gpt.py

from openai import OpenAI
import os
import base64
import requests
from prompts import prompts
from constants import JSON_SCHEMA_FOR_GPT

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

client = OpenAI(api_key=OPENAI_API_KEY)
model = "gpt-4o"
title = "Caimera Mood board Expert"


def createAssistant(instruction_prompt):
    instructions = instruction_prompt
    assistant = client.beta.assistants.create(
        name=title,
        instructions=instructions,
        model=model
    )
    return assistant.id


def saveFileOpenAI(location):
    with open(location, "rb") as f:
        file = client.files.create(file=f, purpose="vision")
    os.remove(location)
    return file.id


def startAssistantThread(file_id_enum, prompt_n, image_needed, json_mode_needed_or_not):
    if json_mode_needed_or_not == "yes":
        if image_needed == "yes":
            messages = [
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "text",
                            "text": prompt_n
                        }
                    ],
                }
            ]
            for file_id in file_id_enum:
                messages[0]["content"].append({
                    "type": "image_file",
                    "image_file": {"file_id": file_id}
                })
        else:
            messages = [
                {
                    "role": "user",
                    "content": prompt_n}]
        thread = client.beta.threads.create(messages=messages)
    else:
        if image_needed == "yes":
            messages = [
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "text",
                            "text": prompt_n
                        }
                    ],
                }
            ]
            for file_id in file_id_enum:
                messages[0]["content"].append({
                    "type": "image_file",
                    "image_file": {"file_id": file_id}
                })
        else:
            messages = [
                {
                    "role": "user",
                    "content": prompt_n}]
        thread = client.beta.threads.create(messages=messages)
    return thread.id


def runAssistant(thread_id, assistant_id):
    run = client.beta.threads.runs.create(thread_id=thread_id, assistant_id=assistant_id)
    return run.id


def checkRunStatus(thread_id, run_id):
    run = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run_id)
    return run.status


def retrieveThread(thread_id):
    thread_messages = client.beta.threads.messages.list(thread_id)
    list_messages = thread_messages.data
    thread_messages = []
    for message in list_messages:
        obj = {}
        obj['content'] = message.content[0].text.value
        obj['role'] = message.role
        thread_messages.append(obj)
    return thread_messages[::-1]


def addMessageToThread(thread_id, prompt_n):
    thread_message = client.beta.threads.messages.create(thread_id, role="user", content=prompt_n)


def create_chat_completion_request_open_ai_for_summary(prompt, json_mode, schema_name="",
                                                       json_schema="",
                                                       system_message="You are expert in Fashion "
                                                                      "Shoots"):
    import requests
    if json_mode == "No":
        url = "https://api.openai.com/v1/chat/completions"
        headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {OPENAI_API_KEY}"
        }
        data = {
            "model": "gpt-4o",
            "messages": [
                {
                    "role": "system",
                    "content": system_message
                },
                {
                    "role": "user",
                    "content": prompt
                }
            ]
        }
        response = requests.post(url, headers=headers, json=data)
        json_response = response.json()
    else:
        url = "https://api.openai.com/v1/chat/completions"
        headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {OPENAI_API_KEY}"
        }
        data = {
            "model": "gpt-4o",
            "messages": [
                {
                    "role": "system",
                    "content": "You are expert in creating prompts for Fashion Shoots."
                },
                {
                    "role": "user",
                    "content": prompt
                }
            ],
            "response_format": {"type": "json_schema", "json_schema": {"name": schema_name, "strict": True, "schema":
                json_schema}}
        }
        response = requests.post(url, headers=headers, json=data)
        json_response = response.json()
    print(json_response)
    return json_response["choices"][0]["message"]["content"]


def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')


def create_image_completion_request_gpt(image_path, prompt):
    base64_image = encode_image(image_path)
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {OPENAI_API_KEY}"
    }
    payload = {
        "model": "gpt-4o",
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": prompt
                    },
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": f"data:image/jpeg;base64,{base64_image}"
                        }
                    }
                ]
            }
        ],
    }
    response = requests.post("https://api.openai.com/v1/chat/completions",
                             headers=headers, json=payload)
    json_resp = response.json()
    return json_resp["choices"][0]["message"]["content"]