import gradio as gr
import os
from openai import OpenAI
from dotenv import load_dotenv, find_dotenv

_ = load_dotenv(find_dotenv()) # read local .env file
os.environ['OPENAI_API_KEY'] = "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"
client = OpenAI()

# account for deprecation of LLM model
import datetime
# Get the current date
current_date = datetime.datetime.now().date()

# Define the date after which the model should be set to "gpt-3.5-turbo"
target_date = datetime.date(2024, 6, 12)

# Set the model variable based on the current date
if current_date > target_date:
    llm_model = "gpt-3.5-turbo"
else:
    llm_model = "gpt-3.5-turbo-0301"

def get_completion(prompt, model=llm_model):
    messages = [{"role": "user", "content": prompt}]
    response = client.chat.completions.create(
        model=model,
        messages=messages,
        temperature=0, 
    )
    return response.choices[0].message.content

def greet(Question):
  return get_completion(Question)

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()