# in folder ==> gradio test_gradio.py ( it won’t provide the automatic reload mechanism?)

import gradio as gr
import numpy as np
import random
import time

# def greet(name):
#     return "Hello " + name + "!"

# demo = gr.Interface(fn=greet, inputs=gr.Textbox(lines=2, placeholder="Name Here..."), outputs="text")
    
# demo.launch()   


# def greet2(name, is_morning, temperature):
#     salutation = "Good morning" if is_morning else "Good evening"
#     greeting = f"{salutation} {name}. It is {temperature} degrees today"
#     celsius = (temperature - 32) * 5 / 9
#     return greeting, round(celsius, 2)

# demo = gr.Interface(
#     fn=greet2,
#     inputs=["text", "checkbox", gr.Slider(0, 100)],
#     outputs=["text", "number"],
# )
# demo.launch()


# def sepia(input_img):
#     sepia_filter = np.array([
#         [0.393, 0.769, 0.189], 
#         [0.349, 0.686, 0.168], 
#         [0.272, 0.534, 0.131]
#     ])
#     sepia_img = input_img.dot(sepia_filter.T)
#     sepia_img /= sepia_img.max()
#     return sepia_img

# demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")
# demo.launch()





def yes_man(message, history):
    if message.endswith("?"):
        return "Yes"
    else:
        return "Ask me anything!"



# gr.ChatInterface(
#     yes_man,
#     chatbot=gr.Chatbot(height=300),
#     textbox=gr.Textbox(placeholder="Ask a question about the uploaded PDF document.", container=False, scale=7),
#     title="Gradio QA Bot",
#     description=f"{intro}",
#     theme="soft",
#     examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
#     cache_examples=True,
#     retry_btn=None,
#     undo_btn="Delete Previous",
#     clear_btn="Clear",
# ).launch()


# intro = "Welcome! This is not just any bot, ..."
title1 = "QA App"
title2 = "Gradio QA Bot"


def file_upload(input_file):
    # Process the uploaded file
    if input_file is not None:
        # Save the uploaded file or perform any desired operations
        file_path = "/tmp/file.pdf"
        content = input_file.read()
        try:
            with open(file_path, 'wb') as file:
                file.write(content)
            return [f"File '{input_file.name}' uploaded successfully in {file_path}.",file_path] 
        except Exception as e:
            return f"Error occurred while writing the file: {e}"
    return ["No file uploaded.", file_path] 


def crash(test, file):
    return("ok")



gr.ChatInterface(
        yes_man,
        chatbot=gr.Chatbot(height=300),
        textbox=gr.Textbox(placeholder="Ask a question about the uploaded PDF document.", container=False, scale=7),
        title="Gradio QA Bot",
        description="blabla",
        theme="soft",
        examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
        cache_examples=True,
        retry_btn=None,
        undo_btn="Delete Previous",
        clear_btn="Clear",
    ).launch()


# with gr.Blocks() as demo:
#     intro = gr.Markdown("""Welcome! This is not just any bot, it's a special one equipped with state-of-the-art natural language processing capabilities, and ready to answer your queries.

#         Ready to explore? Let's get started!

#         * Step 1: Upload a PDF document.
#         * Step 2: Type in a question related to your document's content.
#         * Step 3: Get your answer!

#         Push clear cache before uploading a new doc!
#         """)
    
#     # Create a Gradio interface with a file upload input
#     iface = gr.Interface(
#         fn=file_upload,
#         inputs=gr.File(),
#         outputs=["text", gr.File()],
#         title=title1,
#         description="Drag and drop your document here")
    

#     # bot = gr.Interface(crash,
#     #             inputs=[gr.Textbox(lines=2, placeholder="Ask a question about the uploaded PDF document."), gr.File()],
#     #             outputs=[gr.Chatbot(height=300)],
#     #             title="Gradio QA Bot",
#     #             description=f"{intro}",
#     #             theme="soft",
#     #             examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
#     #             cache_examples=True,
#     #             retry_btn=None,
#     #             undo_btn="Delete Previous",
#     #             clear_btn="Clear")
    
#     # gr.ChatInterface(
#     #     yes_man,
#     #     chatbot=gr.Chatbot(height=300),
#     #     textbox=gr.Textbox(placeholder="Ask a question about the uploaded PDF document.", container=False, scale=7),
#     #     title="Gradio QA Bot",
#     #     description=f"{intro}",
#     #     theme="soft",
#     #     examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
#     #     cache_examples=True,
#     #     retry_btn=None,
#     #     undo_btn="Delete Previous",
#     #     clear_btn="Clear",
#     # )

# demo.launch()



# bot
iface = gr.Interface(qa_bot, 
                     inputs=["file", gr.Textbox(placeholder="Ask a question about the uploaded PDF document.", container=False, scale=7)],
                     outputs="text",
                     title=title2,
                     description="Ask a question about the uploaded PDF document.",
                     theme="soft",
                    examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
                    cache_examples=True,
                    retry_btn=None,
                    undo_btn="Delete Previous",
                    clear_btn="Clear")
#### OR 

iface =  gr.ChatInterface(
            qa_bot,
            chatbot=gr.Chatbot(height=300),
            textbox=gr.Textbox(placeholder="Ask a question about the uploaded PDF document.", container=False, scale=7),
            title=title2,
            description="Ask a question about the uploaded PDF document.",
            theme="soft",
            examples=["What is the title of the document?", "Summarize the main ideas of the documents"],
            cache_examples=True,
            retry_btn=None,
            undo_btn="Delete Previous",
            clear_btn="Clear",
        )