app.py

import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from datasets import load_dataset, Dataset
import pandas as pd

# Load the dataset
ds = load_dataset("bitext/Bitext-customer-support-llm-chatbot-training-dataset")

# Convert the dataset to a pandas DataFrame
df = ds['train'].to_pandas()

# Define labels based on your intent categories
label2id = {label: idx for idx, label in enumerate(df['intent'].unique())}
id2label = {idx: label for label, idx in label2id.items()}

# Encode labels
df['label'] = df['intent'].map(label2id)

# Ensure 'instruction', 'label', 'intent', and 'response' columns are included
df = df[['instruction', 'label', 'intent', 'response']]

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("Chillyblast/Roberta_Question_Answer")
model = AutoModelForSequenceClassification.from_pretrained("Chillyblast/Roberta_Question_Answer")

# Ensure the model is in evaluation mode
model.eval()

# Function to get the predicted intent and response
def get_intent_and_response(instruction):
    # Tokenize the input instruction
    inputs = tokenizer(instruction, return_tensors="pt", truncation=True, padding='max_length', max_length=128)

    # Perform inference
    with torch.no_grad():
        outputs = model(**inputs)
    logits = outputs.logits
    predicted_label_id = torch.argmax(logits, dim=1).item()
    
    # Decode the predicted label to get the intent
    predicted_intent = id2label[predicted_label_id]
    
    # Fetch the appropriate response based on the predicted intent
    response = df[df['intent'] == predicted_intent].iloc[0]['response']
    
    return predicted_intent, response

# Streamlit app setup
st.title("Customer Support Chatbot")
st.write("Ask a question, and I'll do my best to help you.")

instruction = st.text_input("You:")

if st.button("Submit"):
    if instruction:
        predicted_intent, response = get_intent_and_response(instruction)
        st.write(f"**Predicted Intent:** {predicted_intent}")
        st.write(f"**Assistant:** {response}")
    else:
        st.write("Please enter an instruction.")

if st.button("Exit"):
    st.write("Exiting the chat.")