tech-bot / app.py
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Update app.py
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import streamlit as st
from transformers import AutoTokenizer
from transformers import AutoModelForSeq2SeqLM
# Load the model and tokenizer from your Hugging Face Hub repository
model_checkpoint = "abdulllah01/checkpoints" # Replace with your actual checkpoint
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
# Create a pipeline for question answering
# Streamlit UI setup
st.title("Tech Support Bot")
st.write("Enter a context and ask a question related to Tech to get your problems solved!")
# Text area for context input
context = st.text_area("Context:", "")
# Text input for the question
question = st.text_input("Question:", "")
# Example input question and context (document) from your dataset
# Prepare the input text
input_text = f"question: {question} context: {context}"
input_ids = tokenizer.encode(input_text, return_tensors="pt")
# Generate the answer
if st.button("Get Answer"):
if context and question:
# Generate the answer using the pipeline
output_ids = model.generate(input_ids)
answer = tokenizer.decode(output_ids[0], skip_special_tokens=True)
st.write("**Answer:**", answer)
else:
st.write("Please enter both context and question.")