main.py

from llama_index import SimpleDirectoryReader, GPTListIndex, LLMPredictor, PromptHelper, ServiceContext, GPTSimpleVectorIndex
from langchain.chat_models import ChatOpenAI
from langchain.llms import OpenAI
import gradio as gr
import sys
import os

"""
Requirement:
langchain==0.0.153
llama-index==0.5.4
PyPDF2
gradio

buat pdf disimpan di folder ./docs
recommended pakai venv
python main.py, nanti tinggal buka di local URL
"""

os.environ["OPENAI_API_KEY"] = 'openai_api_key'

def construct_index(directory_path):
    max_input_size = 4096
    num_outputs = 1024
    max_chunk_overlap = 40
    chunk_size_limit = 1200
    
    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
    # gpt-3.5-turbo paling bagus 
    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.2, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
    documents = SimpleDirectoryReader(directory_path).load_data()
    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
    index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context)
    index.save_to_disk('index.json')
    return index

def chatbot(input_text):
    index = GPTSimpleVectorIndex.load_from_disk('index.json')
    response = index.query(input_text, response_mode="compact")
    return response.response
iface = gr.Interface(fn=chatbot,
    				 inputs=gr.inputs.Textbox(lines=7, label="Enter your text"),
    				 outputs="text",
    				 title="test")
index = construct_index("docs")
iface.launch(share=True)