app.py

import gradio as gr
import os
from huggingface_hub import login
token = os.environ.get("token")
login(token)
####
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel, PeftConfig

from transformers import AutoTokenizer, pipeline

# Assuming you have it stored securely

model_name="Ikeofai/gemma-2b-for-python-v2"
max_length=200
tokenizer = AutoTokenizer.from_pretrained(model_name)
config = PeftConfig.from_pretrained(model_name,token=token)
model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path)
model = PeftModel.from_pretrained(model, model_name)

#testing

#tokenizer = AutoTokenizer.from_pretrained("Orcawise/eu-ai-act-align", use_fast=True,max_length=200)
#pipe = pipeline("text2text-generation", model=model,tokenizer=tokenizer)
#pipe = pipeline("conversational", model="google/vit-base-patch16-224")

#gr.Interface.from_pipeline(pipe).launch()

def generate_text(prompt):
    """Generates text using the PEFT model.
    Args:
        prompt (str): The user-provided prompt to start the generation.
           Returns:
        str: The generated text.
    """


    # Preprocess the prompt
    input_ids = tokenizer(prompt, return_tensors="pt")["input_ids"]

    # Generate text using beam search
    output = model.generate(
        input_ids=input_ids,
        max_length=max_length,
        num_beams=1,  # Adjust num_beams for better quality (may increase processing time)
    )

    # Decode the generated tokens
    generated_text = tokenizer.batch_decode(output, skip_special_tokens=True)[0]


    return generated_text
#############


### working correctly but  the welcoming message isnt rendering
with gr.Blocks() as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox(placeholder="Ask your question...")  # Add placeholder text
    submit_button = gr.Button("Submit")
    clear = gr.Button("Clear")


    def user(user_message, history):
        return "", history + [[user_message, None]]


    def bot(history):
      history[-1][1] = ""  # Update the last bot message (welcome message or response)
      if len(history) < 0:  # Check if it's the first interaction
          bot_message = "Hi there! How can I help you today?"
          history.append([None, bot_message])  # Add welcome message to history
          for character in bot_message:
            history[-1][1] += character
            yield history  # Yield the updated history character by character

      else:
          previous_message = history[-1][0]  # Access the previous user message
          bot_message = generate_text(previous_message)  # Generate response based on previous message
          for character in bot_message:
            history[-1][1] += character
            yield history  # Yield the updated history character by character



    # Connect submit button to user and then bot functions
    submit_button.click(user, [msg,  chatbot], [msg, chatbot], queue=False).then(
        bot, chatbot, chatbot
    )

    # Trigger user function on Enter key press (same chain as submit button)
    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
        bot, chatbot, chatbot
    )

    clear.click(lambda: None, None, chatbot, queue=False)

demo.launch()