#!/usr/bin/env python3
from diffusers import DiffusionPipeline
from huggingface_hub import HfApi
import os
from pathlib import Path
from compel import Compel
import torch

api = HfApi()

pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", variant="fp16", use_safetensors=True, torch_dtype=torch.float16).to("cuda")
compel = Compel(tokenizer=[pipeline.tokenizer, pipeline.tokenizer_2] , text_encoder=[pipeline.text_encoder, pipeline.text_encoder_2], use_penultimate_clip_layer=True, use_penultimate_layer_norm=False, requires_pooled=[False, True])

# upweight "ball"
prompt = "a cat playing with a ball-- in the forest"
conditioning, pooled = compel(prompt)

# generate image
image = pipeline(prompt_embeds=conditioning, pooled_prompt_embeds=pooled, num_inference_steps=30).images[0]

file_name = f"ball_minus_minus"
path = os.path.join(Path.home(), "images", f"{file_name}.png")
image.save(path)

api.upload_file(
    path_or_fileobj=path,
    path_in_repo=path.split("/")[-1],
    repo_id="patrickvonplaten/images",
    repo_type="dataset",
)
print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")