Spaces:
Paused
Paused
File size: 2,119 Bytes
56458a8 24c50a4 7175dd2 dd17729 afc2656 56458a8 dd17729 522e040 dd17729 522e040 dd17729 522e040 56458a8 7175dd2 fec39f8 dd17729 7175dd2 afc2656 dd17729 56458a8 07eca81 56458a8 7175dd2 56458a8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
import gradio as gr
import os
hf_token = os.environ.get('HF_TOKEN')
from gradio_client import Client
client = Client("https://fffiloni-test-llama-api.hf.space/", hf_token=hf_token)
clipi_client = Client("https://fffiloni-clip-interrogator-2.hf.space/")
def get_text_after_colon(input_text):
# Find the first occurrence of ":"
colon_index = input_text.find(":")
# Check if ":" exists in the input_text
if colon_index != -1:
# Extract the text after the colon
result_text = input_text[colon_index + 1:].strip()
return result_text
else:
# Return the original text if ":" is not found
return input_text
def infer(image_input):
clipi_result = clipi_client.predict(
image_input, # str (filepath or URL to image) in 'parameter_3' Image component
"best", # str in 'Select mode' Radio component
6, # int | float (numeric value between 2 and 24) in 'best mode max flavors' Slider component
api_name="/clipi2"
)
print(clipi_result)
llama_q = f"""
I'll give you a simple image caption, from i want you to provide a story that would fit well with the image:
'{clipi_result}'
"""
result = client.predict(
llama_q, # str in 'Message' Textbox component
api_name="/predict"
)
print(f"Llama2 result: {result}")
result = get_text_after_colon(result)
return clipi_result, result
css="""
#col-container {max-width: 910px; margin-left: auto; margin-right: auto;}
a {text-decoration-line: underline; font-weight: 600;}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(
"""
# Image to Story
Upload an image, get a story !
"""
)
image_in = gr.Image(label="Image input", type="filepath")
submit_btn = gr.Button('Sumbit')
caption = gr.Textbox(label="Generated Caption")
story = gr.Textbox(label="generated Story")
submit_btn.click(fn=infer, inputs=[image_in], outputs=[caption, story])
demo.queue().launch()
|