Spaces:
Running
Running
File size: 5,004 Bytes
22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 1ce1659 22e1b62 |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
import os
import gradio as gr
import openai
import requests
from PIL import Image
import re
from src.application.content_detection import generate_analysis_report
from src.application.url_reader import URLReader
from src.application.content_generation import generate_content, replace_text
# from dotenv import load_dotenv
# load_dotenv()
# AZURE_OPENAI_API_KEY = os.getenv('AZURE_OPENAI_API_KEY')
# AZURE_OPENAI_ENDPOINT = os.getenv('AZURE_OPENAI_ENDPOINT')
# AZURE_OPENAI_API_VERSION = os.getenv('AZURE_OPENAI_API_VERSION')
# client = openai.AzureOpenAI(
# api_version = AZURE_OPENAI_API_VERSION,
# api_key = AZURE_OPENAI_API_KEY,
# azure_endpoint = AZURE_OPENAI_ENDPOINT,
# )
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
SEARCH_ENGINE_ID = os.getenv('SEARCH_ENGINE_ID')
AZURE_OPENAI_MODEL = ["gpt-4o-mini", "gpt-4o"]
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 show_detailed_analysis(title):
return f"More details of {title} will be shown here."
# Define the GUI
with gr.Blocks() as demo:
gr.Markdown("# FAKE NEWS DETECTION")
with gr.Row():
# SETTINGS
with gr.Column(scale=1):
with gr.Accordion("Settings"):
gr.Markdown("This tool generates fake news by modifying the content of a given URL.")
with gr.Accordion("1. Enter a URL"):
url_input = gr.Textbox(
label="URL",
value="https://bbc.com/future/article/20250110-how-often-you-should-wash-your-towels-according-to-science",
)
load_button = gr.Button("Load URL")
with gr.Accordion("2. Select a content-generation model", open=True):
with gr.Row():
text_generation_model = gr.Dropdown(choices=AZURE_OPENAI_MODEL, label="Text-generation model")
image_generation_model = gr.Dropdown(choices=["Dall-e", "Stable Diffusion"], label="Image-generation model")
generate_button = gr.Button("Random generation")
with gr.Accordion("3. Replace any terms", open=True):
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.Column(scale=1):
with gr.Accordion("Generated News Contents"):
detection_button = gr.Button("Check for fake news")
news_title = gr.Textbox(label="Title", value="")
news_image = gr.Image(label="Image")
news_content = gr.Textbox(label="Content", value="", lines=12)
# FAKE NEWS ANALYSIS REPORT
with gr.Column(scale=1):
with gr.Accordion("Fake News Analysis"):
html_out = gr.HTML()
detailed_analysis_button = gr.Button("Show detailed analysis...")
# 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_button.click(generate_content,
inputs=[text_generation_model, image_generation_model, news_title, news_content],
outputs=[news_title, news_content])
detection_button.click(generate_analysis_report,
inputs=[news_title, news_content, news_image],
outputs=html_out)
detailed_analysis_button.click(show_detailed_analysis,
inputs=[news_title],
outputs=[html_out])
# change Image
#url_input.change(load_image, inputs=url_input, outputs=image_view)
demo.launch() |