chatgpt.py

import os
import sys

import openai
from langchain.chains import RetrievalQA
from langchain.chat_models import ChatOpenAI
from langchain.document_loaders import DirectoryLoader, TextLoader
from langchain.embeddings import OpenAIEmbeddings
from langchain.indexes import VectorstoreIndexCreator
from langchain.indexes.vectorstore import VectorStoreIndexWrapper
from langchain.llms import OpenAI
from langchain.vectorstores import Chroma

import constants

os.environ["OPENAI_API_KEY"] = constants.APIKEY

# Enable to save to disk & reuse the model (for repeated queries on the same data)
PERSIST = False

query = sys.argv[1]

if PERSIST and os.path.exists("persist"):
  print("Reusing index...\n")
  vectorstore = Chroma(persist_directory="persist", embedding_function=OpenAIEmbeddings())
  index = VectorStoreIndexWrapper(vectorstore=vectorstore)
else:
  #loader = TextLoader("data/data.txt") # Use this line if you only need data.txt
  loader = DirectoryLoader("data/")
  if PERSIST:
    index = VectorstoreIndexCreator(vectorstore_kwargs={"persist_directory":"persist"}).from_loaders([loader])
  else:
    index = VectorstoreIndexCreator().from_loaders([loader])

chain = RetrievalQA.from_chain_type(
  llm=ChatOpenAI(model="gpt-3.5-turbo"),
  retriever=index.vectorstore.as_retriever(search_kwargs={"k": 1}),
)
print(chain.run(query))