app.py

# from langchain.text_splitter import RecursiveCharacterTextSplitter
# from langchain.document_loaders import UnstructuredFileLoader, DirectoryLoader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma
from langchain.chat_models import ChatOpenAI
from langchain.chains import RetrievalQA
import os, logging

# destination_folder = './data/'
# txt_dir_loader = DirectoryLoader(destination_folder, 
#                                  loader_cls=UnstructuredFileLoader)
# data = txt_dir_loader.load()

# text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, 
#                                                chunk_overlap=20)
# documents = text_splitter.split_documents(data)
print("LOGGING")

embeddings = OpenAIEmbeddings()
print("Got Embeddings")
persist_directory = "./vector_db"
# vectordb = Chroma.from_documents(documents=documents, 
#                                  embedding=embeddings, 
#                                  persist_directory=persist_directory)
# vectordb.persist()
# vectordb = None
vectordb = Chroma(persist_directory=persist_directory, 
                  embedding_function=embeddings)
print("Loaded vector db")

llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo")
print("Instatiated OpenAI LLM")
doc_retriever = vectordb.as_retriever()
print("Retrieved Docs")
hp_qa = RetrievalQA.from_chain_type(llm=llm, 
                                    chain_type="stuff", 
                                    retriever=doc_retriever)
print("Made hp_qa")

def answer_question(query):
  return(hp_qa.run(query))

if __name__ == "__main__":
    import gradio as gr
    # print(answer_question("Who is Harry's Father"))
    
    gr.Interface(
        answer_question,
        [
          gr.inputs.Textbox(lines=2, label="Query"),
        ],
        gr.outputs.Textbox(label="Response"),
        title="Ask Harry Potter",
        description=""" Ask Harry Potter is a tool that let's you ask a question with
                        the books' text as reference"""
    ).launch()