from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-Kontext-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('stablediffusionapi/my_flux_kontext_lora_v1', weight_name='my_flux_kontext_lora_v1.safetensors')
image = pipeline('make the person smile  --ctrl_img /my_workspace/server/control_folder/1.png').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers