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| 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() |