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| import gradio as gr | |
| from llama_index.core import VectorStoreIndex, SimpleDirectoryReader | |
| import openai | |
| import json | |
| from dotenv import load_dotenv | |
| import os | |
| openai.api_key = os.getenv("OPENAI_API_KEY") | |
| documents = SimpleDirectoryReader("data").load_data() | |
| index = VectorStoreIndex.from_documents(documents=documents) | |
| query_engine = index.as_query_engine() | |
| # Function to handle queries | |
| def query_document(message,history): | |
| response = query_engine.query(message) | |
| return str(response) | |
| interface = gr.ChatInterface(fn=query_document | |
| ,textbox=gr.Textbox(placeholder="Ask any information from DDS HR documents!") | |
| ,title="DDS Document Bot", description="Ask about the DDS HR Policy!") | |
| interface.launch(debug=True) | |