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import gradio as gr
import ai
import ai_tasks
import code_tasks
import custom_code
def open__get_text_from_url() -> str:
with open("code_tasks/text_in_url.py") as f:
return f.read()
def open__get_images_from_url() -> str:
with open("code_tasks/images_in_url.py") as f:
return f.read()
def open__get_image_infos() -> str:
with open("custom_code/image_analysis.py") as f:
return f.read()
def get_text_and_images_from_url(url):
return (
code_tasks.text_in_url.get_text_from_url(url),
code_tasks.images_in_url.get_images_from_url(url),
)
def get_images_analysis(images):
return custom_code.image_analysis.analyze_images(eval(images))
def summarize_text(
prompt,
url,
dimensions,
text,
images,
image_infos,
summary,
headline,
):
return ai_tasks.text_summary._summarize_text(
prompt,
url=url,
dimensions=dimensions,
text=text,
images=images,
image_infos=image_infos,
summary=summary,
headline=headline,
)
def get_headline_for_image(
prompt,
url,
dimensions,
text,
images,
image_infos,
summary,
headline,
):
import json
output = ai_tasks.headlines_for_images._get_headline_for_image(
prompt,
url=url,
dimensions=dimensions,
text=text,
images=images,
image_infos=image_infos,
summary=summary,
headline=headline,
)
return output, json.loads(output)["image_url"]
def get_headline_and_prompt(
prompt,
url,
dimensions,
text,
images,
image_infos,
summary,
headline,
):
import json
output = ai_tasks.headlines_for_ai_images._generate_headline_and_prompt(
prompt,
url=url,
dimensions=dimensions,
text=text,
images=images,
image_infos=image_infos,
summary=summary,
headline=headline,
)
output_dict = json.loads(output)
return (
output,
output_dict["ai_prompt"],
output_dict["ai_prompt"],
output_dict["dimension_to_map"],
output_dict["dimension_to_map"],
)
def generate_image(prompt, dimensions):
return ai.image.urls(prompt, 1, dimensions)[0]
with gr.Blocks() as demo:
gr.Markdown(
"""
## Scrape a website and get an ad
Enter an url and the dimensions for an image (eg, 300x600).
<br> A sequence of code and AI tasks will scrape the website and find an image that best fits those dimensions. They will also generate an AI image.
<br> It's your job to edit either of those images. If the image urls are invalid, the app will break.
<br> A headline for your ad will also be generated.
<br> Play around with the AI tasks to get different results. Text in between {} are variables that you have access to.
"""
)
url = gr.Textbox(label="Input: {url}")
dimensions = gr.Textbox(label="Input: {dimensions}")
execute = gr.Button("Run")
with gr.Box():
gr.Markdown("Code task")
with gr.Row():
with gr.Column():
gr.Textbox(
"write a python function that given an url returns all text in the website",
label="ChatGPT-4 prompt",
)
with gr.Accordion("Input: {url}", open=False):
gr.Code(open__get_text_from_url(), "python")
with gr.Column():
text = gr.Textbox(
label="Output: {text}", lines=10, max_lines=10, interactive=False
)
with gr.Box():
gr.Markdown("Code task")
with gr.Row():
with gr.Column():
gr.Textbox(
"write a python function that given an url returns all images in the website",
label="ChatGPT-4 prompt",
)
with gr.Accordion("Input: {url}", open=False):
gr.Code(open__get_images_from_url(), "python")
with gr.Column():
images = gr.Textbox(
label="Output: {images}", lines=10, max_lines=10, interactive=False
)
with gr.Box():
gr.Markdown("Custom code: analyze images with Google Vision")
with gr.Row():
with gr.Column():
with gr.Accordion("Input: {images}", open=False):
gr.Code(open__get_image_infos(), "python")
with gr.Column():
image_infos = gr.Textbox(
label="Output: {image_infos}",
lines=10,
max_lines=10,
interactive=False,
)
with gr.Box():
gr.Markdown("AI task: summarize text")
with gr.Row():
with gr.Column():
summary_prompt = gr.Textbox(
ai_tasks.text_summary.PROMPT,
label="Instructions:",
interactive=True,
)
with gr.Column():
summary = gr.Textbox(
label="Output: {summary}", lines=10, max_lines=10, interactive=False
)
with gr.Box():
gr.Markdown("AI task: generate headline for image")
with gr.Row():
with gr.Column():
headline_prompt = gr.Textbox(
ai_tasks.headlines_for_images.PROMPT,
label="Instructions:",
interactive=True,
lines=20,
)
with gr.Column():
headline = gr.Textbox(
label="Output: {headline}",
lines=10,
max_lines=10,
interactive=False,
)
headline_image = gr.Image(interactive=False)
with gr.Box():
gr.Markdown("AI task: generate headline and prompt for image")
with gr.Row():
with gr.Column():
ai_prompt_prompt = gr.Textbox(
ai_tasks.headlines_for_ai_images.PROMPT,
label="Instructions:",
interactive=True,
)
with gr.Column():
headline_and_prompt = gr.Textbox(
label="Output: {headline_prompt}",
lines=10,
max_lines=10,
interactive=False,
)
dimension_to_map = gr.Textbox(
label="Output: {dimension_to_map}",
interactive=False,
)
ai_prompt = gr.Textbox(
label="Output: {ai_prompt}",
interactive=False,
)
with gr.Box():
gr.Markdown("AI task: generate image")
with gr.Row():
with gr.Column():
ai_image_prompt = gr.Textbox(
label="Instructions: {ai_prompt}",
interactive=False,
)
image_dimensions = gr.Textbox(
label="Input: {dimension_to_map}",
interactive=False,
)
with gr.Column():
ai_image = gr.Image()
vars_ = [
url,
dimensions,
text,
images,
image_infos,
summary,
headline,
]
execute.click(
get_text_and_images_from_url, inputs=[url], outputs=[text, images]
).success(
get_images_analysis,
inputs=[images],
outputs=[image_infos],
).success(
summarize_text,
inputs=[summary_prompt] + vars_, # type: ignore
outputs=[summary],
).success(
get_headline_for_image,
inputs=[headline_prompt] + vars_, # type: ignore
outputs=[headline, headline_image],
).then(
get_headline_and_prompt,
inputs=[ai_prompt_prompt] + vars_, # type: ignore
outputs=[
headline_and_prompt,
ai_prompt,
ai_image_prompt,
dimension_to_map,
image_dimensions,
],
).success(
generate_image, inputs=[ai_image_prompt, image_dimensions], outputs=[ai_image]
)
demo.launch()
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