main.py

from langchain_chroma import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from dotenv import load_dotenv

load_dotenv()

DB_PATH="db"

prompt_template = """
Answer the following question from user:
{question} 

using the follow knowledge base above:

{knowledge_base}"""

def make_question():
    question = input("Question: ")

    db = Chroma(persist_directory=DB_PATH, embedding_function=OpenAIEmbeddings())

    results = db.similarity_search_with_relevance_scores(question, k=4)    
    
    if len(results) == 0 or results[0][1] < 0.7: 
        print("Couldn't find an answer to that question")
    
    full_answer = []
    for result in results:
        text = result[0].page_content
        full_answer.append(text)

    knowledge_base = "\n\n ------ \n\n".join(full_answer)
    prompt = ChatPromptTemplate.from_template(prompt_template)
    prompt = prompt.invoke({"question": question, "knowledge_base": knowledge_base})

    model = ChatOpenAI()
    ai_answering = model.invoke(prompt)
    print(ai_answering)

make_question()