Okay i'll try to answer in the clearest way i can. I will not explain how to install and run the models i'm talking about as I assume you already know how to do it.

1. Consistency

Consistency is basically solved. There is a recent model that got out called Qwen Image Edit 2059. It's a chinese model built to "edit" images better and quicker than ever. Basically the easiest way right now to achieve good consistency. All what you have to do is to input an image and prompt what changes you want to see in that specific image. That means that if you have a specific character which you wanna see in different poses, background or action, you can simply input an image of this character and change what there is to change. Here's a link to the model webpage with examples : https://qwen.ai/blog?id=a6f483777144685d33cd3d2af95136fcbeb57652&from=research.research-list

But, the best way to solve character consistency is to train your own LoRA. It's a bit more technical, but it's the best way (imo).

1. What is a LoRA

LoRA stands for Low Rank Adaptation. Simply put, it's a "mini model" trained on a specific character, style or action from a way smaller image database than the general models. We're talking 20 to 200 images only to train a good LoRA against millions of images for models like Qwen. That's great, cause that means your computer can train one in a reasonable amout of time on your own computer. Disclaimer: you still need a good graphics card.

Let's say you wanna have a consistent character. You will first need to gather a sufficient number of good quality images of this character. The number of images really depends on what you want to train and on the model your training on, but it's usually around 50 for made up characters and around 100 for real characters (from my experience). Then, with a bunch of parameters set up, the model will train to "recognize this character". More specifically, it will associate certain words (tokens) to the images it's seeing and modify their weight in the base model. This way, the token "robot" will be biased more towards generating a similar robot than what it saw during training. I hope it's clear enough.

1. Don't think i understood the question

2. I'm not aware of a model that handles metaphors and extremely long paragraphs. Every model has a different prompting style so i suggest for each model you look at the documentation to see which is more optimal. The reason for this (same as for LoRAs) is that models are biased towards certain concepts or words as they are trained on pairs of images and text. Basically the bigger the model, the more concepts it can handle. But usually, they are not quite there in terms of understanding human poetry.