Create gradio.py

gradio.py

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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()