Image-to-Story / app.py
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import gradio as gr
from share_btn import community_icon_html, loading_icon_html, share_js
import re
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, audience):
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
4, # 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, please provide a fictional story for a {audience} audience that would fit well with the image. Please be creative, do not worry and only generate a cool fictional story.
Here's the image description:
'{clipi_result[0]}'
"""
result = client.predict(
llama_q, # str in 'Message' Textbox component
api_name="/predict"
)
print(f"Llama2 result: {result}")
result = get_text_after_colon(result)
# Split the text into paragraphs based on actual line breaks
paragraphs = result.split('\n')
# Join the paragraphs back with an extra empty line between each paragraph
formatted_text = '\n\n'.join(paragraphs)
return formatted_text, gr.Group.update(visible=True)
css="""
#col-container {max-width: 910px; margin-left: auto; margin-right: auto;}
a {text-decoration-line: underline; font-weight: 600;}
a {text-decoration-line: underline; font-weight: 600;}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
#share-btn-container {
display: flex;
padding-left: 0.5rem !important;
padding-right: 0.5rem !important;
background-color: #000000;
justify-content: center;
align-items: center;
border-radius: 9999px !important;
max-width: 13rem;
}
div#share-btn-container > div {
flex-direction: row;
background: black;
align-items: center;
}
#share-btn-container:hover {
background-color: #060606;
}
#share-btn {
all: initial;
color: #ffffff;
font-weight: 600;
cursor:pointer;
font-family: 'IBM Plex Sans', sans-serif;
margin-left: 0.5rem !important;
padding-top: 0.5rem !important;
padding-bottom: 0.5rem !important;
right:0;
}
#share-btn * {
all: unset;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
#share-btn-container.hidden {
display: none!important;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(
"""
<h1 style="text-align: center">Image to Story</h1>
<p style="text-align: center">Upload an image, get a story made by Llama2 !</p>
"""
)
with gr.Row():
with gr.Column():
image_in = gr.Image(label="Image input", type="filepath", elem_id="image-in", height=420)
audience = gr.Radio(label="Target Audience", choices=["Children", "Adult"], value="Children")
submit_btn = gr.Button('Tell me a story')
with gr.Column():
#caption = gr.Textbox(label="Generated Caption")
story = gr.Textbox(label="generated Story", elem_id="story")
with gr.Group(elem_id="share-btn-container", visible=False) as share_group:
community_icon = gr.HTML(community_icon_html)
loading_icon = gr.HTML(loading_icon_html)
share_button = gr.Button("Share to community", elem_id="share-btn")
gr.Examples(examples=[["./examples/crabby.png", "Children"],["./examples/hopper.jpeg", "Adult"]],
fn=infer,
inputs=[image_in, audience],
outputs=[story, share_group],
cache_examples=True
)
submit_btn.click(fn=infer, inputs=[image_in, audience], outputs=[story, share_group])
share_button.click(None, [], [], _js=share_js)
demo.queue(max_size=12).launch()