pyarrow.lib.arrowinvalid: cannot mix list and non-list, non-null values with map function

### Describe the bug

Encounter pyarrow.lib.arrowinvalid error with map function in some example when loading the dataset

### Steps to reproduce the bug

```
from datasets import load_dataset
from PIL import Image, PngImagePlugin

dataset = load_dataset("leonardPKU/GEOQA_R1V_Train_8K")
system_prompt="You are a helpful AI Assistant"
def make_conversation(example):
    prompt = []

    prompt.append({"role": "system", "content": system_prompt})
    prompt.append(
            {
                "role": "user", 
                "content": [
                        {"type": "image"},
                        {"type": "text", "text": example["problem"]},
                        ]
            }
        )
    return {"prompt": prompt}

def check_data_types(example):
    for key, value in example.items():
        if key == 'image':
            if not isinstance(value, PngImagePlugin.PngImageFile):
                print(value)
        if key == "problem" or key == "solution":
            if not isinstance(value, str):
                print(value)

    return example

dataset = dataset.map(check_data_types)
dataset = dataset.map(make_conversation)
```

### Expected behavior

Successfully process the dataset with map

### Environment info

datasets==3.3.1

Comments:
@lhoestq 

Can you try passing text: None for the image object ? Pyarrow expects all the objects to have the exact same type, in particular the dicttionaries in "content" should all have the keys "type" and "text"

The following modification on system prompt works, but it is different from the usual way to use it.
```
def make_conversation(example):
    prompt = []

    prompt.append({"role": "system", "content": [{"type": "text", "text": system_prompt}]})
    prompt.append(
            {
                "role": "user", 
                "content": [
                        {"type": "image"},
                        {"type": "text", "text": example["problem"]},
                        ]
            }
        )
    return {"prompt": prompt}
```

Good to know ! But yes Arrow / Parquet have this typing limitation (which is great to ensure data integrity, but constraining at the same time). It's is really blocking you, feel free to ping the arrow team / community if they plan to have a Union type or a JSON type

I encounter exactly the similar problem when using pyarrow. This issue truly helps a lot.

It would be very helpful if the error message could provide more context (such as the row index or the offending data) when this issue occurs. When loading large datasets, it's currently like finding a needle in a haystack because we don't know which specific entry caused the type mismatch.

Hi ! with #8027 you will be able to run your code, you'll simply need to pass `features=` with the new `Json()` type, or instead simply pass `on_mixed_types="use_json"`:

```diff
- dataset = dataset.map(make_conversation)
+ dataset = dataset.map(make_conversation, on_mixed_types="use_json")
```

This will encode your fields with mixed types as JSON under the hood. And the resulting dataset looks like this (note the `Json()` type of the `"content"` field)

```python
>>> dataset
DatasetDict({
    train: Dataset({
        features: ['image', 'problem', 'solution', 'prompt'],
        num_rows: 8031
    })
})
>>> dataset["train"].features
{'image': Image(), 'problem': Value('string'), 'solution': Value('string'), 'prompt': List({'content': Json(), 'role': Value('string')})}
>>> dataset["train"][0]
{'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=165x56 at 0x12416E450>,
 'problem': 'In the given diagram, if angle 1 has a measure of 35.0 degrees, what is the measure of angle 2?',
 'solution': '<answer> 145° </answer>',
 'prompt': [
   {'content': 'You are a helpful AI Assistant', 'role': 'system'},
   {'content': [{'type': 'image'}, {'type': 'text', 'text': 'In the given diagram, if angle 1 has a measure of 35.0 degrees, what is the measure of angle 2?'}], 'role': 'user'}
 ]}
```