gr.Blocks(theme=gr.themes.Glass()) as demo:
                gr.Image(value = 'crim_logo.png')
                gr.Markdown("## Generative AI Chat Demo with Structured Outputs")

                chatbot = gr.Chatbot(label="Conversation", height=400)

                with gr.Row():
                    query_input = gr.Textbox(
                        show_label=False,
                        placeholder="Type your query here and press Enter...",
                        lines=1
                    )

                send_btn = gr.Button("Send", scale = 0)
                gr.Markdown("### Latest Response Details")
                with gr.Row():
                    answer_output = gr.Textbox(label="Answer", interactive=False)
                with gr.Row():
                    reasoning_output = gr.Textbox(label="System Reasoning", interactive=False)
                with gr.Row():
                        source_output = gr.Textbox(label="Source", interactive=False)


                with gr.Accordion("Retrieved Documents", open=False):
                    docs_output = gr.Textbox(label="Supporting Documents", interactive=False, lines=30)

                inputs = [chatbot, query_input]
                outputs = [chatbot, query_input, answer_output, reasoning_output, source_output,docs_output]
                query_input.submit(fn=self.process_query, inputs=inputs, outputs=outputs)
                send_btn.click(fn=self.process_query, inputs=inputs, outputs=outputs)


                

        demo.launch()                       

      
        



def main():

    parser = argparse.ArgumentParser()
#    parser.add_argument('--config_file', type=str, required=True, help='File containing the configuration for the backend (in .ini format)')
#    args = parser.parse_args()

    config = configparser.ConfigParser()
    config.read('config.ini')
    demo = Demo(config)
    demo.run_demo()


if __name__ == "__main__":
    main()