gradio.py

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()