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import gradio as gr
import spacy
import networkx as nx
# Load your NLP model and graphs
nlp = spacy.load("en_core_web_sm")
G_unreliable = nx.read_graphml('knowledge_graph.graphml')
G_reliable = nx.read_graphml('knowledge_graph_G1.graphml')
def analyze_misinformation(sentence):
misinformation, corrections = analyze_misinformation(sentence, nlp, G_unreliable, G_reliable)
return {"Misinformation": misinformation, "Corrections": corrections if corrections else "No corrections needed"}
interface = gr.Interface(fn=analyze_misinformation,
inputs="text",
outputs=["json"],
title="Misinformation Detection Demo",
description="Detects whether a sentence is likely to contain misinformation.")
if __name__ == "__main__":
interface.launch()
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