# import gradio as gr
# from groq import Groq

# client = Groq(
#     api_key=("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"),
# )

# def generate_response(input_text):
#     chat_completion = client.chat.completions.create(
#         messages=[
#             {
#                 "role": "user",
#                 "content": input_text,
#             }
#         ],
#         model="llama3-8b-8192",
#     )
#     return chat_completion.choices[0].message.content

# custom_css = """
# body {
#     background-color: #f5f5f5;
#     font-family: 'Arial', sans-serif;
#     color: #333;
# }

# .gradio-container {
#     border-radius: 12px;
#     padding: 20px;
#     background-color: #ffffff;
#     box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
# }

# input[type="text"], textarea {
#     border-radius: 10px;
#     border: 1px solid #ddd;
#     padding: 12px;
#     width: 100%;
#     font-size: 14px;
#     color: #333;
#     background-color: #f9f9f9;
# }

# button {
#     background-color: #007bff;
#     color: white;
#     border: none;
#     padding: 12px 24px;
#     border-radius: 10px;
#     cursor: pointer;
#     font-size: 14px;
#     font-weight: bold;
# }

# button:hover {
#     background-color: #0056b3;
# }

# h1 {
#     font-weight: 600;
#     color: #333;
# }

# textarea {
#     resize: none;
# }
# """

# iface = gr.Interface(
#     fn=generate_response,
#     inputs=gr.Textbox(label="ورودی" , lines=2, placeholder="اینجا یه چی بپرس... "),
#     outputs=gr.Textbox(label="جواب"),
#     title="💬 Parviz Chatbot",
#     description="زنده باد",
#     theme="dark",
#     allow_flagging="never"

# )
# iface.launch()

# import gradio as gr
# from groq import Groq
# import time

# client = Groq(api_key="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")

# def generate_response(message, chat_history):
#     chat_completion = client.chat.completions.create(
#         messages=[{"role": "user", "content": message}],
#         model="llama3-8b-8192",
#     )
#     bot_message = chat_completion.choices[0].message.content
    
#     for i in range(0, len(bot_message), 10):
#         yield chat_history + [(message, bot_message[:i + 10])]
#         time.sleep(0.1)
    
#     yield chat_history + [(message, bot_message)]


# with gr.Blocks() as demo:
#     gr.Markdown("<h1 style='text-align: center;'>💬 Parviz Chatbot</h1><p style='text-align: center; color: #e0e0e0;'>زنده باد</p>")
    
#     chatbot = gr.Chatbot(label="جواب")
#     msg = gr.Textbox(label="ورودی", placeholder="اینجا یه چی بپرس... ", lines=1)
    
#     msg.submit(generate_response, [msg, chatbot], chatbot)
    
#     clear = gr.ClearButton([msg, chatbot])
# demo.launch()








import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, GenerationConfig
import re
import time


tokenizer = AutoTokenizer.from_pretrained("universitytehran/PersianMind-v1.0")
model = AutoModelForSeq2SeqLM.from_pretrained("universitytehran/PersianMind-v1.0")


def generate_response(message, chat_history):

    TEMPLATE = "{context}\nYou: {prompt}\nParvizGPT "
    CONTEXT = "This is a conversation with ParvizGPT. It is an artificial intelligence model designed by Amir Mahdi Parviz " \
        "NLP expert to help you with various tasks such as answering questions, " \
        "providing recommendations, and helping with decision making. You can ask it anything you want and " \
        "it will do its best to give you accurate and relevant information."
    
    prompt = TEMPLATE.format(context=CONTEXT, prompt=message)

    generation_config = GenerationConfig(
        max_new_tokens=128,
        do_sample=True,
        top_k=50,
        top_p=0.95,
        temperature=0.8,
        repetition_penalty=1.2
    )

    tokenized_test_text = tokenizer(prompt, return_tensors='pt').input_ids.to("cpu")
    model.to("cpu")
    

    outputs = model.generate(tokenized_test_text, generation_config=generation_config, max_new_tokens=128)
    result = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]

    for i in range(0, len(result), 10):
        yield chat_history + [(message, result[:i + 10])]
        time.sleep(0.1)

    yield chat_history + [(message, result)]



with gr.Blocks() as demo:
    gr.Markdown("<h1 style='text-align: center;'>💬 Parviz GPT</h1><p style='text-align: center;'>made by A.M.Parviz \</p>")
    
    chatbot = gr.Chatbot(label="جواب")
    msg = gr.Textbox(label="ورودی", placeholder="سوال خودتو رو بپرس", lines=1)
    
    msg.submit(generate_response, [msg, chatbot], chatbot)
    
    clear = gr.ClearButton([msg, chatbot])

demo.launch()