import gradio as gr
import random
import time

from ctransformers import AutoModelForCausalLM

# Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
model = AutoModelForCausalLM.from_pretrained(
    "manan05/mistral-7b-friends-v0.1.gguf",
    model_file="mistralfriends-7b-v0.1.gguf",
    model_type="mistral",
    gpu_layers=0,
    hf=True
)

from transformers import AutoTokenizer, pipeline

# Tokenizer
tokenizer = AutoTokenizer.from_pretrained("manan05/mistral-7b-friends")

# Pipeline
generator = pipeline(
    model=model, tokenizer=tokenizer,
    task='text-generation',
    max_new_tokens=50,
    repetition_penalty=1.1
)

with gr.Blocks() as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox()
    clear = gr.ClearButton([msg, chatbot])

    def respond(message, chat_history):
        user_message = "<s>[INST] Given the following conversation context, generate the upcomming dialogue of Joey in his style. \n CONTEXT: Me: " + message + "[/INST]"
        bot_message = generator(user_message[0]["generated_text"])
        chat_history.append((user_message, bot_message))
        time.sleep(2)
        return "", chat_history

    msg.submit(respond, [msg, chatbot], [msg, chatbot])

demo.launch()