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import gradio as gr | |
from indexer import index_text, answer_query | |
# Gradio interface function to handle the RAG system | |
def rag_system(query,history): | |
# Index the input text | |
vectorstore = index_text() | |
# Answer the query based on the indexed text | |
answer = answer_query(query,history, vectorstore) | |
return answer | |
iface = gr.ChatInterface( | |
rag_system, | |
type="messages", | |
chatbot=gr.Chatbot(height=600,placeholder="Let's understand AI Alignment"), | |
title="AI Alignment ChatBot", | |
textbox=gr.Textbox(placeholder="Ask Anything", container=True, scale=10), | |
theme="Origin", | |
examples=["What is Orthogonality Thesis?"] | |
) | |
# Launch the app | |
iface.launch() |