models/gpt_model.py

import openai

class ImageToText:
    def __init__(self, api_key):
        self.template = self.initialize_template()
        openai.api_key = api_key

    def initialize_template(self):
        prompt_prefix_1 = """Generate only an informative and nature paragraph based on the given information(a,b,c,d):\n"""  
        prompt_prefix_2 = """\n a. Image Resolution:  """
        prompt_prefix_3 = """\n b. Image Caption: """
        prompt_prefix_4 = """\n c. Dense Caption: """
        prompt_prefix_5 = """\n d. Region Semantic: """
        prompt_suffix = """\n There are some rules:
        Show object, color and position.
        Use nouns rather than coordinates to show position information of each object.
        No more than 7 sentences.
        Only use one paragraph.
        Do not appear number.
        """
        template = f"{prompt_prefix_1}{prompt_prefix_2}{{width}}X{{height}}{prompt_prefix_3}{{caption}}{prompt_prefix_4}{{dense_caption}}{prompt_prefix_5}{{region_semantic}}{prompt_suffix}"
        return template
    
    def paragraph_summary_with_gpt(self, caption, dense_caption, region_semantic, width, height):
        question = self.template.format(width=width, height=height, caption=caption, dense_caption=dense_caption, region_semantic=region_semantic)
        print('*'*100)
        print("question:", question)
        completion = openai.ChatCompletion.create(
            model="gpt-3.5-turbo", 
            messages = [
            {"role": "user", "content" : question}]
        )
        print("chatgpt response:", completion['choices'][0]['message']['content'])
        print('*'*100)
        return completion['choices'][0]['message']['content']

    def paragraph_summary_with_gpt_debug(self, caption, dense_caption, width, height):
        question = self.template.format(width=width, height=height, caption=caption, dense_caption=dense_caption)
        print("paragraph_summary_with_gpt_debug:")
        return question