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import os
import gradio as gr
import requests
from PIL import Image
from src.application.content_detection import NewsVerification
from src.application.url_reader import URLReader
from src.application.content_generation import generate_fake_image, generate_fake_text, replace_text
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
SEARCH_ENGINE_ID = os.getenv('SEARCH_ENGINE_ID')
AZURE_TEXT_MODEL = ["gpt-4o-mini", "gpt-4o"]
AZURE_IMAGE_MODEL = ["dall-e-3", "Stable Diffusion (not supported)"]
def load_url(url):
"""
Load content from the given URL.
"""
content = URLReader(url)
image = None
header = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36'}
try:
response = requests.get(
url,
headers = header,
stream = True
)
response.raise_for_status() # Raise an exception for bad status codes
image_response = requests.get(content.top_image, stream=True)
try:
image = Image.open(image_response.raw)
except:
print(f"Error loading image from {content.top_image}")
except (requests.exceptions.RequestException, FileNotFoundError) as e:
print(f"Error fetching image: {e}")
return content.title, content.text, image
def generate_analysis_report(news_title:str, news_content: str, news_image: Image):
news_analysis = NewsVerification()
news_analysis.load_news(news_title, news_content, news_image)
news_analysis.generate_analysis_report()
return news_analysis.analyze_details()
# Define the GUI
with gr.Blocks() as demo:
gr.Markdown("# NEWS VERIFICATION")
with gr.Row():
# SETTINGS
with gr.Column(scale=1):
with gr.Accordion("1. Enter a URL"):
url_input = gr.Textbox(
label="",
show_label=False,
value="",
)
load_button = gr.Button("Load URL")
with gr.Accordion("2. Select content-generation models", open=True, visible=False):
with gr.Row():
text_generation_model = gr.Dropdown(choices=AZURE_TEXT_MODEL, label="Text-generation model")
image_generation_model = gr.Dropdown(choices=AZURE_IMAGE_MODEL, label="Image-generation model")
generate_text_button = gr.Button("Generate text")
generate_image_button = gr.Button("Generate image")
with gr.Accordion("3. Replace any terms", open=True, visible=False):
replace_df = gr.Dataframe(
headers=["Find what:", "Replace with:"],
datatype=["str", "str"],
row_count=(1, "dynamic"),
col_count=(2, "fixed"),
interactive=True
)
replace_button = gr.Button("Replace all")
# GENERATED CONTENT
with gr.Accordion("Input News"):
news_title = gr.Textbox(label="Title", value="")
news_image = gr.Image(label="Image", type="filepath")
news_content = gr.Textbox(label="Content", value="", lines=12)
# NEWS ANALYSIS REPORT
with gr.Column(scale=2):
with gr.Accordion("News Analysis"):
detection_button = gr.Button("Verify news")
detailed_analysis = gr.HTML()
# Connect events
load_button.click(
load_url,
inputs=url_input,
outputs=[news_title, news_content, news_image]
)
replace_button.click(replace_text,
inputs=[news_title, news_content, replace_df],
outputs=[news_title, news_content])
generate_text_button.click(generate_fake_text,
inputs=[text_generation_model, news_title, news_content],
outputs=[news_title, news_content])
generate_image_button.click(generate_fake_image,
inputs=[image_generation_model, news_title],
outputs=[news_image])
detection_button.click(generate_analysis_report,
inputs=[news_title, news_content, news_image],
outputs=[detailed_analysis])
# change Image
#url_input.change(load_image, inputs=url_input, outputs=image_view)
try:
with open('sample_1.txt','r', encoding='utf-8') as file:
text_sample_1 = file.read()
with open('sample_2.txt','r', encoding='utf-8') as file:
text_sample_2 = file.read()
with open('sample_3.txt','r', encoding='utf-8') as file:
text_sample_3 = file.read()
except FileNotFoundError:
print("File not found.")
except Exception as e:
print(f"An error occurred: {e}")
title_1 = "The ancient discovery that put a Silk Road city back on the map"
title_2 = "The modern rediscovery that erased a Silk Road city from the map"
image_1 = "sample_1.jpg.webp"
image_2 = "sample_2.jpg.webp"
gr.Examples(
examples=[
[title_1, image_1, text_sample_1],
[title_2, image_2, text_sample_2],
[title_1, image_2, text_sample_3],
],
inputs=[news_title, news_image, news_content],
label="Examples",
example_labels=[
"2 real news",
"2 modified news",
"1 real news & 1 fake news",
],
)
demo.launch(share=False)
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