ai_generate.py

import torch
from openai import OpenAI
import os
from transformers import pipeline

client = OpenAI(
    api_key=os.environ.get("openai_key"),
)

pipes = {
    'GPT-Neo': pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B"),
    'Llama 3': pipeline("text-generation", model="meta-llama/Meta-Llama-3-8B")
}

def generate(text, model):
    if model is "GPT-Neo":
        response = pipes[model](text)
        return response[0]
    elif model is "Llama 3":
        response = pipes[model](text)
        return response[0] 
    elif model is "OpenAI GPT 3.5":
        message=[{"role": "user", "content": text}]
        response = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages = message,
            temperature=0.2,
            max_tokens=800,
            frequency_penalty=0.0
        )
        return response[0].message.content
    elif model is "OpenAI GPT 4":
        message=[{"role": "user", "content": text}]
        response = client.chat.completions.create(
            model="gpt-4-turbo",
            messages = message,
            temperature=0.2,
            max_tokens=800,
            frequency_penalty=0.0
        )
        return response[0].message.content
    elif model is "OpenAI GPT 4o":
        message=[{"role": "user", "content": text}]
        response = client.chat.completions.create(
            model="gpt-4o",
            messages = message,
            temperature=0.2,
            max_tokens=800,
            frequency_penalty=0.0
        )
        return response[0].message.content