Function create_generation_request

RealChart2Code_eval/evaluate_task3.py:247–306

(category: str, data_info: Dict[str, str], refine_before_image_path: str, image_path: str, improvement_suggestion: str, refine_before_code: str,
                            generation_prompt: str, user_history_generation_prompt:str, model_name: str)

def create_generation_request(category: str, data_info: Dict[str, str], refine_before_image_path: str, image_path: str, improvement_suggestion: str, refine_before_code: str,
                            generation_prompt: str, user_history_generation_prompt:str, model_name: str) -> Dict:
    
    # user_prompt = create_user_prompt(category, instruction, data_info)
    refine_before_image_base64 = encode_image_to_base64(refine_before_image_path)
    image_base64 = encode_image_to_base64(image_path)
    user1_content = [
        {
            "type": "text",
            "text": f"# Task /n Category: {category}. Note that in this environment, the version of matplotlib is {matplotlib.__version__}, the version of seaborn is {seaborn.__version__}, the version of plotly is {plotly.__version__}, the version of bokeh is {bokeh.__version__}, the version of altair is {altair.__version__}."
        },
        {
            "type": "image_url",
            "image_url": {
                "url": image_base64
            }
        }
    ]
    
    messages = [
        {"role": "system", "content": user_history_generation_prompt},
        {"role": "user", "content": user1_content}
    ]
    
    assistant1_content = f"""Here's the Python code:
```python
{refine_before_code}
```
"""

    user2_content = [
        {
            "type": "text",
            "text": f"Look at this chart image and fix the errors in the code based on the instruction provided.\nCategory: {category}.\n\n**Instruction**: {improvement_suggestion}.\n\n**chart image**:"
        },
        {
            "type": "image_url",
            "image_url": {
                "url": refine_before_image_base64
            }
        }
    ]
    
    messages.extend([
            {"role": "assistant", "content": assistant1_content},
            {"role": "user", "content": user2_content}
        ])
    
    print(user_history_generation_prompt)
    print(user1_content[0])
    print(assistant1_content)
    print(user2_content[0])
    
    return {
        "model": model_name,
        "messages": messages,
        "max_tokens": 32768,
        "temperature": 0.0,