bacancydataprophets/Data_Anonymization

1import streamlit as st2from langchain_experimental.data_anonymizer import PresidioAnonymizer, PresidioReversibleAnonymizer3from langchain_groq import ChatGroq4# from langchain.chat_models import ChatGroq 5from dotenv import load_dotenv6import os7# Load environment variables8load_dotenv()9 10GROQ_API_KEY = os.getenv("GROQ_API_KEY")11 12# Initialize anonymizer13anonymizer = PresidioReversibleAnonymizer()14llm = ChatGroq(model_name="llama-3.3-70b-versatile")  # Choose an available model15 16st.title("Call on Doc Data Anonymization")17 18# User Input19user_input = st.text_area("Enter your text:", "My name is John Doe and my phone number is 123-456-7890.")20 21if st.button("Process"):22    # Anonymization23    anonymized_text = anonymizer.anonymize(user_input)24    st.subheader("1. Original Text:")25    st.write(user_input)26    27    st.subheader("2. Anonymized Text:")28    st.write(anonymized_text)29    30    # Get LLM response31    response = llm.predict(anonymized_text)32    st.subheader("3. LLM Response:")33    st.write(response)34    35    # De-anonymization36    deanonymized_response = anonymizer.deanonymize(response)37    st.subheader("4. De-anonymized Response:")38    st.write(deanonymized_response)39