app2.py

from llama_index import SimpleDirectoryReader, GPTVectorStoreIndex, LLMPredictor, ServiceContext, StorageContext, load_indices_from_storage
from langchain import OpenAI
import gradio as gr
import os
import sys


#Video that helped me debug code:
#https://www.google.com/search?q=llama_index+GPTVectorStoreIndex.load_from_disk&sxsrf=AB5stBhdEaCyyzzr1fvXHEyR_S5tcpsYZw%3A1689355641558&ei=eYWxZKfZIffq1e8Pr5Kc8AU&ved=0ahUKEwjn-aeX3I6AAxV3dfUHHS8JB14Q4dUDCA8&uact=5&oq=llama_index+GPTVectorStoreIndex.load_from_disk&gs_lp=Egxnd3Mtd2l6LXNlcnAiLmxsYW1hX2luZGV4IEdQVFZlY3RvclN0b3JlSW5kZXgubG9hZF9mcm9tX2Rpc2syBxAhGKABGAoyBxAhGKABGApIm2ZQ4Q1YvGJwAXgBkAEAmAH4AaABuQaqAQUwLjEuM7gBA8gBAPgBAfgBAsICChAAGEcY1gQYsAPCAgQQIxgnwgINEAAYgAQYsQMYgwEYCsICBxAAGIAEGAriAwQYACBBiAYBkAYI&sclient=gws-wiz-serp#fpstate=ive&vld=cid:75e4eb00,vid:tU6EmusO43A

os.environ["OPENAI_API_KEY"] = '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' 
os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"

def construct_index(directory_path):
    num_outputs = 512

    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="text-davinci-003", max_tokens=num_outputs))

    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)

    docs = SimpleDirectoryReader(directory_path).load_data()

    index = GPTVectorStoreIndex.from_documents(docs, service_context=service_context)

    #index.save_to_disk('index.json')
    index.storage_context.persist(persist_dir = 'Store')

    return index

def chatbot(input_text):
    #index = GPTVectorStoreIndex.load_from_disk('index.json')
    storage_context = StorageContext.from_defaults(persist_dir = 'Store')
    index = load_indices_from_storage(storage_context)
    query_engine = index[0].as_query_engine()
    response = query_engine.query(input_text)
    #return response.response
    return response

iface = gr.Interface(fn=chatbot,
                     inputs=gr.inputs.Textbox(lines=7, label="Enter your text"),
                     outputs="text",
                     title="Custom-trained AI Chatbot")

index = construct_index("docs")
iface.launch(share=True)