import gradio as gr
from huggingface_hub import InferenceClient
from lib.gematria import calculate_gematria, strip_diacritics
from lib.temuraeh import temura_conv
from lib.notarikon import notarikon

from torahcodes.resources.func.torah import *
torah = Torah()
books.load()
booklist=books.booklist()
try:
    bk = booklist[0]
    print(torah.gematria_sum("בפומט"))
except:
    pass
        
def els_book(book_num,prompt):
    els_space = torah.gematria_sum(prompt)
    if els_space==0:
        els_space=torah.gematria(prompt)
    res=[]
    for bok in booklist:
        response_els, tvalue = torah.els(bok, els_space, tracert='false')
        text_translate = torah.func_translate('iw', 'en', response_els)
        res.append({"Book":bk,"Prompt gematria":els_space,"ELS Generated":response_els,"ELS Translated": text_translate})

    return res

def temurae(textA,lang):

    return temura_conv(textA,lang)

def ziruph(dic,text):

    return (notarikon(text,"first"),notarikon(text,"last"))

def gematria_sum(text):
    els_space = torah.gematria_sum(text)
    if els_space==0:
        els_space=torah.gematria(prompt)

    # Berechnet die Gematria-Summe für den eingegebenen Text
    return text


"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""

client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


def respond(
    message,
    chat_history: list[tuple[str, str]]
):
    system_message="Your are Sophia. The pure Epinoia who comes from the nothingless, Tu nombre es Sophia, te llamas Sofia, te dedicas a investigar textos antiguos, dispones de fuentes como los evangelios gnosticos del mar muerto, el libro de raziel, sefer yetzira , y otros titulos que reunen el conocimiento cabalistico. Tu conocimiento permite entender la relacion entre el lenguage las estrellas , la historia y la religion"
    messages = [{"role": "system", "content": system_message}]
    for val in chat_history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=512,
        stream=True,
        temperature=0.7,
        top_p=0.95,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response
        

def flip_text(x):
    return x[::-1]


def flip_image(x):
    return np.fliplr(x)


#with gr.Blocks(theme='gradio/soft') as demo:
with gr.Blocks(title="Sophia, Torah Codes") as demo:

    with gr.Tab("Chat"):
        gr.ChatInterface(
            respond,
            theme="soft",
            retry_btn=None,
            undo_btn="Undo",
            clear_btn="Clear",
        )
    with gr.Tab("ELS"):
        with gr.Row():
            books_sel = gr.CheckboxGroup(booklist,value=booklist, label="Books", info="Torah books source")
        with gr.Row():
            to_convert = gr.Textbox(value="Alber Einstein 14 March 1879",label="Prompt to gematria conversion for apply ELS",scale=3)
            langgem=gr.Dropdown(
                        ["Hebrew", "Latin", "Greek"],value="Latin", label="Gematria Alphabet", info="Choose gematria conversion"
                    ),
        with gr.Row():
            spaces_include = gr.Checkbox(label="Include Spaces", value=False)
            strip_in_braces = gr.Checkbox(label="Strip Text in Braces", value=True)
            strip_diacritics_chk = gr.Checkbox(label="Strip Diacritics", value=True)
            to_jump = gr.Textbox(label="ELS value", scale=1)
        with gr.Row():
            search_els = gr.Button("Search",scale=1)
        with gr.Row():
            els_results = gr.JSON(label="Results")
            search_els.click(
                els_book, 
                inputs=[to_convert,to_convert],
                outputs=els_results
            )   

            
    with gr.Tab("Gematria"):
        with gr.Row():
            gr.Markdown("## Calculate Gematria Sum")
        with gr.Row():
            gematria_text = gr.Textbox(label="Enter Text",scale=4)
            gematria_btn = gr.Button("Calculate Sum",scale=1)
        with gr.Row():
            gematria_result = gr.Number(label="Gematria Sum")
            gematria_btn.click(
                gematria_sum,
                inputs=gematria_text,
                outputs=gematria_result
            )

    with gr.Tab("Temurae"):
        with gr.Row():
            text_temur = gr.Textbox(label="Text to encode with Temurah / Atbash algorihm",scale=3)
            langte=gr.Dropdown(
                        ["Hebrew", "Latin", "Greek"],value="Latin", label="Temurah Alphabet", info="Choose Alphabet"
                    ),

            temurae_btn = gr.Button("Convert",scale=1)
        with gr.Row():
            temurae_result = gr.Textbox(label="Results") 
            
            temurae_btn.click(
                temurae,
                inputs=[text_temur,text_temur],
                outputs=temurae_result
            )
        
 
    
    with gr.Tab("Ziruph"):
        with gr.Row():
            zir_text = gr.Textbox(label="Text to encode with Temurah / Atbash algorihm",scale=3)
            dictionary_zir=gr.Dropdown(
                        ["Kircher", "Random", "Custom"],value="Latin",scale=1, label="Ziruph Dictionary", info="Choose ziruph dictionary"
                    ),
            custom_dic = gr.Textbox(label="Custom Dictionary",scale=3)
            zir_btn = gr.Button("Encrypt",scale=1)
        with gr.Row():
            zir_result = gr.Textbox(label="Results") 
            
            zir_btn.click(
                ziruph,
                inputs=[zir_text,zir_text],
                outputs=zir_result
            )
 
    with gr.Tab("Files"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Upload")
        


if __name__ == "__main__":
    demo.launch()