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from gpt_index import Document, SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import openai
import gradio as gr
import sys
import os
def chatbot(indexName, input_text):
"""
Chatbot function that takes in a prompt and returns a response
"""
index = GPTSimpleVectorIndex.load_from_disk(indexName+'.json')
response = index.query(input_text, response_mode="compact")
return response.response
iface = gr.Interface(fn=chatbot,
inputs= [
gr.Dropdown(["RetroFeedback", "WizFeedback", "Passwordless"],
type="value", value="RetroFeedback", label="Select Pulse Data"),
gr.Textbox(lines=7, label="Ask any question", placeholder='What is the summary?')],
outputs="text",
title="NLP Demo for Chat Interface")
iface.launch(auth=('axiamatic', os.environ['LOGIN_PASS']),
auth_message='For access, please check my Slack profile or contact me in Slack.',
share=False) |